SwePub - search: WFRF:(Mastinu Enzo 1987)

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1.	Mastinu, Enzo, 1987, et al. (author) Neural feedback strategies to improve grasping coordination in neuromusculoskeletal prostheses 2020 In: Scientific Reports. - : Springer Science and Business Media LLC. - 2045-2322 .- 2045-2322. ; 10:1 Journal article (peer-reviewed)abstract Conventional prosthetic arms suffer from poor controllability and lack of sensory feedback. Owing to the absence of tactile sensory information, prosthetic users must rely on incidental visual and auditory cues. In this study, we investigated the effect of providing tactile perception on motor coordination during routine grasping and grasping under uncertainty. Three transhumeral amputees were implanted with an osseointegrated percutaneous implant system for direct skeletal attachment and bidirectional communication with implanted neuromuscular electrodes. This neuromusculoskeletal prosthesis is a novel concept of artificial limb replacement that allows to extract control signals from electrodes implanted on viable muscle tissue, and to stimulate severed afferent nerve fibers to provide somatosensory feedback. Subjects received tactile feedback using three biologically inspired stimulation paradigms while performing a pick and lift test. The grasped object was instrumented to record grasping and lifting forces and its weight was either constant or unexpectedly changed in between trials. The results were also compared to the no-feedback control condition. Our findings confirm, in line with the neuroscientific literature, that somatosensory feedback is necessary for motor coordination during grasping. Our results also indicate that feedback is more relevant under uncertainty, and its effectiveness can be influenced by the selected neuromodulation paradigm and arguably also the prior experience of the prosthesis user.
2.	Ahkami, Bahareh, 1994, et al. (author) Extra-neural signals from severed nerves enable intrinsic hand movements in transhumeral amputations 2022 In: Scientific Reports. - : Springer Science and Business Media LLC. - 2045-2322. ; 12:1 Journal article (peer-reviewed)abstract Robotic prostheses controlled by myoelectric signals can restore limited but important hand function in individuals with upper limb amputation. The lack of individual finger control highlights the yet insurmountable gap to fully replacing a biological hand. Implanted electrodes around severed nerves have been used to elicit sensations perceived as arising from the missing limb, but using such extra-neural electrodes to record motor signals that allow for the decoding of phantom movements has remained elusive. Here, we showed the feasibility of using signals from non-penetrating neural electrodes to decode intrinsic hand and finger movements in individuals with above-elbow amputations. We found that information recorded with extra-neural electrodes alone was enough to decode phantom hand and individual finger movements, and as expected, the addition of myoelectric signals reduced classification errors both in offline and in real-time decoding.
3.	Buist, Mirka, et al. (author) Development and Validation of a Wearable Device to Provide Rich Somatosensory Stimulation for Rehabilitation After Sensorimotor Impairment 2023 In: IEEE Transactions on Biomedical Circuits and Systems. - : Institute of Electrical and Electronics Engineers (IEEE). - 1932-4545 .- 1940-9990. ; 17:3, s. 547-557 Journal article (peer-reviewed)abstract Training sensory discrimination of the skin has the potential to reduce chronic pain due to sensorimotor impairments and increase sensorimotor function. Currently, there is no such device that can systematically provide rich skin stimulation suitable for a training protocol for individuals with amputation or major sensory impairment. This study describes the development and validation of a non-invasive wearable device meant to repeatedly and safely deliver somatosensory stimulations. The development was guided by a structured design control process to ensure the verifiability and validity of the design outcomes. Two sub-systems were designed: 1) a tactile display for touch and vibration sensations, and 2) a set of bands for sliding, pressure, and strain sensations. The device was designed with a versatile structure that allows for its application on different body parts. We designed a device-paired interactive computer program to enable structured sensory training sessions. Validation was performed with 11 individuals with intact limbs whose upper arm tactile sensitivity was measured over 5 training sessions. Tactile discrimination and perception threshold were measured using the standard 2-point discrimination and Semmes-Weinstein monofilament tests, respectively. The results of the monofilament test showed a significant improvement (p = 0.011), but the improvement was not significant for the 2-point discrimination test(p = 0.141). These promising results confirm the potential of the proposed training to increase the sensory acuity in the upper arms of individuals with intact limbs. Further studies will be conducted to determine how to transfer the findings of this work to improve the pain and/or functional rehabilitation in individuals with sensorimotor impairments.
