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Sökning: WFRF:(Antfolk Christian)

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1.
  • Antfolk, Christian, et al. (författare)
  • Transfer of tactile input from an artificial hand to the forearm: experiments in amputees and able-bodied volunteers
  • 2013
  • Ingår i: Disability and Rehabilitation: Assistive Technology. - : Informa UK Limited. - 1748-3115 .- 1748-3107. ; 8:3, s. 249-254
  • Tidskriftsartikel (refereegranskat)abstract
    • Abstract in UndeterminedPurpose:This study explores the possibilities of transferring peripheral tactile stimulations from an artificial hand to the forearm skin.Method:A tactile display applied to the forearm skin was used to transfer tactile input to the forearm from various locations on a hand displayed on a computer screen. Discernment of location, levels of pressure and a combination of the two in simulated functional grips was tested to quantify the participants' ability to accurately perceive the tactile stimulations presented. Ten participants (5 forearm amputees and 5 able-bodied volunteers) unfamiliar with the equipment participated in the three-stage experiments comprising a learning session with vision, a reinforced learning session without vision and a validation session without vision.Results:The location discernment accuracy was high in both groups (75.2% and 89.6% respectively). The capacity to differentiate between three different levels of pressure was also high (91.7% and 98.1% respectively in the two groups). Recognition of simulated grip was slightly more difficult with the groups scoring 58.7% and 68.0% respectively for accuracy in the validation session.Conclusions:This study demonstrates that it is possible, following a brief training period, to transfer tactile input from an artificial hand to the forearm skin. The level of accuracy was lower for the more complex task, simulated grip recognition, possibly because this represents a more complex task requiring higher order brain functions. These results could form the basis for developing sensory feedback in hand prostheses. [Box: see text].
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2.
  • Cipriani, Christian, et al. (författare)
  • A novel concept for a prosthetic hand with bidirectional non-invasive interface: a feasibility study
  • 2009
  • Ingår i: IEEE Transactions on Biomedical Engineering. - 1558-2531. ; 56:11, s. 2739-2743
  • Tidskriftsartikel (refereegranskat)abstract
    • Abstract in Undetermined A conceptually novel prosthesis consisting of a mechatronic hand, an electromyographic classifier, and a tactile display has been developed and evaluated by addressing problems related to controllability in prosthetics: intention extraction, perception, and feeling of ownership. Experiments have been performed, and encouraging results for a young transradial amputee are reported.
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3.
  • Antfolk, Christian, et al. (författare)
  • A Tactile Display System for Hand Prostheses to Discriminate Pressure and Individual Finger Localization
  • 2010
  • Ingår i: Journal of Medical and Biological Engineering. - : Taiwanese Society of Biomedical Engineering. - 1609-0985. ; 30:6, s. 355-359
  • Tidskriftsartikel (refereegranskat)abstract
    • No current commercially available myoelectrically controlled prosthetic hands provide conscious sensory feedback to the user. A system aiming at relocation of sensory input from a prosthetic hand equipped with force sensors to the forearm skin of amputees, a tactile display, has been developed and constructed. The system consists of five piezoresistive force sensors or, alternatively, a prosthetic hand equipped with force sensors, five digital servomotors with a lever and a circular plastic disk pushing on the skin, control electronics based on an MSP430 microcontroller and a test application implemented in LabVIEW running on a PC. The tactile display system is intended to be integrated into the socket of a hand prosthesis and used as a conscious sensory feedback system for hand amputees using a myoelectrically controlled hand prosthesis. The system will provide continuous force feedback from sensors in the fingertips of each prosthetic finger and will likely improve the users' controllability and perception of the prosthetic hand. Here we report on tests made on "a five site" localization discrimination task and three pressure level discrimination tasks on the forearm of five healthy participants (non-amputees) using the LabView application to generate the stimulations. A mean five-finger discrimination accuracy of 86% and a mean three-level pressure discrimination accuracy of 93% were achieved, indicating the system to be a viable method of producing sensory feedback on the level of individual fingers.
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4.
  • Antfolk, Christian, et al. (författare)
  • Artificial Redirection of Sensation From Prosthetic Fingers to the Phantom Hand Map on Transradial Amputees: Vibrotactile Versus Mechanotactile Sensory Feedback
  • 2013
  • Ingår i: IEEE Transactions on Neural Systems and Rehabilitation Engineering. - 1534-4320. ; 21:1, s. 112-120
  • Tidskriftsartikel (refereegranskat)abstract
    • This work assesses the ability of transradial amputees to discriminate multi-site tactile stimuli in sensory discrimination tasks. It compares different sensory feedback modalities using an artificial hand prosthesis in: 1) a modality matched paradigm where pressure recorded on the five fingertips of the hand was fed back as pressure stimulation on five target points on the residual limb; and 2) a modality mismatched paradigm where the pressures were transformed into mechanical vibrations and fed back. Eight transradial amputees took part in the study and were divided in two groups based on the integrity of their phantom map; group A had a complete phantom map on the residual limb whereas group B had an incomplete or nonexisting map. The ability in localizing stimuli was compared with that of 10 healthy subjects using the vibration feedback and 11 healthy subjects using the pressure feedback (in a previous study), on their forearms, in similar experiments. Results demonstrate that pressure stimulation surpassed vibrotactile stimulation in multi-site sensory feedback discrimination. Furthermore, we demonstrate that subjects with a detailed phantom map had the best discrimination performance and even surpassed healthy participants for both feedback paradigms whereas group B had the worst performance overall. Finally, we show that placement of feedback devices on a complete phantom map improves multi-site sensory feedback discrimination, independently of the feedback modality.
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5.
  • Antfolk, Christian, et al. (författare)
  • Design and technical construction of a tactile display for sensory feedback in a hand prosthesis system
  • 2010
  • Ingår i: BioMedical Engineering Online. - 1475-925X. ; 9
  • Tidskriftsartikel (refereegranskat)abstract
    • Background: The users of today's commercial prosthetic hands are not given any conscious sensory feedback. To overcome this deficiency in prosthetic hands we have recently proposed a sensory feedback system utilising a "tactile display" on the remaining amputation residual limb acting as man-machine interface. Our system uses the recorded pressure in a hand prosthesis and feeds back this pressure onto the forearm skin. Here we describe the design and technical solution of the sensory feedback system aimed at hand prostheses for trans-radial/humeral amputees. Critical parameters for the sensory feedback system were investigated. Methods: A sensory feedback system consisting of five actuators, control electronics and a test application running on a computer has been designed and built. Firstly, we investigate which force levels were applied to the forearm skin of the user while operating the sensory feedback system. Secondly, we study if the proposed system could be used together with a myoelectric control system. The displacement of the skin caused by the sensory feedback system would generate artefacts in the recorded myoelectric signals. Accordingly, EMG recordings were performed and an analysis of the these are included. The sensory feedback system was also preliminarily evaluated in a laboratory setting on two healthy non-amputated test subjects with a computer generating the stimuli, with regards to spatial resolution and force discrimination. Results: We showed that the sensory feedback system generated approximately proportional force to the angle of control. The system can be used together with a myoelectric system as the artefacts, generated by the actuators, were easily removed using a simple filter. Furthermore, the application of the system on two test subjects showed that they were able to discriminate tactile sensation with regards to spatial resolution and level of force. Conclusions: The results of these initial experiments in non-amputees indicate that the proposed tactile display, in its simple form, can be used to relocate tactile input from an artificial hand to the forearm and that the system can coexist with a myoelectric control systems. The proposed system may be a valuable addition to users of myoelectric prosthesis providing conscious sensory feedback during manipulation of objects.
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6.
  • Antfolk, Christian, et al. (författare)
  • Exploring the conditions for PhD-students to develop abilities to independently formulate research questions
  • 2015
  • Rapport (populärvet., debatt m.m.)abstract
    • Developing an ability to independently formulate research questions is an important goal in doctoral education. During a seminar in the “Docent course”, accredited by Genombrottet at Lund University, the authors behind this paper ended up in a discussion on the actual conditions for developing such ability. During the discussions, the authors, based on their own experiences, identified several conditions that could hamper the PhD-students’ abilities to develop the skills required to independently formulate research questions. Examples of such conditions were: involvement in projects where objectives and deliverables already were stated by a funder, a lack of discussions with supervisors early in the PhD-process, and/or a lack of proper training. The authors also discussed if working with a compilation thesis automatically lead to contrived overall research questions, which resulted primarily as an afterthought at a very late stage in the process.
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7.
  • Antfolk, Christian, et al. (författare)
  • Sensory feedback in upper limb prosthetics.
  • 2013
  • Ingår i: Expert Review of Medical Devices. - : Informa UK Limited. - 1745-2422 .- 1743-4440. ; 10:1, s. 45-54
  • Tidskriftsartikel (refereegranskat)abstract
    • One of the challenges facing prosthetic designers and engineers is to restore the missing sensory function inherit to hand amputation. Several different techniques can be employed to provide amputees with sensory feedback: sensory substitution methods where the recorded stimulus is not only transferred to the amputee, but also translated to a different modality (modality-matched feedback), which transfers the stimulus without translation and direct neural stimulation, which interacts directly with peripheral afferent nerves. This paper presents an overview of the principal works and devices employed to provide upper limb amputees with sensory feedback. The focus is on sensory substitution and modality matched feedback; the principal features, advantages and disadvantages of the different methods are presented.
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8.
  • Antfolk, Christian, et al. (författare)
  • SmartHand tactile display: A new concept for providing sensory feedback in hand prostheses.