4.	Buist, Mirka, et al. (author) Novel Wearable Device for Mindful Sensorimotor Training: Integrating Motor Decoding and Somatosensory Stimulation for Neurorehabilitation 2024 In: IEEE Transactions on Neural Systems and Rehabilitation Engineering. - : Institute of Electrical and Electronics Engineers (IEEE). - 1558-0210 .- 1534-4320. ; 32, s. 1515-1523 Journal article (peer-reviewed)abstract Sensorimotor impairment is a prevalent condition requiring effective rehabilitation strategies. This study introduces a novel wearable device for Mindful Sensorimotor Training (MiSMT) designed for sensory and motor rehabilitation. Our MiSMT device combines motor training using myoelectric pattern recognition along sensory training using two tactile displays. This device offers a comprehensive solution, integrating electromyography and haptic feedback, lacking in existing devices. The device features eight electromyography channels, a rechargeable battery, and wireless Bluetooth or Wi-Fi connectivity for seamless communication with a computer or mobile device. Its flexible material allows for adaptability to various body parts, ensuring ease of use in diverse patients. The two tactile displays, with 16 electromagnetic actuators each, provide touch and vibration sensations up to 250 Hz. In this proof-of-concept study, we show improved two-point discrimination after 5 training sessions in participants with intact limbs (p=0.047). We also demonstrated successful acquisition, processing, and decoding of myoelectric signals in offline and online evaluations. In conclusion, the MiSMT device presents a promising tool for sensorimotor rehabilitation by combining motor execution and sensory training benefits. Further studies are required to assess its effectiveness in individuals with sensorimotor impairments. Integrating mindful sensory and motor training with innovative technology can enhance rehabilitation outcomes and improve the quality of life for those with sensorimotor impairments.
5.	D'Accolti, Daniele, et al. (author) Decoding of Multiple Wrist and Hand Movements Using a Transient EMG Classifier 2023 In: IEEE Transactions on Neural Systems and Rehabilitation Engineering. - 1558-0210 .- 1534-4320. ; 31, s. 208-217 Journal article (peer-reviewed)abstract The design of prosthetic controllers by means of neurophysiological signals still poses a crucial challenge to bioengineers. State of the art of electromyographic (EMG) continuous pattern recognition controllers rely on the questionable assumption that repeated muscular contractions produce repeatable patterns of steady-state EMG signals. Conversely, we propose an algorithm that decodes wrist and hand movements by processing the signals that immediately follow the onset of contraction (i.e., the \textit {transient} EMG). We collected EMG data from the forearms of 14 non-amputee and 5 transradial amputee participants while they performed wrist flexion/extension, pronation/supination, and four hand grasps (power, lateral, bi-digital, open). We firstly identified the combination of wrist and hand movements that yielded the best control performance for the same participant (intra-subject classification). Then, we assessed the ability of our algorithm to classify participant data that were not included in the training set (cross-subject classification). Our controller achieved a median accuracy of 96% with non-amputees, while it achieved heterogeneous outcomes with amputees, with a median accuracy of 89%. Importantly, for each amputee, it produced at least one \textit {acceptable} combination of wrist-hand movements (i.e., with accuracy >85%). Regarding the cross-subject classifier, while our algorithm obtained promising results with non-amputees (accuracy up to 80%), they were not as good with amputees (accuracy up to 35%), possibly suggesting further assessments with domain-adaptation strategies. In general, our offline outcomes, together with a preliminary online assessment, support the hypothesis that the transient EMG decoding could represent a viable pattern recognition strategy, encouraging further online assessments.
6.	D'Accolti, Daniele, et al. (author) Online Classification of Transient EMG Patterns for the Control of the Wrist and Hand in a Transradial Prosthesis 2023 In: IEEE Robotics and Automation Letters. - 2377-3766. ; 8:2, s. 1045-1052 Journal article (peer-reviewed)abstract Decoding human motor intentions by processing electrophysiological signals is a crucial, yet unsolved, challenge for the development of effective upper limb prostheses. Pattern recognition of continuous myoelectric (EMG) signals represents the state-of-art for multi-DoF prosthesis control. However, this approach relies on the unreliable assumption that repeatable muscular contractions produce repeatable patterns of steady-state EMGs. Here, we propose an approach for decoding wrist and hand movements by processing the signals associated with the onset of contraction (transient EMG). Specifically, we extend the concept of a transient EMG controller for the control of both wrist and hand, and tested it online. We assessed it with one transradial amputee and 15 non-amputees via the Target Achievement Control test. Non-amputees successfully completed 95% of the trials with a median completion time of 17 seconds, showing a significant learning trend (p < 0.001). The transradial amputee completed about the 80% of the trials with a median completion time of 26 seconds. Although the performance proved comparable with earlier studies, the long completion times suggest that the current controller is not yet clinically viable. However, taken collectively, our outcomes reinforce earlier hypothesis that the transient EMG could represent a viable alternative to steady-state pattern recognition approaches.
7.	Earley, Eric, 1989, et al. (author) Competitive motivation increased home use and improved prosthesis self-perception after Cybathlon 2020 for neuromusculoskeletal prosthesis user 2022 In: Journal of NeuroEngineering and Rehabilitation. - : Springer Science and Business Media LLC. - 1743-0003. ; 19:1 Journal article (peer-reviewed)abstract Background Assistive technologies, such as arm prostheses, are intended to improve the quality of life of individuals with physical disabilities. However, certain training and learning is usually required from the user to make these technologies more effective. Moreover, some people can be encouraged to train more through competitive motivation. Methods In this study, we investigated if the training for and participation in a competitive event (Cybathlon 2020) could promote behavioral changes in an individual with upper limb amputation (the pilot). We defined behavioral changes as the active time while his prosthesis was actuated, ratio of opposing and simultaneous movements, and the pilot's ability to finely modulate his movement speeds. The investigation was based on extensive home-use data from the period before, during and after the Cybathlon 2020 competition. Results Relevant behavioral changes were found from both quantitative and qualitative analyses. The pilot's home use of his prosthesis nearly doubled in the period before the Cybathlon, and remained 66% higher than baseline after the competition. Moreover, he improved his speed modulation when controlling his prosthesis, and he learned and routinely operated new movements in the prosthesis (wrist rotation) at home. Additionally, as confirmed by semi-structured interviews, his self-perception of the prosthetic arm and its functionality also improved. Conclusions An event like the Cybathlon may indeed promote behavioral changes in how competitive individuals with amputation use their prostheses. Provided that the prosthesis is suitable in terms of form and function for both competition and at-home daily use, daily activities can become opportunities for training, which in turn can improve prosthesis function and create further opportunities for daily use. Moreover, these changes appeared to remain even well after the event, albeit relevant only for individuals who continue using the technology employed in the competition.
8.	Earley, Eric, 1989, et al. (author) Cross-Channel Impedance Measurement for Monitoring Implanted Electrodes 2022 In: Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS. - 1557-170X. ; 2022-July, s. 4880-4883 Conference paper (peer-reviewed)abstract Implanted electrodes, such as those used for cochlear implants, brain-computer interfaces, and prosthetic limbs, rely on particular electrical conditions for optimal operation. Measurements of electrical impedance can be a diagnostic tool to monitor implanted electrodes for changing conditions arising from glial scarring, encapsulation, and shorted or broken wires. Such measurements provide information about the electrical impedance between a single electrode and its electrical reference, but offer no insights into the overall network of impedances between electrodes. Other solutions generally rely on geometrical assumptions of the arrangement of the electrodes and may not generalize to other electrode networks. Here, we propose a linear algebra-based approach, Cross-Channel Impedance Measurement (CCIM), for measuring a network of impedances between electrodes which all share a common electrical reference. This is accomplished by measuring the voltage response from all electrodes to a known current applied between each electrode and the shared reference, and is agnostic to the number and arrangement of electrodes. The approach is validated using a simulated 8-electrode network, demonstrating direct impedance measurements between electrodes and the reference with 96.6% ±0.2% accuracy, and cross-channel impedance measurements with 93.3% ±0.6% accuracy in a typical system. Subsequent analyses on randomized systems demonstrate the sensitivity of the model to impedance range and measurement noise. Clinical Relevance- CCIM provides a system-agnostic diagnostic test for implanted electrode networks, which may aid in the longitudinal tracking of electrode performance and early identification of electronics failures.
9.	Earley, Eric J., et al. (author) Low-Cost, Wireless Bioelectric Signal Acquisition and Classification Platform 2024 In: IEEE Access. - 2169-3536 .- 2169-3536. ; 12, s. 69350-69358 Journal article (peer-reviewed)abstract Bioelectric signal classification is a flourishing area of biomedical research, however conducting this research in a clinical setting can be difficult to achieve. The lack of inexpensive acquisition hardware can limit researchers from collecting and working with real-time data. Furthermore, hardware requiring direct connection to a computer can impose restrictions on typically mobile clinical settings for data collection. Here, we present an open-source ADS1299-based bioelectric signal acquisition system with wireless capability suitable for mobile data collection in clinical settings. This system is based on the ADS_BP and BioPatRec, both open-source bioelectric signal acquisition hardware and MATLAB-based pattern recognition software, respectively. We provide 3D-printable housing enabling the hardware to be worn by users during experiments and demonstrate the suitability of this platform for real-time signal acquisition and classification. In conjunction, these developments provide a unified hardware-software platform for a cost of around $150 USD. This device can enable researchers and clinicians to record bioelectric signals from able-bodied or motor-impaired individuals in laboratory or clinical settings, and to perform offline or real-time intent classification for the control of robotic and virtual devices.