  • 2010
  • Ingår i: Scandinavian Journal of Plastic and Reconstructive Surgery and Hand Surgery. - : Medical Journals Sweden AB. - 1651-2073. ; 44, s. 50-53
  • Tidskriftsartikel (refereegranskat)abstract
    • Abstract A major drawback with myoelectric prostheses is that they do not provide the user with sensory feedback. Using a new principle for sensory feedback, we did a series of experiments involving 11 healthy subjects. The skin on the volar aspect of the forearm was used as the target area for sensory input. Experiments included discrimination of site of stimuli and pressure levels at a single stimulation point. A tactile display based on digital servomotors with one actuating element for each of the five fingers was used as a stimulator on the forearm. The results show that the participants were able to discriminate between three fingers with an accuracy of 97%, between five fingers with an accuracy of 82%, and between five levels with an accuracy of 79%. The tactile display may prove a helpful tool in providing amputees with sensory feedback from a prosthetic hand by transferring tactile stimuli from the prosthetic hand to the skin at forearm level.
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9.
  • Antfolk, Christian, et al. (författare)
  • Using EMG for Real-time Prediction of Joint Angles to Control a Prosthetic Hand Equipped with a Sensory Feedback System
  • 2010
  • Ingår i: Journal of Medical and Biological Engineering. - : Taiwanese Society of Biomedical Engineering. - 1609-0985. ; 30:6, s. 399-405
  • Tidskriftsartikel (refereegranskat)abstract
    • All commercially available upper limb prosthesis controllers only allow the hand to be commanded in an open and close fashion without any sensory feedback to the user. Here the evaluation of a multi-degree of freedom hand controlled using a real-time EMG pattern recognition algorithm and incorporating a sensory feedback system is reported. The hand prosthesis, called SmartHand, was controlled in real-time by using 16 myoelectric signals from the residual limb of a 25-year old male transradial amputee in a two day long evaluation session. Initial training of the EMG pattern recognition algorithm was performed with a dataglove fitted to the contralateral hand recording joint angle positions of the fingers and mapping joint angles of the fingers to the EMG data. In the following evaluation sessions, the myoelectric signals were classified using local approximation and lazy learning, producing finger joint angle outputs and consequently controlling the prosthetic hand. Sensory information recorded from force sensors in the artificial hand was relayed to actuators, integrated in the socket of the prosthesis, continuously delivering force sensory feedback stimulations to the stump of the amputee. The participant was able to perform several dextrous movements as well as functional grip tasks after only two hours of training and increased his controllability during the two day session. In the final evaluation session a mean classification accuracy of 86% was achieved.
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10.
  • Antfolk, Maria, et al. (författare)
  • A single inlet two-stage acoustophoresis chip enabling tumor cell enrichment from white blood cells
  • 2015
  • Ingår i: Lab on a Chip. - 1473-0189. ; 15:9, s. 2102-2109
  • Tidskriftsartikel (refereegranskat)abstract
    • Metastatic disease is responsible for most cancer deaths, and hematogenous spread through circulating tumor cells (CTC) is a prerequisite for tumor dissemination. CTCs may undergo epithelial–mesenchymal transition where many epithelial cell characteristics are lost. Therefore, CTC isolation systems relying on epithelial cell markers are at risk of losing important subpopulations of cells. Here, a simple acoustophoresis-based cell separation instrument is presented. Cells are uniquely separated while maintained in their initial suspending medium, thus eliminating the need for a secondary cell-free medium to hydrodynamically pre-position them before the separation. When characterizing the system using polystyrene particles, 99.6 ± 0.2% of 7 μm diameter particles were collected through one outlet while 98.8 ± 0.5% of 5 μm particles were recovered through a second outlet. Prostate cancer cells (DU145) spiked into blood were enriched from white blood cells at a sample flow rate of 100 μL min−1 providing 86.5 ± 6.7% recovery of the cancer cells with 1.1 ± 0.2% contamination of white blood cells. By increasing the acoustic intensity a recovery of 94.8 ± 2.8% of cancer cells was achieved with 2.2 ± 0.6% contamination of white blood cells. The single inlet approach makes this instrument insensitive to acoustic impedance mismatch; a phenomenon reported to importantly affect accuracy in multi-laminar flow stream acoustophoresis. It also offers a possibility of concentrating the recovered cells in the chip, as opposed to systems relying on hydrodynamic pre-positioning which commonly dilute the target cells.
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11.
  • Cipriani, Christian, et al. (författare)
  • Online Myoelectric Control of a Dexterous Hand Prosthesis by Transradial Amputees
  • 2011
  • Ingår i: IEEE Transactions on Neural Systems and Rehabilitation Engineering. - 1534-4320. ; 19:3, s. 260-270
  • Tidskriftsartikel (refereegranskat)abstract
    • A real-time pattern recognition algorithm based on k-nearest neighbors and lazy learning was used to classify, voluntary electromyography (EMG) signals and to simultaneously control movements of a dexterous artificial hand. EMG signals were superficially recorded by eight pairs of electrodes from the stumps of five transradial amputees and forearms of five able-bodied participants and used online to control a robot hand. Seven finger movements (not involving the wrist) were investigated in this study. The first objective was to understand whether and to which extent it is possible to control continuously and in real-time, the finger postures of a prosthetic hand, using superficial EMG, and a practical classifier, also taking advantage of the direct visual feedback of the moving hand. The second objective was to calculate statistical differences in the performance between participants and groups, thereby assessing the general applicability of the proposed method. The average accuracy of the classifier was 79% for amputees and 89% for able-bodied participants. Statistical analysis of the data revealed a difference in control accuracy based on the aetiology of amputation, type of prostheses regularly used and also between able-bodied participants and amputees. These results are encouraging for the development of noninvasive EMG interfaces for the control of dexterous prostheses.
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12.
  • Farserotu, John, et al. (författare)
  • Smart Skin for tactile prosthetics
  • 2012
  • Ingår i: [Host publication title missing]. - 9781467312349 ; , s. 1-8
  • Konferensbidrag (refereegranskat)abstract
    • This paper provides an overview of a concept for a Smart Skin, for enabling tactile prosthetics that provide for a natural sensation of touch. The solution embeds miniature, ultra-low power, wireless sensors into the silicone coating of the prosthetic. The solution offers advantages in terms of scalability, ability to place the sensors almost anywhere, fault tolerance and potential ease of manufacturing.
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13.
  • Huang, Huaiqi, et al. (författare)
  • Automatic hand phantom map detection methods
  • 2015
  • Ingår i: IEEE Biomedical Circuits and Systems Conference: Engineering for Healthy Minds and Able Bodies, BioCAS 2015 - Proceedings. - 9781479972333
  • Konferensbidrag (refereegranskat)abstract
    • Many amputees have maps of referred sensation from their missing hand on their residual limb (phantom maps). This skin area can serve as a target for providing amputees with tactile sensory feedback. Providing tactile feedback on the phantom map can improve the object manipulation ability, enhance embodiment of myoelectric prostheses users and help reduce phantom limb pain. The distribution of the phantom map varies with the individual. Here, we investigate a fast and accurate method for hand phantom map shape detection. We present three elementary (group testing, adaptive edge finding and support vector machines (SVM)) and two combined methods (SVM with majority-pooling and SVM with active learning) tested with different types of phantom map models and compare the classification error rates. The results show that SVM with majority-pooling has the smallest classification error rate.
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14.
  • Huang, Huaiqi, et al. (författare)
  • Automatic hand phantom map generation and detection using decomposition support vector machines
  • 2018
  • Ingår i: BioMedical Engineering Online. - : Springer Science and Business Media LLC. - 1475-925X. ; 17:1
  • Tidskriftsartikel (refereegranskat)abstract
    • Background: There is a need for providing sensory feedback for myoelectric prosthesis users. Providing tactile feedback can improve object manipulation abilities, enhance the perceptual embodiment of myoelectric prostheses and help reduce phantom limb pain. Many amputees have referred sensation from their missing hand on their residual limbs (phantom maps). This skin area can serve as a target for providing amputees with non-invasive tactile sensory feedback. One of the challenges of providing sensory feedback on the phantom map is to define the accurate boundary of each phantom digit because the phantom map distribution varies from person to person. Methods: In this paper, automatic phantom map detection methods based on four decomposition support vector machine algorithms and three sampling methods are proposed, complemented by fuzzy logic and active learning strategies. The algorithms and methods are tested on two databases: the first one includes 400 generated phantom maps, whereby the phantom map generation algorithm was based on our observation of the phantom maps to ensure smooth phantom digit edges, variety, and representativeness. The second database includes five reported phantom map images and transformations thereof. The accuracy and training/ classification time of each algorithm using a dense stimulation array (with 100 $$\times $$ × 100 actuators) and two coarse stimulation arrays (with 3 $$\times $$ × 5 and 4 $$\times $$ × 6 actuators) are presented and compared. Results: Both generated and reported phantom map images share the same trends. Majority-pooling sampling effectively increases the training size, albeit introducing some noise, and thus produces the smallest error rates among the three proposed sampling methods. For different decomposition architectures, one-vs-one reduces unclassified regions and in general has higher classification accuracy than the other architectures. By introducing fuzzy logic to bias the penalty parameter, the influence of pooling-induced noise is reduced. Moreover, active learning with different strategies was also tested and shown to improve the accuracy by introducing more representative training samples. Overall, dense arrays employing one-vs-one fuzzy support vector machines with majority-pooling sampling have the smallest average absolute error rate (8.78% for generated phantom maps and 11.5% for reported and transformed phantom map images). The detection accuracy of coarse arrays was found to be significantly lower than for dense array. Conclusions: The results demonstrate the effectiveness of support vector machines using a dense array in detecting refined phantom map shapes, whereas coarse arrays are unsuitable for this task. We therefore propose a two-step approach, using first a non-wearable dense array to detect an accurate phantom map shape, then to apply a wearable coarse stimulation array customized according to the detection results. The proposed methodology can be used as a tool for helping haptic feedback designers and for tracking the evolvement of phantom maps.