10.	Gusman, Jacob, et al. (author) Evaluation of Computer-Based Target Achievement Tests for Myoelectric Control 2017 In: IEEE Journal of Translational Engineering in Health and Medicine. - 2168-2372. ; 5 Journal article (peer-reviewed)abstract Real-time evaluation of novel prosthetic control schemes is critical for translational research on artificial limbs. Recently, two computer-based, real-time evaluation tools, the target achievement control (TAC) test and the Fitts' law test (FLT), have been proposed to assess real-time controllability. Whereas TAC tests provides an anthropomorphic visual representation of the limb at the cost of confusing visual feedback, FLT clarifies the current and target locations by simplified non-anthropomorphic representations. Here, we investigated these two approaches and quantified differences in common performance metrics that can result from the chosen method of visual feedback. Ten able-bodied and one amputee subject performed target achievement tasks corresponding to the FLT and TAC test with equivalent indices of difficulty. Able-bodied subjects exhibited significantly (p
11.	Lendaro, Eva, 1989, et al. (author) Real-time classification of non-weight bearing lower-limb movements using EMG to facilitate phantom motor execution: Engineering and case study application on phantom limb pain 2017 In: Frontiers in Neurology. - : Frontiers Media SA. - 1664-2295. ; 8:SEP, s. Article number 470- Journal article (peer-reviewed)abstract Phantom motor execution (PME), facilitated by myoelectric pattern recognition (MPR) and virtual reality (VR), is positioned to be a viable option to treat phantom limb pain (PLP). A recent clinical trial using PME on upper-limb amputees with chronic intractable PLP yielded promising results. However, further work in the area of signal acquisition is needed if such technology is to be used on subjects with lower-limb amputation. We propose two alternative electrode configurations to conventional, bipolar, targeted recordings for acquiring surface electromyography. We evaluated their performance in a real-time MPR task for non-weight-bearing, lower-limb movements. We found that monopolar recordings using a circumferential electrode of conductive fabric, performed similarly to classical bipolar recordings, but were easier to use in a clinical setting. In addition, we present the first case study of a lower-limb amputee with chronic, intractable PLP treated with PME. The patient's Pain Rating Index dropped by 22 points (from 32 to 10, 68%) after 23 PME sessions. These results represent a methodological advancement and a positive proof-of-concept of PME in lower limbs. Further work remains to be conducted for a high-evidence level clinical validation of PME as a treatment of PLP in lower-limb amputees.
12.	Mastinu, Enzo, 1987, et al. (author) An Alternative Myoelectric Pattern Recognition Approach for the Control of Hand Prostheses : A Case Study of Use in Daily Life by a Dysmelia Subject 2018 In: IEEE Journal of Translational Engineering in Health and Medicine. - : Institute of Electrical and Electronics Engineers (IEEE). - 2168-2372. ; 6 Journal article (peer-reviewed)abstract The functionality of upper limb prostheses can be improved by intuitive control strategies that use bioelectric signals measured at the stump level. One such strategy is the decoding of motor volition via myoelectric pattern recognition (MPR), which has shown promising results in controlled environments and more recently in clinical practice. Moreover, not much has been reported about daily life implementation and real-time accuracy of these decoding algorithms. This paper introduces an alternative approach in which MPR allows intuitive control of four different grips and open/close in a multifunctional prosthetic hand. We conducted a clinical proof-of-concept in activities of daily life by constructing a self-contained, MPR-controlled, transradial prosthetic system provided with a novel user interface meant to log errors during real-time operation. The system was used for five days by a unilateral dysmelia subject whose hand had never developed, and who nevertheless learned to generate patterns of myoelectric activity, reported as intuitive, for multi-functional prosthetic control. The subject was instructed to manually log errors when they occurred via the user interface mounted on the prosthesis. This allowed the collection of information about prosthesis usage and real-time classification accuracy. The assessment of capacity for myoelectric control test was used to compare the proposed approach to the conventional prosthetic control approach, direct control. Regarding the MPR approach, the subject reported a more intuitive control when selecting the different grips, but also a higher uncertainty during proportional continuous movements. This paper represents an alternative to the conventional use of MPR, and this alternative may be particularly suitable for a certain type of amputee patients. Moreover, it represents a further validation of MPR with dysmelia cases.
13.	Mastinu, Enzo, 1987, et al. (author) Analog Front-Ends comparison: on the way to a portable, lowpower and low-cost EMG controller based on Pattern Recognition 2015 In: Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS. - 1557-170X. - 9781424492718 ; 2015-November, s. 2111-2114 Conference paper (peer-reviewed)abstract Compact and low-noise Analog Front-Ends (AFEs)are becoming increasingly important for the acquisition ofbioelectric signals in portable system. In this work, we comparetwo popular AFEs available on the market, namely theADS1299 (Texas Instruments) and the RHA2216 (IntanTechnologies). This work develops towards the identification ofsuitable acquisition modules to design an affordable, reliableand portable device for electromyography (EMG) acquisitionand prosthetic control. Device features such as Common ModeRejection (CMR), Input Referred Noise (IRN) and Signal toNoise Ratio (SNR) were evaluated, as well as the resultingaccuracy in myoelectric pattern recognition (MPR) for thedecoding of motion intention. Results reported better noiseperformances and higher MPR accuracy for the ADS1299 andsimilar SNR values for both devices.
14.	Mastinu, Enzo, 1987, et al. (author) Digital Controller for Artificial Limbs fed by Implanted Neuromuscular Interfaces via Osseointegration 2016 In: 38th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC). ; , s. 1- Conference paper (peer-reviewed)abstract Despite the technological progress in robotics, mechatronic limbs still lack functionality, reliability and comfort. This work builds upon osseointegration and implanted neuromuscular interfaces for the realization of an embedded system for artificial upper limb control. The controller allows for bioelectric signals acquisition, processing, decoding and prosthetic control. It includes a neurostimulator to provide direct neural feedback aimed for restoration of tactile sensations. It was designed to be reliably used in activities of daily living, as well as a research platform to monitor prosthesis usage and training, machine learning based control techniques and neural stimulation paradigms. The system has passed bench tests and its functionality was proven in a first pilot patient.