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15.
  • Huang, Huaiqi, et al. (författare)
  • EMG pattern recognition using decomposition techniques for constructing multiclass classifiers
  • 2016
  • Ingår i: 2016 6th IEEE International Conference on Biomedical Robotics and Biomechatronics, BioRob 2016. - 9781509032877 ; , s. 1296-1301
  • Konferensbidrag (refereegranskat)abstract
    • To improve the dexterity of multi-functional myoelectric prosthetic hand, more accurate hand gesture recognition based on surface electromyographic (sEMG) signal is needed. This paper evaluates two types of time-domain EMG features, one independent feature and one combined feature including four features. The selected features from eight subjects with 13 finger movements were tested with four decomposed multi-class support vector machines (SVM), four decomposed linear discriminant analyses (LDA) and a multi-class LDA. The classification accuracy, training, and classification time are compared. The results have shown that the combined features decrease error rate, and binary tree based decomposition multiclass classifiers yield the highest classification success rate (88.2%) with relatively low training and classification time.
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16.
  • Huang, Huaiqi, et al. (författare)
  • Experiment and investigation of two types of vibrotactile devices
  • 2016
  • Ingår i: 2016 6th IEEE International Conference on Biomedical Robotics and Biomechatronics, BioRob 2016. - 9781509032884 - 9781509032877 ; , s. 1266-1271
  • Konferensbidrag (refereegranskat)abstract
    • Tactile displays have a wide range of applications in assistive technology, prosthetics, and rehabilitation. Vibrotactile stimulation shows potential to be integrated into wearable devices because of its small size, low power consumption, and relative fast responding speed. In this paper, experiments investigating vibrotactile minimal detectable level, just noticeable difference, and two point discrimination distance using eccentric rotating mass (ERM) and linear resonant actuator (LRA) are described and the results were analyzed. LRAs have shown potential to transmit binary information, while ERMs are more suitable for conveying more complexed signals. For both LRAs and ERMs, it is difficult to for subjects to correctly distinguish two points within 45 mm.
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17.
  • Huang, Huaiqi, et al. (författare)
  • Multi-modal sensory feedback system for upper limb amputees
  • 2017
  • Ingår i: Proceedings - 2017 1st New Generation of CAS, NGCAS 2017. - 9781509064472 ; , s. 193-196
  • Konferensbidrag (refereegranskat)abstract
    • Providing sensory feedback for myoelectric prosthetic users can not only increase the manipulation ability but can also introduce a feeling of embodiment. Previous research has demonstrated the feasibility of providing mechanotactile or vibrotactile feedback on the remaining stumps of amputees. To improve the recognition rate and reduce mental work load when identifying stimulation patterns, we propose a multi-modal sensory feedback system for upper limb amputees. The system consists of five tactile sensors, Bluetooth wireless communication modules, and a custom-designed multi-modal stimulation array incorporating vibrotactile and mechanotactile stimulation modalities. Three amputees (two with phantom map and one without phantom map) tested the system in localization and stimulation intensity identification tasks. Experimental results show the effectiveness of the multi-modal stimulation compared with single modal stimulation. To the best of our knowledge, this is the first attempt to combine vibrotactile and mechanotactile stimulation in a sensory feedback system for upper limb amputees.
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18.
  • Kanitz, Gunter, et al. (författare)
  • Decoding of individuated finger movements using surface EMG and input optimization applying a genetic algorithm.
  • 2011
  • Ingår i: [Host publication title missing]. - 1557-170X. - 9781424441211 ; , s. 1608-1611
  • Konferensbidrag (refereegranskat)abstract
    • In this paper we present surface electromyographic (EMG) data collected from 16 channels on five unimpaired subjects and one transradial amputee performing 12 individual finger movements and a rest class. EMG were processed using a traditional Time Domain feature-set and classifiers: a Linear Discriminant Analysis (LDA) a k-Nearest Neighbors (k-NN) and Support Vector Machine (SVM). Using continuous datasets we show that it is possible to achieve an accuracy up to 80% across subjects. Thereafter possibilities to reduce the numbers of channels physically required, as well as the number of features have been investigated by means of a developed Genetic Algorithm (GA) that included a bonus system to reward eliminated features and channels. The classification was performed firstly on the full datasets and in later runs using the GA. The GA demonstrated high redundancy in the recorded 16 channel data as well as the insignificance of certain features. Although the GA optimization yielded to reduce 8 to 11 channels depending on the subject, such reduction had little to no effect on the classification accuracies.
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19.
  • Malesevic, Nebojsa, et al. (författare)
  • A database of multi-channel intramuscular electromyogram signals during isometric hand muscles contractions
  • 2020
  • Ingår i: Scientific Data. - : Springer Science and Business Media LLC. - 2052-4463. ; 7:1
  • Tidskriftsartikel (refereegranskat)abstract
    • Hand movement is controlled by a large number of muscles acting on multiple joints in the hand and forearm. In a forearm amputee the control of a hand prosthesis is traditionally depending on electromyography from the remaining forearm muscles. Technical improvements have made it possible to safely and routinely implant electrodes inside the muscles and record high-quality signals from individual muscles. In this study, we present a database of intramuscular EMG signals recorded with fine-wire electrodes alongside recordings of hand forces in an isometric setup and with the addition of spike-sorted metadata. Six forearm muscles were recorded from twelve able-bodied subjects and nine forearm muscles from two subjects. The fully automated recording protocol, based on command cues, comprised a variety of hand movements, including some requiring slowly increasing/decreasing force. The recorded data can be used to develop and test algorithms for control of a prosthetic hand. Assessment of the signals was done in both quantitative and qualitative manners.
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20.
  • Malešević, Nebojša, et al. (författare)
  • Decoding of individual finger movements from surface EMG signals using vector autoregressive hierarchical hidden Markov models (VARHHMM)
  • 2017
  • Ingår i: 2017 International Conference on Rehabilitation Robotics, ICORR 2017. - 9781538622964 ; , s. 1518-1523
  • Konferensbidrag (refereegranskat)abstract
    • In this paper we present a novel method for predicting individual fingers movements from surface electromyography (EMG). The method is intended for real-time dexterous control of a multifunctional prosthetic hand device. The EMG data was recorded using 16 single-ended channels positioned on the forearm of healthy participants. Synchronously with the EMG recording, the subjects performed consecutive finger movements based on the visual cues. Our algorithm could be described in following steps: extracting mean average value (MAV) of the EMG to be used as the feature for classification, piece-wise linear modeling of EMG feature dynamics, implementation of hierarchical hidden Markov models (HHMM) to capture transitions between linear models, and implementation of Bayesian inference as the classifier. The performance of our classifier was evaluated against commonly used real-time classifiers. The results show that the current algorithm setup classifies EMG data similarly to the best among tested classifiers but with equal or less computational complexity.
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21.
  • Malešević, Nebojša, et al. (författare)
  • Instrumented platform for assessment of isometric hand muscles contractions
  • 2019
  • Ingår i: Measurement Science and Technology. - : IOP Publishing. - 0957-0233 .- 1361-6501. ; 30:6
  • Tidskriftsartikel (refereegranskat)abstract
    • Measurement of forces exerted by a human hand while performing common gestures is a highly valuable task for assessment of neurorehabilitation and neurological disorders, but also, for control of movement that could be directly transferred to assistive devices. Even though accurate and selective multi-joint measurement of hand forces is desirable in both clinical and research applications there is no commercially available device able to perform such measurements. Moreover, the custom-made systems used in research commonly impose limitations, such as availability of only single, predefined hand aperture. Furthermore, there is no consensus on design requirements for custom made measurement systems that would enable comparison of results obtained during research or clinical hand function studies. In an attempt to provide a possible solution for a device capable of multi-joint hand forces measurement and disseminate it to the research community, this paper presents the mechanical and electronic design of an instrumented platform for assessment of isometric hand muscles contractions. Some of the key features related to the developed system are: flexibility in placing the hand/fingers, fast and easy hand fitting, adjustability to different lengths, circumferences and postures of the digits, and the possibility to register individual bidirectional forces from the digits and the wrist. The accuracy of isometric force measurements was evaluated in a controlled test with the reference high accuracy force gauge device during which the developed system showed high linearity (R 2 = 0.9999). As the more realistic test, the device was evaluated when force was applied to individual sensors but also during the intramuscular electromyography (iEMG) study. The data gathered during the iEMG measurements was thoroughly assessed to obtain three appropriate metrics; the first estimating crosstalk between individual force sensors; the second evaluating agreement between measured forces and forces estimated through iEMG; and the third providing qualitative evaluation of hand force in respect to activations of individual muscle units. The results of these analyses performed on multiple joint forces show agreement with previously published results, but with the difference that in that case, the measurement was performed with a single degree of freedom device.
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22.