15.	Mastinu, Enzo, 1987, et al. (author) Digital Controller for Artificial Limbs fed by Implanted Neuromuscular Interfaces via Osseointegration 2016 In: Trent International Prosthetic Symposium 2016. Conference paper (other academic/artistic)abstract Although the development of bioelectrically controlled upper limb prosthesis started in the 1970’s, the majority of amputees do not use this technology due to its poor functionality, reliability and comfort. This study is based on the previous work conducted by Ortiz-Catalan, Håkansson, and Brånemark, who developed a permanent bidirectional interface into the human body, namely the Osseointegrated Human-Machine Gateway (OHMG).The aim of this study was to develop an Artificial Limb Controller (ALC) that decodes motor volition and provides sensory feedback using the OHMG.
16.	Mastinu, Enzo, 1987 (author) Embedded Controller for Artificial Limbs 2017 Licentiate thesis (other academic/artistic)abstract Promising developments are currently ongoing worldwide in the field of neuroprosthetics and artificial limb control. It is now possible to chronically connect a robotic limb to bone, nerves and muscles of a human being, and use the signals sourced from these connections to enable movements in the artificial limb. It is also possible to surgically redirect a nerve, deprived from its original target muscle due to amputation, to a new target in order to restore the original motor functionality. Intelligent signal processing algorithms can now utilize the bioelectric signals gathered from remaining muscles on the stump to decode the motor intention of the amputee, providing an intuitive control interface. Unfortunately for patients, clinical implementations still lag behind the advancements of research, and the conventional solutions for amputees remained basically unchanged since decades. More efforts are therefore needed from researchers to close the gap between scientific publications and hospital practices.The ultimate focus of this thesis is set on the intuitive control of a prosthetic upper limb. It was developed an embedded system capable of prosthetic control via the processing of bioelectric signals and pattern recognition algorithms. It includes a neurostimulator to provide direct neural feedback modulated by sensory information from artificial sensors. The system was designed towards clinical implementation and its functionality was proven by amputee subjects in daily life. It also constitutes a research platform to monitor prosthesis usage and training, machine learning based control algorithms, and neural stimulation paradigms.
17.	Mastinu, Enzo, 1987, et al. (author) Embedded System for Prosthetic Control Using Implanted Neuromuscular Interfaces Accessed Via an Osseointegrated Implant 2017 In: IEEE Transactions on Biomedical Circuits and Systems. - 1940-9990 .- 1932-4545. ; 11:4, s. 867-877 Journal article (peer-reviewed)abstract Despite the technological progress in robotics achieved in the last decades, prosthetic limbs still lack functionality, reliability, and comfort. Recently, an implanted neuromusculoskeletal interface built upon osseointegration was developed and tested in humans, namely the Osseointegrated Human-Machine Gateway. Here, we present an embedded system to exploit the advantages of this technology. Our artificial limb controller allows for bioelectric signals acquisition, processing, decoding of motor intent, prosthetic control, and sensory feedback. It includes a neurostimulator to provide direct neural feedback based on sensory information. The system was validated using real-time tasks characterization, power consumption evaluation, and myoelectric pattern recognition performance. Functionality was proven in a first pilot patient from whom results of daily usage were obtained. The system was designed to be reliably used in activities of daily living, as well as a research platform to monitor prosthesis usage and training, machine-learning-based control algorithms, and neural stimulation paradigms.
18.	Mastinu, Enzo, 1987, et al. (author) Grip control and motor coordination with implanted and surface electrodes while grasping with an osseointegrated prosthetic hand 2019 In: Journal of Neuroengineering and Rehabilitation. - : Springer Science and Business Media LLC. - 1743-0003. ; 16:1 Journal article (peer-reviewed)abstract Background: Replacement of a lost limb by an artificial substitute is not yet ideal. Resolution and coordination of motor control approximating that of a biological limb could dramatically improve the functionality of prosthetic devices, and thus reduce the gap towards a suitable limb replacement. Methods: In this study, we investigated the control resolution and coordination exhibited by subjects with transhumeral amputation who were implanted with epimysial electrodes and an osseointegrated interface that provides bidirectional communication in addition to skeletal attachment (e-OPRA Implant System). We assessed control resolution and coordination in the context of routine and delicate grasping using the Pick and Lift and the Virtual Eggs Tests. Performance when utilizing implanted electrodes was compared with the standard-of-care technology for myoelectric prostheses, namely surface electrodes. Results: Results showed that implanted electrodes provide superior controllability over the prosthetic terminal device compared to conventional surface electrodes. Significant improvements were found in the control of the grip force and its reliability during object transfer. However, these improvements failed to increase motor coordination, and surprisingly decreased the temporal correlation between grip and load forces observed with surface electrodes. We found that despite being more functional and reliable, prosthetic control via implanted electrodes still depended highly on visual feedback. Conclusions: Our findings indicate that incidental sensory feedback (visual, auditory, and osseoperceptive in this case) is insufficient for restoring natural grasp behavior in amputees, and support the idea that supplemental tactile sensory feedback is needed to learn and maintain the motor tasks internal model, which could ultimately restore natural grasp behavior in subjects using prosthetic hands. © 2019 The Author(s).