  • Malešević, Nebojša, et al. (författare)
  • Vector Autoregressive Hierarchical Hidden Markov Models for Extracting Finger Movements Using Multichannel Surface EMG Signals
  • 2018
  • Ingår i: Complexity. - : Hindawi Limited. - 1076-2787 .- 1099-0526. ; 2018
  • Tidskriftsartikel (refereegranskat)abstract
    • We present a novel computational technique intended for the robust and adaptable control of a multifunctional prosthetic hand using multichannel surface electromyography. The initial processing of the input data was oriented towards extracting relevant time domain features of the EMG signal. Following the feature calculation, a piecewise modeling of the multidimensional EMG feature dynamics using vector autoregressive models was performed. The next step included the implementation of hierarchical hidden semi-Markov models to capture transitions between piecewise segments of movements and between different movements. Lastly, inversion of the model using an approximate Bayesian inference scheme served as the classifier. The effectiveness of the novel algorithms was assessed versus methods commonly used for real-time classification of EMGs in a prosthesis control application. The obtained results show that using hidden semi-Markov models as the top layer, instead of the hidden Markov models, ranks top in all the relevant metrics among the tested combinations. The choice of the presented methodology for the control of prosthetic hand is also supported by the equal or lower computational complexity required, compared to other algorithms, which enables the implementation on low-power microcontrollers, and the ability to adapt to user preferences of executing individual movements during activities of daily living.
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23.
  • Rosén, Birgitta, et al. (författare)
  • Referral of sensation to an advanced humanoid robotic hand prosthesis.
  • 2009
  • Ingår i: Scandinavian Journal of Plastic and Reconstructive Surgery and Hand Surgery. - : Informa UK Limited. - 1651-2073 .- 0284-4311. ; 43:5, s. 260-266
  • Tidskriftsartikel (refereegranskat)abstract
    • Hand prostheses that are currently available on the market are used by amputees to only a limited extent, partly because of lack of sensory feedback from the artificial hand. We report a pilot study that showed how amputees can experience a robot-like advanced hand prosthesis as part of their own body. We induced a perceptual illusion by which touch applied to the stump of the arm was experienced from the artificial hand. This illusion was elicited by applying synchronous tactile stimulation to the hidden amputation stump and the robotic hand prosthesis in full view. In five people who had had upper limb amputations this stimulation caused referral touch sensation from the stump to the artificial hand, and the prosthesis was experienced more like a real hand. We also showed that this illusion can work when the amputee controls the movements of the artificial hand by recordings of the arm muscle activity with electromyograms. These observations indicate that the previously described "rubber hand illusion" is also valid for an advanced hand prosthesis, even when it has a robotic-like appearance.
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24.
  • Abbaspour, Sara, 1984- (författare)
  • Electromyogram Signal Enhancement and Upper-Limb Myoelectric Pattern Recognition
  • 2019
  • Doktorsavhandling (övrigt vetenskapligt/konstnärligt)abstract
    • Losing a limb causes difficulties in our daily life. To regain the ability to live an independent life, artificial limbs have been developed. Hand prostheses belong to a group of artificial limbs that can be controlled by the user through the activity of the remnant muscles above the amputation. Electromyogram (EMG) is one of the sources that can be used for control methods for hand prostheses. Surface EMGs are powerful, non-invasive tools that provide information about neuromuscular activity of the subjected muscle, which has been essential to its use as a source of control for prosthetic limbs. However, the complexity of this signal introduces a big challenge to its applications. EMG pattern recognition to decode different limb movements is an important advancement regarding the control of powered prostheses. It has the potential to enable the control of powered prostheses using the generated EMG by muscular contractions as an input. However, its use has yet to be transitioned into wide clinical use. Different algorithms have been developed in state of the art to decode different movements; however, the challenge still lies in different stages of a successful hand gesture recognition and improvements in these areas could potentially increase the functionality of powered prostheses. This thesis firstly focuses on improving the EMG signal’s quality by proposing novel and advanced filtering techniques. Four efficient approaches (adaptive neuro-fuzzy inference system-wavelet, artificial neural network-wavelet, adaptive subtraction and automated independent component analysis-wavelet) are proposed to improve the filtering process of surface EMG signals and effectively eliminate ECG interferences. Then, the offline performance of different EMG-based recognition algorithms for classifying different hand movements are evaluated with the aim of obtaining new myoelectric control configurations that improves the recognition stage. Afterwards, to gain proper insight on the implementation of myoelectric pattern recognition, a wide range of myoelectric pattern recognition algorithms are investigated in real time. The experimental result on 15 healthy volunteers suggests that linear discriminant analysis (LDA) and maximum likelihood estimation (MLE) outperform other classifiers. The real-time investigation illustrates that in addition to the LDA and MLE, multilayer perceptron also outperforms the other algorithms when compared using classification accuracy and completion rate.
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25.
  • Alriksson-Schmidt, Ann, et al. (författare)
  • Improving the Health of Individuals With Cerebral Palsy: Protocol for the Multidisciplinary Research Program MOVING ON WITH CP
  • 2019
  • Ingår i: Jmir Research Protocols. - Toronto, Canada : JMIR Publications Inc.. - 1929-0748. ; 8:10
  • Tidskriftsartikel (refereegranskat)abstract
    • Background: Cerebral palsy (CP) is one of the most common early onset disabilities globally. The causative brain damage in CP is nonprogressive, yet secondary conditions develop and worsen over time. Individuals with CP in Sweden and most of the Nordic countries are systematically followed in the national registry and follow-up program entitled the Cerebral Palsy Follow-Up Program (CPUP). CPUP has improved certain aspects of health care for individuals with CP and strengthened collaboration among professionals. However, there are still issues to resolve regarding health care for this specific population. Objective: The overall objectives of the research program MOVING ON WITH CP are to (1) improve the health care processes and delivery models; (2) develop, implement, and evaluate real-life solutions for Swedish health care provision; and (3) evaluate existing health care and social insurance benefit programs and processes in the context of CP. Methods: MOVING ON WITH CP comprises 9 projects within 3 themes. Evaluation of Existing Health Care (Theme A) consists of registry studies where data from CPUP will be merged with national official health databases, complemented by survey and interview data. In Equality in Health Care and Social Insurance (Theme B), mixed methods studies and registry studies will be complemented with focus group interviews to inform the development of new processes to apply for benefits. In New Solutions and Processes in Health Care Provision (Theme C), an eHealth (electronic health) procedure will be developed and tested to facilitate access to specialized health care, and equipment that improves the assessment of movement activity in individuals with CP will be developed. Results: The individual projects are currently being planned and will begin shortly. Feedback from users has been integrated. Ethics board approvals have been obtained. Conclusions: In this 6-year multidisciplinary program, professionals from the fields of medicine, social sciences, health sciences, and engineering, in collaboration with individuals with CP and their families, will evaluate existing health care, create conditions for a more equal health care, and develop new technologies to improve the health care management of people with CP.
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26.
  • Antfolk, Christian (författare)
  • On sensory feedback in hand prostheses
  • 2012
  • Doktorsavhandling (övrigt vetenskapligt/konstnärligt)abstract
    • Amputation of the hand implies the loss of the ability to grasp and the ability to "feel". The grasping function can be primitively restored using an active prosthesis. Multi­articulating electrically powered hands have recently made their way to the market and these hands provide enhanced grasping and gripping capabilities. However, these hands provide no direct and conscious sensory feedback to the user and there are ongoing research efforts in providing prosthetic hands with a sense of touch. There is no commercially available system for artificial limbs today that provides the user with conscious sensory feedback. This thesis presents the development and experimental studies of a new concept for providing users of prosthetic hands with a conscious sensory feedback. Previous studies have mostly relied on "sensory substitution" methods where sensory feedback is delivered in a different modality or to a different location on the body. By using modality matched sensory feedback, e.g. if pressure is sensed at a prosthetic finger then pressure is fed back to the amputee, the amputee would not have to learn to interpret the feedback signal (e.g. pressure coded as vibrations). Furthermore, many amputees experience a phantom "hand map" in their residual limb and when specific areas of this map is stimulated, the stimuli is perceived as coming from specific fingers in the amputated hand. By utilizing the phantom "hand map", amputees can be provided with modality matched sensory feedback, delivered to the "correct" body location and activating the correct location in the somatosensory cortex. In several studies, feedback actuators in the form of digital servomotors or air­mediated pressure bulbs were used to provide both non­amputees and amputees with sensory feedback. It was shown that amputees can learn to interpret sensory feedback on different locations and that the developed sensory feedback system would not interfere negatively with a myoelectric control system. Furthermore, it was shown that the use of modality matched feedback in a multi­site discrimination task yielded better results than modality mismatched sensory feedback. In conclusion, the studies indicate that this new concept for sensory feedback in hand prostheses can be useful in future artificial hands and enhance the sense of body ownership of the prosthesis.
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27.
  • Antfolk, Christian, et al. (författare)
  • Sensory feedback from a prosthetic hand based on air-mediated pressure from the hand to the forearm skin.
  • 2012
  • Ingår i: Journal of rehabilitation medicine : official journal of the UEMS European Board of Physical and Rehabilitation Medicine. - : Medical Journals Sweden AB. - 1651-2081. ; 44:8, s. 702-707
  • Tidskriftsartikel (refereegranskat)abstract
    • Objective: Lack of sensory feedback is a drawback in today's hand prostheses. We present here a non-invasive simple sensory feedback system, which provides the user of a prosthetic hand with sensory feedback on the arm stump. It is mediated by air in a closed loop system connecting silicone pads on the prosthetic hand with pads on the amputation stump. The silicone pads in a "tactile display" on the amputation stump expand when their corresponding sensor-bulb in the prosthesis is touched, evoking an experience of "real touch". Methods: Twelve trans-radial amputees and 20 healthy non-amputees participated in the study. We investigated the capacity of the system to mediate detection of touch, discrimination between different levels of pressure and, on the amputees also, the ability to locate touch. Results: The results showed a median touch threshold of 80 and 60 g in amputees and non-amputees, respectively, and 90% and 80% correct answers, respectively, in discrimination between 2 levels of pressure. The amputees located touch (3 sites) correctly in 96% of trials. Conclusion: This simple sensory feedback system has the potential to restore sensory feedback in hand amputees and thus it could be a useful tool to enhance prosthesis use.