19.	Mastinu, Enzo, 1987, et al. (author) Low-cost, open source bioelectric signal acquisition system 2017 In: 14th International Conference on Wearable and Implantable Body Sensor Networks. - 9781509062447 ; , s. 19-22 Conference paper (peer-reviewed)abstract Bioelectric potentials provide an intuitive source of control in human-machine interfaces. In this work, a low-cost system for bioelectric signals acquisition and processing was developed and made available as open source. A single module based on the ADS1299 (Texas Instruments, USA) can acquire up to 8 differential or single-ended channels with a resolution of 24 bits and programmable gain up to 24 V/V. Several modules can be daisy-chained together to increase the number of input channels. Opto-isolated USB communication was included in the design to interface safely with a personal computer. The system was designed to be compatible with a low-cost and widely available microcontroller development platform, namely the Tiva LaunchPad (Texas Instruments, USA) featuring an ARM Cortex-M4 core. We made the source files for the PCB, firmware, and high-level software available online (GitHub: ADS_BP). Digital processing was used for float conversion and filtering. The high-level software for control and acquisition was integrated into an already existent open source platform for advanced myoelectric control, namely BioPatRec. This integration provide a complete system for intuitive myoelectric control where signal processing, machine learning, and control algorithms are used for the prediction of motor volition and control of robotic and virtual devices.
20.	Mastinu, Enzo, 1987, et al. (author) Myoelectric signals and pattern recognition from implanted electrodes in two TMR subjects with an osseointegrated communication interface 2018 In: Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS. - 1557-170X. ; 2018-July, s. 5174-5177 Conference paper (peer-reviewed)abstract Permanent implantation of electrodes for prosthetic control is now possible using an osseointegrated implant as a long-term stable communication interface (e-OPRA). The number of myoelectric sites to host such electrodes can be increased by Targeted Muscle Reinnervation (TMR). Traditionally, patients need to wait several months before the TMR signals are strong enough to be recorded by electrodes placed over the skin. In this study, we report the evolution of the TMR myoelectric signals recorded from two subjects via implanted electrodes using e-OPRA, and monitored for up to 48 weeks after surgery. The signals were analyzed with regard to amplitude (signal-to-noise ratio), independence (cross-correlation) and myoelectric pattern recognition (classification accuracy). TMR signals appeared at the first follow-up, one month post-surgery, and developed around 20 dB by the last. Cross-correlation between signals decreased over time and converged to a few percentage points. Classification accuracies were over 97% by the last follow up. These preliminary results suggest that implanted electrodes via the e-OPRA interface allow for an earlier and more effective use of motor signals from TMR sites compared to conventional skin surface electrodes.
21.	Mastinu, Enzo, 1987 (author) Towards clinically viable neuromuscular control of bone-anchored prosthetic arms with sensory feedback 2019 Doctoral thesis (other academic/artistic)abstract Promising developments are currently ongoing worldwide in the field of neuroprosthetics and artificial limb control. It is now possible to chronically connect a robotic limb to bone, nerves, and muscles of a human being, and to use the signals sourced from these connections to enable movements of the artificial limb. It is also possible to surgically redirect a nerve, deprived from its original target muscle due to amputation, to a new target in order to restore the original motor functionality. Intelligent signal processing algorithms can now utilize the bioelectric signals gathered from remaining muscles on the stump to decode the motor intention of the amputee, providing an intuitive control interface. Unfortunately, clinical implementations still lag behind the advancements made in research, and the conventional solutions for amputees have remained largely unchanged for decades. More efforts are needed from researchers to close the gap between scientific developments and clinical practices. This thesis ultimately focuses on the intuitive control of a prosthetic upper limb. In the first part of this doctoral project, an embedded system capable of prosthetic control via the processing of bioelectric signals and pattern recognition algorithms was developed. The design included a neurostimulator to provide direct neural feedback modulated by sensory information from artificial sensors. The system was designed towards clinical implementation and its functionality was proven by its use by amputee subjects in daily life. This system was then used during the second part of the doctoral project as a research platform to monitor prosthesis usage and training, machine learning based control algorithms, and neural stimulation paradigms for tactile sensory feedback. Within this work, a novel method for interfacing a multi-grip prosthetic hand to facilitate posture selection via pattern recognition was proposed. Moreover, the need for tactile sensory feedback was investigated in order to restore natural grasping behavior in amputees. Notably, the benefit for motor coordination of somatotopic tactile feedback achieved via direct neural stimulation was demonstrated. The findings and the technology developed during this project open to the clinical use of a new class of prosthetic arms that are directly connected to the neuromusculoskeletal system, intuitively controlled and capable of tactile sensory feedback.