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28.
  • Björkman, Anders, et al. (författare)
  • Sensory qualities of the phantom hand map in the residual forearm of amputees
  • 2016
  • Ingår i: Journal of Rehabilitation Medicine. - : Medical Journals Sweden AB. - 1651-2081 .- 1650-1977. ; 48:4, s. 70-365
  • Tidskriftsartikel (refereegranskat)abstract
    • OBJECTIVE: Most amputees experience referred sensations, known as a phantom hand map, on the residual forearm, where touch on specific areas is perceived as touch on the amputated hand. The aim of this study was to evaluate the sensory qualities of the phantom hand map.METHODS: In 10 traumatic forearm-amputees touch thres-holds and discriminative touch of the phantom hand map were assessed and compared with corresponding areas on the contralateral forearm. The study assessed the localization of touch on the phantom hand map, and how distinct and similar to normal touch the referred feeling was.RESULTS: Similar touch thresholds were seen in the phantom hand map and the control site. Tactile discrimination, requiring both detection of stimulus and interpretation, was significantly better in the phantom hand map.CONCLUSION: This explorative study suggests that the phantom hand map and the superior tactile discrimination seen in the phantom hand map are based on adaptations within the brain. Further studies investigating the neural basis for the phantom hand map are needed.
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29.
  • Grenvall, Carl, et al. (författare)
  • Two-dimensional acoustic particle focusing enables sheathless chip Coulter counter with planar electrode configuration.
  • 2014
  • Ingår i: Lab on a Chip. - : Royal Society of Chemistry (RSC). - 1473-0189. ; 14:24, s. 4629-4637
  • Tidskriftsartikel (refereegranskat)abstract
    • The field of cytometry has grown in scope and importance ever since the early 20th century with leaps in technology introducing the Coulter counter and the flow cytometer. Cytometry methods have brought about a revolution for the medical and biotechnology industry by providing fast and accurate analysis of cell and particle suspensions. Recent developments in the field aim at improving current cytometers and to provide miniaturized low-cost cytometry systems for point-of-care clinical diagnostics or research. In an attempt to address the need for particle positioning which is important for both impedance and optically based cytometers we present a microfluidic system which precisely positions cells and particles, using acoustic forces and subsequently performs measurements using an integrated and simple planar electrode Coulter-type impedance cytometer without the need for sheath flows. Data is presented to show how the acoustic method improves the accuracy of the impedance cytometer when prefocusing is employed to particles and cells (diluted whole blood). Confocal imaging and simulations support the findings and provide the basis for further improvements. The acoustophoretic prefocusing technique opens a path towards small, low cost cytometers while also providing an easy way to improve current systems.
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30.
  • Jones, Benedict C, et al. (författare)
  • To which world regions does the valence-dominance model of social perception apply?
  • 2021
  • Ingår i: Nature Human Behaviour. - : Springer Science and Business Media LLC. - 2397-3374. ; 5:1, s. 159-169
  • Tidskriftsartikel (refereegranskat)abstract
    • Over the past 10 years, Oosterhof and Todorov's valence-dominance model has emerged as the most prominent account of how people evaluate faces on social dimensions. In this model, two dimensions (valence and dominance) underpin social judgements of faces. Because this model has primarily been developed and tested in Western regions, it is unclear whether these findings apply to other regions. We addressed this question by replicating Oosterhof and Todorov's methodology across 11 world regions, 41 countries and 11,570 participants. When we used Oosterhof and Todorov's original analysis strategy, the valence-dominance model generalized across regions. When we used an alternative methodology to allow for correlated dimensions, we observed much less generalization. Collectively, these results suggest that, while the valence-dominance model generalizes very well across regions when dimensions are forced to be orthogonal, regional differences are revealed when we use different extraction methods and correlate and rotate the dimension reduction solution. PROTOCOL REGISTRATION: The stage 1 protocol for this Registered Report was accepted in principle on 5 November 2018. The protocol, as accepted by the journal, can be found at https://doi.org/10.6084/m9.figshare.7611443.v1 .
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31.
  • Kizyte, Asta, 1993- (författare)
  • High-Density Electromyography-Based Methods for Joint Torque Prediction and Motor Unit Behavior Observation
  • 2023
  • Licentiatavhandling (övrigt vetenskapligt/konstnärligt)abstract
    • Electromyography (EMG) is a technique that measures the electrical activity of muscles. It reflects muscle activation and provides an interface to the central nervous system at the level of the muscle or individual motor units, which helps us understand the mechanisms of muscle force production, control, and coordination. EMG can also be used to detect changes in muscle activity caused by pathology, making it a valuable tool for research, diagnosis, and rehabilitation. One of the latest advancements in EMG technology is high-density EMG (HD-EMG). HD-EMG measures multiple spatially separated samples of muscle activation. This additional spatial information in HD-EMG offers new possibilities for the prediction of joint torques and the ability to look into individual motor units by decomposing the signals using blind source separation methods. This thesis presents two studies that explore the use of HD-EMG methods for joint torque estimation and the observation of motor unit behavior. In the first paper, we presented a detailed investigation of the effects of different EMG and kinematic inputs on the accuracy and robustness of ankle joint torque prediction using support vector regression. To evaluate the robustness, we analyzed the results in three cases (intra-session, inter-subject, and inter-session) and two movement categories (isometric contraction and dynamic movement). We found that HD-EMG-derived inputs improve the accuracy and robustness of torque prediction of the isometric contractions. However, in dynamic movements, good prediction results could only be achieved by including additional kinematic features (ankle joint position and angular velocity), and the type of EMG input did not strongly influence the results.In the second paper, we investigated the changes in motor unit behavior of the ankle plantar flexor (soleus) and dorsiflexor (tibialis anterior) caused by spinal cord injury (SCI). We computed torque, EMG, and motor unit parameters during volitional sub-maximal voluntary contractions for the SCI group and compared them to a non-injured control cohort. We found that participants in both groups could maintain the prescribed torque with similar variability. However, the SCI group required higher muscle activation levels (normalized to maximum) to achieve the same level of relative torque compared to the control group. The SCI group had lower intramuscular coherence in the alpha frequency band than the control group, indicating altered neural synchronization at the sub-cortical level. The soleus motor unit firing patterns were more variable post-SCI than in the control group. In addition, at high torque levels (50% of personal maximum), both muscle's motor units were recruited and de-recruited at lower torques, and motor units fired at lower rates in the tibialis anterior muscle in persons with SCI, indicating altered force gradation strategies after the injury.The studies presented in this thesis demonstrated that HD-EMG is suitable for robust isometric ankle joint torque prediction, which has potential in applications such as robot-assisted rehabilitation and robotic gait assistive technology. In particular, the robustness and accuracy of HD-EMG-based predictions are essential for improved estimation of the joint torque that can then be used in the human-in-the-loop control scheme. In addition, HD-EMG decomposition enables a non-invasive way to observe the motor unit behavior in vivo in persons with neuromusculoskeletal disorders, which can enhance the understanding of the underlying neurophysiological mechanisms of motor impairments. The insights provided by such HD-EMG analysis in the future may be beneficial for developing targeted interventions and personalized therapies.
  •  
32.
  • Li, Tao, et al. (författare)
  • Tactile display on the remaining hand for unilateral hand amputees
  • 2016
  • Ingår i: Current Directions in Biomedical Engineering. - : Walter de Gruyter GmbH. - 2364-5504. ; 2:1, s. 399-403
  • Tidskriftsartikel (refereegranskat)abstract
    • Human rely profoundly on tactile feedback from fingertips to interact with the environment, whereas most hand prostheses used in clinics provide no tactile feedback. In this study we demonstrate the feasibility to use a tactile display glove that can be worn by a unilateral hand amputee on the remaining healthy hand to display tactile feedback from a hand prosthesis. The main benefit is that users could easily distinguish the feedback for each finger, even without training. The claimed advantage is supported by preliminary tests with healthy subjects. This approach may lead to the development of effective and affordable tactile display devices that provide tactile feedback for individual fingertip of hand prostheses.
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33.
  • Liu, Jia, et al. (författare)
  • Analysis of modulations of mental fatigue on intra-individual variability from single-trial event related potentials
  • 2024
  • Ingår i: Journal of Neuroscience Methods. - 0165-0270. ; 406
  • Tidskriftsartikel (refereegranskat)abstract
    • Background: Intra-individual variability (IIV), a measure of variance within an individual's performance, has been demonstrated as metrics of brain responses for neural functionality. However, how mental fatigue modulates IIV remains unclear. Consequently, the development of robust mental fatigue detection methods at the single-trial level is challenging. New methods: Based on a long-duration flanker task EEG dataset, the modulations of mental fatigue on IIV were explored in terms of response time (RT) and trial-to-trial latency variations of event-related potentials (ERPs). Specifically, latency variations were quantified using residue iteration decomposition (RIDE) to reconstruct latency-corrected ERPs. We compared reconstructed ERPs with raw ERPs by means of temporal principal component analysis (PCA). Furthermore, a single-trial classification pipeline was developed to detect the changes of mental fatigue levels. Results: We found an increased IIV in the RT metric in the fatigue state compared to the alert state. The same sequence of ERPs (N1, P2, N2, P3a, P3b, and slow wave, or SW) was separated from both raw and reconstructed ERPs using PCA, whereas differences between raw and reconstructed ERPs in explained variances for separated ERPs were found owing to IIV. Particularly, a stronger N2 was detected in the fatigue than alert state after RIDE. The single-trial fatigue detection pipeline yielded an acceptable accuracy of 73.3%. Comparison with existing methods: The IIV has been linked to aging and brain disorders, and as an extension, our finding demonstrates IIV as an efficient indicator of mental fatigue. Conclusions: This study reveals significant modulations of mental fatigue on IIV at the behavioral and neural levels and establishes a robust mental fatigue detection pipeline.
  •  
34.
  • Liu, Jia, et al. (författare)
  • Analysis of modulations of mental fatigue on intra-individual variability from single-trial event related potentials
  • 2024
  • Ingår i: JOURNAL OF NEUROSCIENCE METHODS. - 0165-0270 .- 1872-678X. ; 406
  • Tidskriftsartikel (refereegranskat)abstract
    • Background: Intra-individual variability (IIV), a measure of variance within an individual's performance, has been demonstrated as metrics of brain responses for neural functionality. However, how mental fatigue modulates IIV remains unclear. Consequently, the development of robust mental fatigue detection methods at the single-trial level is challenging. New methods: Based on a long-duration flanker task EEG dataset, the modulations of mental fatigue on IIV were explored in terms of response time (RT) and trial-to-trial latency variations of event-related potentials (ERPs). Specifically, latency variations were quantified using residue iteration decomposition (RIDE) to reconstruct latency-corrected ERPs. We compared reconstructed ERPs with raw ERPs by means of temporal principal component analysis (PCA). Furthermore, a single-trial classification pipeline was developed to detect the changes of mental fatigue levels. Results: We found an increased IIV in the RT metric in the fatigue state compared to the alert state. The same sequence of ERPs (N1, P2, N2, P3a, P3b, and slow wave, or SW) was separated from both raw and reconstructed ERPs using PCA, whereas differences between raw and reconstructed ERPs in explained variances for separated ERPs were found owing to IIV. Particularly, a stronger N2 was detected in the fatigue than alert state after RIDE. The single-trial fatigue detection pipeline yielded an acceptable accuracy of 73.3%. Comparison with existing methods: The IIV has been linked to aging and brain disorders, and as an extension, our finding demonstrates IIV as an efficient indicator of mental fatigue. Conclusions: This study reveals significant modulations of mental fatigue on IIV at the behavioral and neural levels and establishes a robust mental fatigue detection pipeline.
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35.
  • Liu, Jia, et al. (författare)
  • Long term sustained attention alters dynamic functional connectivity patterns
  • 2023
  • Ingår i: 2023 45th Annual International Conference of the IEEE Engineering in Medicine & Biology Society (EMBC). - 9798350324488 - 9798350324471
  • Konferensbidrag (refereegranskat)abstract
    • Mental fatigue has attracted much attention from researchers as it plays a key role in performance efficiency and safety situations. Functional connectivity analysis using graph theory is an effective method for revealing changes in cognition resources influenced by mental fatigue. Previous studies have revealed that functional networks are dynamically reorganized. Therefore, it is critical to explore dynamic timescales of networks related to specific cognitive abilities. In this study, we used an open EEG dataset of twenty-one subjects recorded in a 60-minutes sustained attention task. After preprocessing, we constructed connectivity matrices using the weighted phase lag index (wPLI) in the theta band and characterized them with dynamic graph measures, namely characteristic path length (CPL) and clustering coefficient (CC). The results show that the frontal-parietal brain networks in theta band are involved in a sustaining attention task. When averaging from temporal and spatial activations, CPL and CC decreased with time-on-task. Our results indicate that mental fatigue results in deteriorations in sustaining attention, and graph theory analysis can provide support for mental fatigue analysis.Clinical Relevance— Identification of the effects of long term sustained attention on dynamic brain networks may be potential for mechanism study and detection of mental states and attentional deficits caused by mental diseases.
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36.
  • Liu, Jia, et al. (författare)
  • Reconfiguration of cognitive control networks during a long-duration flanker task
  • Ingår i: IEEE Transactions on Cognitive and Developmental Systems. - 2379-8920. ; , s. 1-10
  • Tidskriftsartikel (refereegranskat)abstract
    • Continuous task engagement generally leads to vigilance decrement and deteriorates task performance. However, how conflict effect is modulated by vigilance decrement has no consistent evidence, and little is known about the underlying neural mechanisms. Here we adopted an electroencephalogram dataset collected during a prolonged flanker task to examine the interactions between vigilance and congruency on behavioral performance and neural measures. Specifically, we extracted a sequence of ERPs using temporal principal component analysis (PCA) and performed functional network analysis with graph measures. Behavioral analysis results showed that behavioral performance deteriorated due to vigilance decrement, but the capability of conflict processing was maintained over time. Regarding the neural analysis results, the conflict effect reflected in P3a and P3b was changed and maintained respectively when affected by vigilance decrement. The theta band frontoparietal network was observed in the face of conflicting interference and the conflict effect for graph measures disappeared over time. These results demonstrated deteriorated task performance, impaired cognitive functions, and the reconfiguration of cognitive control networks during a prolonged flanker task. Our findings also support the evidence that temporal PCA and event-related network analysis might be efficient for the investigation of the neural dynamics of complex cognitive processes.
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37.
  • Lundsberg, Jonathan, et al. (författare)
  • Compressed spike-triggered averaging in iterative decomposition of surface EMG
  • 2023
  • Ingår i: Computer Methods and Programs in Biomedicine. - : Elsevier BV. - 0169-2607. ; 228
  • Tidskriftsartikel (refereegranskat)abstract
    • Background and Objective: Analysis of motor unit activity is important for assessing and treating diseases or injuries affecting natural movement. State-of-the-art decomposition translates high-density surface electromyography (HDsEMG) into motor unit activity. However, current decomposition methods offer far from complete separation of all motor units. Methods: This paper proposes a peel-offapproach to automatic decomposition of HDsEMG into motor unit action potential (MUAP) trains, based on the Fast Independent Component Analysis algorithm (FastICA). The novel steps include utilizing compression by means of Principal Component Analysis and spike-triggered averaging, to estimate surface MUAP distributions with less noise, which are iteratively subtracted from the HDsEMG dataset. Furthermore, motor unit spike trains are estimated by highdimensional density-based clustering of peaks in the FastICA source output. And finally, a new reliability measure is used to discard poor motor unit estimates by comparing the variance of the FastICA source output before and after the peel-offstep. The method was validated using reconstructed synthetic data at three different signal-to-noise levels and was compared to an established deflationary FastICA approach. Results: Both algorithms had very high recall and precision, over 90%, for spikes from matching motor units, referred to as matched performance. However, the peel-offalgorithm correctly identified more motor units for all noise levels. When accounting for unidentified motor units, total recall was up to 33 percentage points higher; and when accounting for duplicate estimates, total precision was up to 24 percentage points higher, compared to the state-of-the-art reference. In addition, a comparison was done using experimental data where the proposed algorithm had a matched recall of 97% and precision of 85% with respect to the reference algorithm. Conclusion: These results show a substantial performance increase for decomposition of simulated HDsEMG data and serve to validate the proposed approach. This performance increase is an important step towards complete decomposition and extraction of information of motor unit activity. (C) 2022TheAuthor(s). PublishedbyElsevierB.V.
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38.
  • Lundsberg, Jonathan, et al. (författare)
  • Inferring position of motor units from high-density surface EMG
  • 2024
  • Ingår i: SCIENTIFIC REPORTS. - 2045-2322. ; 14:1
  • Tidskriftsartikel (refereegranskat)abstract
    • The spatial distribution of muscle fibre activity is of interest in guiding therapy and assessing recovery of motor function following injuries of the peripheral or central nervous system. This paper presents a new method for stable estimation of motor unit territory centres from high-density surface electromyography (HDsEMG). This completely automatic process applies principal component compression and a rotatable Gaussian surface fit to motor unit action potential (MUAP) distributions to map the spatial distribution of motor unit activity. Each estimated position corresponds to the signal centre of the motor unit territory. Two subjects were used to test the method on forearm muscles, using two different approaches. With the first dataset, motor units were identified by decomposition of intramuscular EMG and the centre position of each motor unit territory was estimated from synchronized HDsEMG data. These positions were compared to the positions of the intramuscular fine wire electrodes with depth measured using ultrasound. With the second dataset, decomposition and motor unit localization was done directly on HDsEMG data, during specific muscle contractions. From the first dataset, the mean estimated depth of the motor unit centres were 8.7, 11.6, and 9.1 mm, with standard deviations 0.5, 0.1, and 1.3 mm, and the respective depths of the fine wire electrodes were 8.4, 15.8, and 9.1 mm. The second dataset generated distinct spatial distributions of motor unit activity which were used to identify the regions of different muscles of the forearm, in a 3-dimensional and projected 2-dimensional view. In conclusion, a method is presented which estimates motor unit centre positions from HDsEMG. The study demonstrates the shifting spatial distribution of muscle fibre activity between different efforts, which could be used to assess individual muscles on a motor unit level.
  •  
39.