22.	Matran-Fernandez, A., et al. (author) Crosstalk Reduction in Epimysial EMG Recordings from Transhumeral Amputees with Principal Component Analysis 2018 In: Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS. - 1557-170X. ; 2018-July, s. 2124-2127 Conference paper (peer-reviewed)abstract Electromyographic (EMG) recordings of muscle activity using monopolar electrodes suffer from poor spatial resolution due to the crosstalk from neighbouring muscles. This effect has mainly been studied on surface EMG recordings. Here, we use Principal Component Analysis (PCA) to reduce the crosstalk in recordings from unipolar epimysial electrodes implanted in three transhumeral amputees. We show that the PCA-transformed signals have, on average, a better signal-tonoise ratio than the original unipolar recordings. Preliminary investigations show that this transformation is stable over long periods of time. If the latter is confirmed, our results show that the combination of PCA with unipolar electrodes allows for a higher number of muscles to be targeted in an implant (compared with bipolar electrodes), thus facilitating 1-to-1 proportional control of prosthetic hands.
23.	Merad, M., et al. (author) Assessment of an automatic prosthetic elbow control strategy using residual limb motion for transhumeral amputated individuals with socket or osseointegrated prostheses 2020 In: IEEE Transactions on Medical Robotics and Bionics. - 2576-3202. ; 2:1, s. 38-49 Journal article (peer-reviewed)abstract Most transhumeral amputated individuals deplore the lack of functionality of their prosthesis due to control-related limitations. Commercialized prosthetic elbows are controlled via myoelectric signals, yielding complex control schemes when users have to control an entire prosthetic limb. Limited control causes the development of compensatory strategies. An alternative control strategy associates residual limb motions to automatize the prosthetic elbow motion using a model of physiological shoulder/elbow synergies. Preliminary studies have shown that elbow motion could be predicted from residual limb kinematic measurements, but results with transhumeral amputated individuals were lacking. This study focuses on the experimental assessment of automatic prosthetic elbow control during a reaching task, compared to conventional myoelectric control, with six transhumeral amputated individuals, among whom, three had an osseointegrated device. Part of the recruited participants had an osseointegrated prosthetic device. The task was achieved within physiological precision errors with both control modes. Automatic elbow control reduced trunk compensations, and restored a physiologically-like shoulder/elbow movement synchronization. However, the kinematic assessment showed that amputation and prosthesis wear modifies the shoulder movements in comparison with physiological shoulder kinematics. Overall, participants described the automatic elbow control strategy as intuitive, and this work highlights the interest of automatized prosthetic elbow motion.
24.	Naber, Autumn, 1988, et al. (author) Stationary wavelet processing and data imputing in myoelectric pattern recognition on a low-cost embedded system 2019 In: IEEE Transactions on Medical Robotics and Bionics. - 2576-3202. ; 1:4, s. 256-266 Journal article (peer-reviewed)abstract Pattern recognition-based decoding of surface electromyography allows for intuitive and flexible control of prostheses but comes at the cost of sensitivity to in-band noise and sensor faults. System robustness can be improved with wavelet-based signal processing and data imputing, but no attempt has been made to implement such algorithms on real-time, portable systems. The aim of this work was to investigate the feasibility of low-latency, wavelet-based processing and data imputing on an embedded device capable of controlling upper-arm prostheses. Nine able-bodied subjects performed Motion Tests while inducing transient disturbances. Additional investigation was performed on pre-recorded Motion Tests from 15 able-bodied subjects with simulated disturbances. Results from real-time tests were inconclusive, likely due to the low number of disturbance episodes, but simulated tests showed significant improvements in most metrics for both algorithms. However, both algorithms also showed reduced responsiveness during disturbance episodes. These results suggest wavelet-based processing and data imputing can be implemented in portable, real-time systems to potentially improve robustness to signal distortion in prosthetic devices with the caveat of reduced responsiveness for the typically short duration of signal disturbances. The trade-off between large-scale signal corruption robustness and system responsiveness warrants further studies in daily life activities.
25.	Ortiz Catalan, Max Jair, 1982, et al. (author) A highly integrated bionic hand with neural control and feedback for use in daily life 2023 In: Science Robotics. - 2470-9476. ; 8:83 Journal article (peer-reviewed)abstract Restoration of sensorimotor function after amputation has remained challenging because of the lack of human-machine interfaces that provide reliable control, feedback, and attachment. Here, we present the clinical implementation of a transradial neuromusculoskeletal prosthesis-a bionic hand connected directly to the user's nervous and skeletal systems. In one person with unilateral below-elbow amputation, titanium implants were placed intramedullary in the radius and ulna bones, and electromuscular constructs were created surgically by transferring the severed nerves to free muscle grafts. The native muscles, free muscle grafts, and ulnar nerve were implanted with electrodes. Percutaneous extensions from the titanium implants provided direct skeletal attachment and bidirectional communication between the implanted electrodes and a prosthetic hand. Operation of the bionic hand in daily life resulted in improved prosthetic function, reduced postamputation, and increased quality of life. Sensations elicited via direct neural stimulation were consistently perceived on the phantom hand throughout the study. To date, the patient continues using the prosthesis in daily life. The functionality of conventional artificial limbs is hindered by discomfort and limited and unreliable control. Neuromusculoskeletal interfaces can overcome these hurdles and provide the means for the everyday use of a prosthesis with reliable neural control fixated into the skeleton.