  • Malešević, Nebojša, et al. (författare)
  • A database of high-density surface electromyogram signals comprising 65 isometric hand gestures
  • 2021
  • Ingår i: Scientific Data. - : Springer Science and Business Media LLC. - 2052-4463. ; 8:1
  • Tidskriftsartikel (refereegranskat)abstract
    • Control of contemporary, multi-joint prosthetic hands is commonly realized by using electromyographic signals from the muscles remaining after amputation at the forearm level. Although this principle is trying to imitate the natural control structure where muscles control the joints of the hand, in practice, myoelectric control provides only basic hand functions to an amputee using a dexterous prosthesis. This study aims to provide an annotated database of high-density surface electromyographic signals to aid the efforts of designing robust and versatile electromyographic control interfaces for prosthetic hands. The electromyographic signals were recorded using 128 channels within two electrode grids positioned on the forearms of 20 able-bodied volunteers. The participants performed 65 different hand gestures in an isometric manner. The hand movements were strictly timed using an automated recording protocol which also synchronously recorded the electromyographic signals and hand joint forces. To assess the quality of the recorded signals several quantitative assessments were performed, such as frequency content analysis, channel crosstalk, and the detection of poor skin-electrode contacts.
  •  
40.
  • Maleševic, Nebojša, et al. (författare)
  • Contactless real-time heartbeat detection via 24 ghz continuous-wave doppler radar using artificial neural networks
  • 2020
  • Ingår i: Sensors (Switzerland). - : MDPI AG. - 1424-8220. ; 20:8
  • Tidskriftsartikel (refereegranskat)abstract
    • The measurement of human vital signs is a highly important task in a variety of environments and applications. Most notably, the electrocardiogram (ECG) is a versatile signal that could indicate various physical and psychological conditions, from signs of life to complex mental states. The measurement of the ECG relies on electrodes attached to the skin to acquire the electrical activity of the heart, which imposes certain limitations. Recently, due to the advancement of wireless technology, it has become possible to pick up heart activity in a contactless manner. Among the possible ways to wirelessly obtain information related to heart activity, methods based on mm-wave radars proved to be the most accurate in detecting the small mechanical oscillations of the human chest resulting from heartbeats. In this paper, we presented a method based on a continuous-wave Doppler radar coupled with an artificial neural network (ANN) to detect heartbeats as individual events. To keep the method computationally simple, the ANN took the raw radar signal as input, while the output was minimally processed, ensuring low latency operation (<1 s). The performance of the proposed method was evaluated with respect to an ECG reference (“ground truth”) in an experiment involving 21 healthy volunteers, who were sitting on a cushioned seat and were refrained from making excessive body movements. The results indicated that the presented approach is viable for the fast detection of individual heartbeats without heavy signal preprocessing.
  •  
41.
  • Malesevic, Nebojsa, et al. (författare)
  • Evaluation of Simple Algorithms for Proportional Control of Prosthetic Hands Using Intramuscular Electromyography
  • 2022
  • Ingår i: Sensors. - : MDPI AG. - 1424-8220. ; 22:13
  • Tidskriftsartikel (refereegranskat)abstract
    • Although seemingly effortless, the control of the human hand is backed by an elaborate neuro-muscular mechanism. The end result is typically a smooth action with the precise positioning of the joints of the hand and an exerted force that can be modulated to enable precise interaction with the surroundings. Unfortunately, even the most sophisticated technology cannot replace such a comprehensive role but can offer only basic hand functionalities. This issue arises from the drawbacks of the prosthetic hand control strategies that commonly rely on surface EMG signals that contain a high level of noise, thus limiting accurate and robust multi-joint movement estimation. The use of intramuscular EMG results in higher quality signals which, in turn, lead to an improvement in prosthetic control performance. Here, we present the evaluation of fourteen common/well-known algorithms (mean absolute value, variance, slope sign change, zero crossing, Willison amplitude, waveform length, signal envelope, total signal energy, Teager energy in the time domain, Teager energy in the frequency domain, modified Teager energy, mean of signal frequencies, median of signal frequencies, and firing rate) for the direct and proportional control of a prosthetic hand. The method involves the estimation of the forces generated in the hand by using different algorithms applied to iEMG signals from our recently published database, and comparing them to the measured forces (ground truth). The results presented in this paper are intended to be used as a baseline performance metric for more advanced algorithms that will be made and tested using the same database.
  •  
42.
  • Malesevic, Nebojsa, et al. (författare)
  • Exploration of sensations evoked during electrical stimulation of the median nerve at the wrist level
  • 2023
  • Ingår i: Journal of Neural Engineering. - 1741-2560 .- 1741-2552. ; 20:6
  • Tidskriftsartikel (refereegranskat)abstract
    • Objective. Nerve rehabilitation following nerve injury or surgery at the wrist level is a lengthy process during which not only peripheral nerves regrow towards receptors and muscles, but also the brain undergoes plastic changes. As a result, at the time when nerves reach their targets, the brain might have already allocated some of the areas within the somatosensory cortex that originally processed hand signals to some other regions of the body. The aim of this study is to show that it is possible to evoke a variety of somatotopic sensations related to the hand while stimulating proximally to the injury, therefore, providing the brain with the relevant inputs from the hand regions affected by the nerve damage. Approach. This study included electrical stimulation of 28 able-bodied participants where an electrode that acted as a cathode was placed above the Median nerve at the wrist level. The parameters of electrical stimulation, amplitude, frequency, and pulse shape, were modulated within predefined ranges to evaluate their influence on the evoked sensations. Main results. Using this methodology, the participants reported a wide variety of somatotopic sensations from the hand regions distal to the stimulation electrode. Significance. Furthermore, to propose an accelerated stimulation tuning procedure that could be implemented in a clinical protocol and/or standalone device for providing meaningful sensations to the somatosensory cortex during nerve regeneration, we trained machine-learning techniques using the gathered data to predict the location/area, naturalness, and sensation type of the evoked sensations following different stimulation patterns.
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43.
  • Moshontz, Hannah, et al. (författare)
  • The Psychological Science Accelerator: Advancing Psychology Through a Distributed Collaborative Network
  • 2018
  • Ingår i: Advances in Methods and Practices in Psychological Science. - : SAGE Publications. - 2515-2459 .- 2515-2467. ; 1:4, s. 501-515
  • Tidskriftsartikel (refereegranskat)abstract
    • Concerns about the veracity of psychological research have been growing. Many findings in psychological science are based on studies with insufficient statistical power and nonrepresentative samples, or may otherwise be limited to specific, ungeneralizable settings or populations. Crowdsourced research, a type of large-scale collaboration in which one or more research projects are conducted across multiple lab sites, offers a pragmatic solution to these and other current methodological challenges. The Psychological Science Accelerator (PSA) is a distributed network of laboratories designed to enable and support crowdsourced research projects. These projects can focus on novel research questions or replicate prior research in large, diverse samples. The PSA’s mission is to accelerate the accumulation of reliable and generalizable evidence in psychological science. Here, we describe the background, structure, principles, procedures, benefits, and challenges of the PSA. In contrast to other crowdsourced research networks, the PSA is ongoing (as opposed to time limited), efficient (in that structures and principles are reused for different projects), decentralized, diverse (in both subjects and researchers), and inclusive (of proposals, contributions, and other relevant input from anyone inside or outside the network). The PSA and other approaches to crowdsourced psychological science will advance understanding of mental processes and behaviors by enabling rigorous research and systematic examination of its generalizability.
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44.
  • Olsson, Alexander E., et al. (författare)
  • Automatic discovery of resource-restricted Convolutional Neural Network topologies for myoelectric pattern recognition
  • 2020
  • Ingår i: Computers in Biology and Medicine. - : Elsevier BV. - 0010-4825. ; 120
  • Tidskriftsartikel (refereegranskat)abstract
    • Convolutional Neural Networks (CNNs) have been subject to extensive attention in the pattern recognition literature due to unprecedented performance in tasks of information extraction from unstructured data. Whereas available methods for supervised training of a CNN with a given network topology are well-defined with rigorous theoretical justification, procedures for the initial selection of topology are currently not. Work incorporating selection of the CNN topology has instead substantially been guided by the domain-specific expertise of the creator(s), followed by iterative improvement via empirical evaluation. This limitation of methodology is restricting in the pursuit of naturally controlled muscle-computer interfaces, where CNNs have been identified as a promising research avenue but effective topology selection heuristics are lacking. With the goal of mitigating ambiguities in topology selection, this paper presents a systematic approach wherein we apply a novel evolutionary algorithm to search a space of candidate topologies. Furthermore, we constrain the search-space by excluding topologies with excessive inference-time computational complexity, making the obtained results implementable in embedded systems. In contrast to manual topology design, our algorithm requires the user to only specify a relatively small set of intuitive hyperparameters. To validate our approach, we use it in order to create topologies for myoelectric pattern recognition via movement decoding of surface electromyography signals. By collating offline classification accuracies obtained from experiments on a collection of publicly available databases, we demonstrate that our method generates computationally lightweight topologies with performance comparable to those of available alternatives.
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45.
  • Olsson, Alexander E., et al. (författare)
  • Can Deep Synthesis of EMG Overcome the Geometric Growth of Training Data Required to Recognize Multiarticulate Motions?