26.	Ortiz Catalan, Max Jair, 1982, et al. (author) Chronic Use of a Sensitized Bionic Hand Does Not Remap the Sense of Touch 2020 In: Cell Reports. - : Elsevier BV. - 2211-1247. ; 33:12 Journal article (peer-reviewed)abstract Electrical stimulation of tactile nerve fibers can be used to restore touch through a bionic hand. Ortiz-Catalan et al. show that a mismatch between the location of the sensor on the bionic hand and the tactile experience is not resolved after long-term prosthesis use.
27.	Ortiz Catalan, Max Jair, 1982, et al. (author) Patterned Stimulation of Peripheral Nerves Produces Natural Sensations With Regards to Location but Not Quality 2019 In: IEEE Transactions on Medical Robotics and Bionics. - 2576-3202. ; 1:3, s. 199-203 Journal article (peer-reviewed)abstract Sensory feedback is crucial for dexterous manipulation and sense of ownership. Electrical stimulation of severed afferent fibers due to an amputation elicits referred sensations in the missing limb. However, these sensations are commonly reported with a concurrent “electric” or “tingling” character (paresthesia). In this paper, we examined the effect of modulating different pulse parameters on the quality of perceived sensations. Three subjects with above-elbow amputation were implanted with cuff electrodes and stimulated with a train of pulses modulated in either amplitude, width, or frequency (“patterned stimulation”). Pulses were shaped using a slower carrier wave or via quasi-random generation. Subjects were asked to evaluate the natural quality of the resulting sensations using a numeric rating scale. We found that the location of the percepts was distally referred and somatotopically congruent, but their quality remained largely perceived as artificial despite employing patterned modulation. Sensations perceived as arising from the missing limb are intuitive and natural with respect to their location and, therefore, useful for functional restoration. However, our results indicate that sensory transformation from paresthesia to natural qualia seems to require more than patterned stimulation.
28.	Ortiz Catalan, Max Jair, 1982, et al. (author) Self-Contained Neuromusculoskeletal Arm Prostheses 2020 In: New England Journal of Medicine. - 0028-4793 .- 1533-4406. ; 382:18, s. 1732-1738 Journal article (peer-reviewed)abstract After transhumeral amputation, four patients had implantation of a self-contained, osseointegrated prosthesis with a neuromusculoskeletal interface that allowed intuitive control of the prosthetic hand and arm over 3 to 7 years. A video shows use of the prostheses in daily life. We report the use of a bone-anchored, self-contained robotic arm with both sensory and motor components over 3 to 7 years in four patients after transhumeral amputation. The implant allowed for bidirectional communication between a prosthetic hand and electrodes implanted in the nerves and muscles of the upper arm and was anchored to the humerus through osseointegration, the process in which bone cells attach to an artificial surface without formation of fibrous tissue. Use of the device did not require formal training and depended on the intuitive intent of the user to activate movement and sensory feedback from the prosthesis. Daily use resulted in increasing sensory acuity and effectiveness in work and other activities of daily life. (Funded by the Promobilia Foundation and others.)
29.	Zbinden, Jan, 1994, et al. (author) Improved control of a prosthetic limb by surgically creating electro-neuromuscular constructs with implanted electrodes 2023 In: Science translational medicine. - 1946-6234 .- 1946-6242. ; 15:704 Journal article (peer-reviewed)abstract Remnant muscles in the residual limb after amputation are the most common source of control signals for prosthetic hands, because myoelectric signals can be generated by the user at will. However, for individuals with amputation higher up the arm, such as an above-elbow (transhumeral) amputation, insufficient muscles remain to generate myoelectric signals to enable control of the lost arm and hand joints, thus making intuitive control of wrist and finger prosthetic joints unattainable. We show that severed nerves can be divided along their fascicles and redistributed to concurrently innervate different types of muscle targets, particularly native denervated muscles and nonvascularized free muscle grafts. We engineered these neuromuscular constructs with implanted electrodes that were accessible via a permanent osseointegrated interface, allowing for bidirectional communication with the prosthesis while also providing direct skeletal attachment. We found that the transferred nerves effectively innervated their new targets as shown by a gradual increase in myoelectric signal strength. This allowed for individual flexion and extension of all five fingers of a prosthetic hand by a patient with a transhumeral amputation. Improved prosthetic function in tasks representative of daily life was also observed. This proof-of-concept study indicates that motor neural commands can be increased by creating electro-neuromuscular constructs using distributed nerve transfers to different muscle targets with implanted electrodes, enabling improved control of a limb prosthesis.

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