  • 2021
  • Ingår i: Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference. - 2694-0604. ; 2021, s. 6380-6383
  • Tidskriftsartikel (refereegranskat)abstract
    • By being predicated on supervised machine learning, pattern recognition approaches to myoelectric prosthesis control require electromyography (EMG) training data collected concurrently with every detectable motion. Within this framework, calibration protocols for simultaneous control of multifunctional prosthetic hands rapidly become prohibitively long-the number of unique motions grows geometrically with the number of controllable degrees of freedom (DoFs). This paper proposes a technique intended to circumvent this combinatorial explosion. Using EMG windows from 1-DoF motions as input and EMG windows from 2-DoF motions as targets, we train generative deep learning models to synthesize EMG windows appertaining to multi-DoF motions. Once trained, such models can be used to complete datasets consisting of only 1-DoF motions, enabling simple calibration protocols with durations that scale linearly with the number of DoFs. We evaluated synthetic EMG produced in this way via a classification task using a database of forearm surface EMG collected during 1-DoF and 2-DoF motions. Multi-output classifiers were trained on either (I) real data from 1-DoF and 2-DoF motions, (II) real data from only 1-DoF motions, or (III) real data from 1-DoF motions appended with synthetic EMG from 2-DoF motions. When tested on data containing all possible motions, classifiers trained on synthetic-appended data (III) significantly outperformed classifiers trained on 1-DoF real data (II), although significantly underperformed classifiers trained on both 1- and 2-DoF real data (I) (I < 0.05). These findings suggest that it is feasible to model EMG concurrent with multiarticulate motions as nonlinear combinations of EMG from constituent 1-DoF motions, and that such modelling can be harnessed to synthesize realistic training data.
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46.
  • Olsson, Alexander E, et al. (författare)
  • End-to-End Estimation of Hand- and Wrist Forces From Raw Intramuscular EMG Signals Using LSTM Networks
  • 2021
  • Ingår i: Frontiers in Neuroscience. - 1662-453X .- 1662-4548. ; 15
  • Tidskriftsartikel (refereegranskat)abstract
    • Processing myoelectrical activity in the forearm has for long been considered a promising framework to allow transradial amputees to control motorized prostheses. In spite of expectations, contemporary muscle-computer interfaces built for this purpose typically fail to satisfy one or more important desiderata, such as accuracy, robustness, and/or naturalness of control, in part due to difficulties in acquiring high-quality signals continuously outside laboratory conditions. In light of such problems, surgically implanted electrodes have been made a viable option that allows for long-term acquisition of intramuscular electromyography (iEMG) measurements of spatially precise origin. As it stands, the question of how information embedded in such signals is best extracted and combined across multiple channels remains open. This study presents and evaluates an approach to this end that uses deep neural networks based on the Long Short-Term Memory (LSTMs) architecture to regress forces exerted by multiple degrees of freedom (DoFs) from multichannel iEMG. Three deep learning models, representing three distinct regression strategies, were evaluated: (I) One-to-One, wherein each DoF is separately estimated by an LSTM model processing a single iEMG channel, (II) All-to-One, wherein each DoF is separately estimated by an LSTM model processing all iEMG channels, and (III) All-to-All, wherein a single LSTM model with access to all iEMG channels estimates all DoFs simultaneously. All models operate on raw iEMG, with no preliminary feature extraction required. When evaluated on a dataset comprising six iEMG channels with concurrent force measurements acquired from 14 subjects, all LSTM strategies were found to significantly outperform a baseline feature-based linear control regression method. This finding indicates that recurrent neural networks can learn to transform raw forearm iEMG signals directly into representations that correlate with forces exerted at the level of the hand to a greater degree than simple features do. Furthermore, the All-to-All and All-to-One strategies were found to exhibit better performance than the One-to-One strategy. This finding suggests that, in spite of the spatially local nature of signals, iEMG from muscles not directly actuating the relevant DoF can provide contextual information that aid in decoding motor intent.
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47.
  • Olsson, Alexander E., et al. (författare)
  • Extraction of Multi-Labelled Movement Information from the Raw HD-sEMG Image with Time-Domain Depth
  • 2019
  • Ingår i: Scientific Reports. - : Springer Science and Business Media LLC. - 2045-2322. ; 9:1
  • Tidskriftsartikel (refereegranskat)abstract
    • In contemporary muscle-computer interfaces for upper limb prosthetics there is often a trade-off between control robustness and range of executable movements. As a very low movement error rate is necessary in practical applications, this often results in a quite severe limitation of controllability; a problem growing ever more salient as the mechanical sophistication of multifunctional myoelectric prostheses continues to improve. A possible remedy for this could come from the use of multi-label machine learning methods, where complex movements can be expressed as the superposition of several simpler movements. Here, we investigate this claim by applying a multi-labeled classification scheme in the form of a deep convolutional neural network (CNN) to high density surface electromyography (HD-sEMG) recordings. We use 16 independent labels to model the movements of the hand and forearm state, representing its major degrees of freedom. By training the neural network on 16 × 8 sEMG image sequences 24 samples long with a sampling rate of 2048 Hz to detect these labels, we achieved a mean exact match rate of 78.7% and a mean Hamming loss of 2.9% across 14 healthy test subjects. With this, we demonstrate the feasibility of highly versatile and responsive sEMG control interfaces without loss of accuracy.
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48.
  • Olsson, Alexander E., et al. (författare)
  • Learning regularized representations of categorically labelled surface EMG enables simultaneous and proportional myoelectric control
  • 2021
  • Ingår i: Journal of NeuroEngineering and Rehabilitation. - : Springer Science and Business Media LLC. - 1743-0003. ; 18:1
  • Tidskriftsartikel (refereegranskat)abstract
    • BackgroundProcessing the surface electromyogram (sEMG) to decode movement intent is a promising approach for natural control of upper extremity prostheses. To this end, this paper introduces and evaluates a new framework which allows for simultaneous and proportional myoelectric control over multiple degrees of freedom (DoFs) in real-time. The framework uses multitask neural networks and domain-informed regularization in order to automatically find nonlinear mappings from the forearm sEMG envelope to multivariate and continuous encodings of concurrent hand- and wrist kinematics, despite only requiring categorical movement instruction stimuli signals for calibration.MethodsForearm sEMG with 8 channels was collected from healthy human subjects (N=20) and used to calibrate two myoelectric control interfaces, each with two output DoFs. The interfaces were built from (I) the proposed framework, termed Myoelectric Representation Learning (MRL), and, to allow for comparisons, from (II) a standard pattern recognition framework based on Linear Discriminant Analysis (LDA). The online performances of both interfaces were assessed with a Fitts's law type test generating 5 quantitative performance metrics. The temporal stabilities of the interfaces were evaluated by conducting identical tests without recalibration 7 days after the initial experiment session.ResultsMetric-wise two-way repeated measures ANOVA with factors method (MRL vs LDA) and session (day 1 vs day 7) revealed a significant (p<0.05) advantage for MRL over LDA in 5 out of 5 performance metrics, with metric-wise effect sizes (Cohen's d) separating MRL from LDA ranging from d =0.62 to d=1.13. No significant effect on any metric was detected for neither session nor interaction between method and session, indicating that none of the methods deteriorated significantly in control efficacy during one week of intermission.ConclusionsThe results suggest that MRL is able to successfully generate stable mappings from EMG to kinematics, thereby enabling myoelectric control with real-time performance superior to that of the current commercial standard for pattern recognition (as represented by LDA). It is thus postulated that the presented MRL approach can be of practical utility for muscle-computer interfaces.
  •  
49.
  • Olsson, Alexander, et al. (författare)
  • Exploiting the Intertemporal Structure of the Upper-Limb sEMG: Comparisons between an LSTM Network and Cross-Sectional Myoelectric Pattern Recognition Methods
  • 2019
  • Ingår i: 2019 41st Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC). - 9781538613122 - 9781538613122
  • Konferensbidrag (refereegranskat)abstract
    • The use of natural myoelectric interfaces promises great value for a variety of potential applications, clinical and otherwise, provided a computational mapping between measured neuromuscular activity and executed motion can be approximated to a satisfactory degree. However, prevalent methods intended for such decoding of movement intent from the surface electromyogram (sEMG) based on pattern recognition typically do not capitalize on the inherently time series-like nature of the acquired signals. In this paper, we present the results from a comparative study in which the performances of traditional cross-sectional pattern recognition methods were compared with that of a classifier built on the natural assumption of temporal ordering by utilizing a long short-term memory (LSTM) neural network. The resulting evaluation indicate that the LSTM approach outperforms traditional gesture recognition techniques which are based on cross-sectional inference. These findings held both when the LSTM classifier operated on conventional features and on raw sEMG and for both healthy subjects and transradial amputees.
  •  
50.
  • Rohlén, Robin, et al. (författare)
  • A fast blind source separation algorithm for decomposing ultrafast ultrasound images into spatiotemporal muscle unit kinematics
  • 2024
  • Annan publikation (övrigt vetenskapligt/konstnärligt)abstract
    • Objective: Ultrasound can detect individual motor unit (MU) activity during voluntary isometric contractions based on their subtle axial displacements. The detection pipeline, currently performed offline, is based on displacement velocity images and identifying the subtle axial displacements. This identification can preferably be made through a blind source separation (BSS) algorithm with the feasibility of translating the pipeline from offline to online. However, the question remains how to reduce the computational time for the BSS algorithm, which includes demixing tissue velocities from many different sources, e.g., the active MU displacements, arterial pulsations, bones, connective tissue, and noise.Approach: This study proposes a fast velocity-based BSS (velBSS) algorithm suitable for online purposes that decomposes velocity images from low-force voluntary isometric contractions into spatiotemporal components associated with single MU activities. The proposed algorithm will be compared against stICA, i.e., the method used in previous papers, for various subjects, ultrasound- and EMG systems, where the latter acts as MU reference recordings.Main results: We found that the spatial and temporal correlation between the MU-associated components from velBSS and stICA was high (0.86 +/- 0.05 and 0.87 +/- 0.06). The spike-triggered averaged twitch responses (using the MU spike trains from EMG) had an extremely high correlation (0.99 +/- 0.01). In addition, the computational time for velBSS was at least 50 times less than for stICA.Significance: The present algorithm (velBSS) outperforms the currently available method (stICA). It provides a promising translation towards an online pipeline and will be important in the continued development of this research field of functional neuromuscular imaging.
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