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1.	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.
2.	Ortiz Catalan, Max Jair, 1982, et al. (author) Offline Accuracy: A Potentially Misleading Metric in Myoelectric Pattern Recognition for Prosthetic Control. 2015 In: Proceedings of the 37th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC), Milan, Italy, 15-19 August 2015. - 1557-170X. - 9781424492718 ; , s. 1140-1143 Conference paper (peer-reviewed)abstract Offline accuracy has been the preferred performance measure in myoelectric pattern recognition (MPR) for the prediction of motion volition. In this study, different metrics relating the fundamental binary prediction outcomes were analyzed. Our results indicate that global accuracy is biased by 1) the unbalanced number of possible true positive and negative outcomes, and 2) the almost perfect specificity and negative predicted value, which were consistently found across algorithms, topologies, and movements (individual and simultaneous). Therefore, class-specific accuracy is advisable instead. Additionally, we propose the use of precision (positive predictive value) and sensitivity (recall) as a complement to accuracy to better describe the discrimination capabilities of MPR algorithms, as these consider the effect of false predictions. However, all the studied offline metrics failed to predict real-time decoding, and therefore real-time testing continue to be necessary to truly evaluate the clinical usability of MPR.
3.	Sambo, Francesco, et al. (author) A Bayesian Network analysis of the probabilistic relations between risk factors in the predisposition to type 2 diabetes 2015 In: 2015 37th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC). - 1557-170X. - 9781424492718 ; 2015, s. 22-2119 Conference paper (peer-reviewed)abstract In order to better understand the relations between different risk factors in the predisposition to type 2 diabetes, we present a Bayesian Network analysis of a large dataset, composed of three European population studies. Our results show, together with a key role of metabolic syndrome and of glucose after 2 hours of an Oral Glucose Tolerance Test, the importance of education, measured as the number of years of study, in the predisposition to type 2 diabetes.
4.	Iyer, Srinivasan, et al. (author) Interpreting the dipolar plasmon resonance of rectangular metallic nanoantennas In: Plasmonics. - 1557-1955 .- 1557-1963. Journal article (other academic/artistic)
5.	Abualhoul, Mohammad Y., et al. (author) Free space optical link for biomedical applications 2012 In: Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS. - 1557-170X. - 9781424441198 ; , s. 1667-1670 Conference paper (peer-reviewed)abstract Free space optics is an interesting alternative for telemetry with medical implants, due to the high data bandwidths available at optical frequencies. Especially implanted brain-computer interfaces gives rise to large data sets that needs to be transmitted transcutaneous. In this paper we show that it is possible to establish such a link at near-IR wavelengths using a modulated reflector in the implant, thus keeping the laser and the detector on the outside. In addition, we show that it will not only work on short, i.e. touch, distances but also at larger distances, in the range of a meter. We have used an electro absorption modulator to modulate the reflection of an external laser source back towards an external detector. The only part of this system that needs to be implanted is the modulator and drive electronics. The study has been done both by Monte-Carlo simulations of a multi-layer model of a rat skull, and with an experiment demonstrating the feasibility of the link when transmitted through biological tissue. The results show that it is possible to establish a transcutaneous link with an external laser source and light detector, and an internal modulated reflector.
6.	Ahkami, Bahareh, 1994, et al. (author) Probability-Based Rejection of Decoding Output Improves the Accuracy of Locomotion Detection During Gait 2023 In: Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS. - 1557-170X. Conference paper (peer-reviewed)abstract Prosthetic users need reliable control over their assistive devices to regain autonomy and independence, particularly for locomotion tasks. Despite the potential for myoelectric signals to reflect the users' intentions more accurately than external sensors, current motorized prosthetic legs fail to utilize these signals, thus hindering natural control. A reason for this challenge could be the insufficient accuracy of locomotion detection when using muscle signals in activities outside the laboratory, which may be due to factors such as suboptimal signal recording conditions or inaccurate control algorithms.This study aims to improve the accuracy of detecting locomotion during gait by utilizing classification post-processing techniques such as Linear Discriminant Analysis with rejection thresholds. We utilized a pre-recorded dataset of electromyography, inertial measurement unit sensor, and pressure sensor recordings from 21 able-bodied participants to evaluate our approach. The data was recorded while participants were ambulating between various surfaces, including level ground walking, stairs, and ramps. The results of this study show an average improvement of 3% in accuracy in comparison with using no post-processing (p-value < 0.05). Participants with lower classification accuracy profited more from the algorithm and showed greater improvement, up to 8% in certain cases. This research highlights the potential of classification post-processing methods to enhance the accuracy of locomotion detection for improved prosthetic control algorithms when using electromyogram signals.Clinical Relevance-Decoding of locomotion intent can be improved using post-processing techniques thus resulting in a more reliable control of lower limb prostheses.
7.	Alcaraz Martinez, Raul, et al. (author) Application of frequency and sample entropy to discriminate long-term recordings of paroxysmal and persistent atrial fibrillation 2010 In: Engineering in Medicine and Biology Society (EMBC), 2010 Annual International Conference of the IEEE. - 1557-170X. - 9781424441235 ; , s. 4558-4561 Conference paper (peer-reviewed)abstract Atrial fibrillation (AF) is the most common arrhythmia in clinical practice. At an early stage of the disease, AF may terminate spontaneously and is then referred to as paroxysmal AF. On the other hand, when external intervention is required for the arrhythmia to terminate, it is referred to as persistent AF. In this work, a method to discriminate between paroxysmal and persistent AF in the long-term ECGs is presented. The dominant frequency as well as the organization of the atrial activity are employed to characterize AF. The dominant atrial frequency (DAF) is estimated using hidden Markov model based frequency tracking, and organization is estimated by the sample entropy of the main atrial wave (MAW) and the first two harmonics, respectively. Long-term variations in DAF and organization from 50 ECG recordings were evaluated, showing that episodes of paroxysmal AF were consistently associated with lower DAF and organization of the MAW and the harmonics, than was persistent AF. Discrimination of paroxysmal and persistent AF resulted in classification rates of 84.1±26.1%, thus suggesting that it possible to discriminate between paroxysmal and persistent AF in patients without previously known AF history.
8.	Alipoor, Mohammad, 1983, et al. (author) On High Order Tensor-based Diffusivity Profile Estimation 2013 In: Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS. - 1557-170X. - 9781457702167 ; , s. 93-96, s. 4- Conference paper (peer-reviewed)abstract Diffusion weighted magnetic resonance imaging (dMRI) is used to measure, in vivo, the self-diffusion of water molecules in biological tissues. High order tensors (HOTs) are used to model the apparent diffusion coefficient (ADC) profile at each voxel from the dMRI data. In this paper we propose: (i) A new method for estimating HOTs from dMRI data based on weighted least squares (WLS) optimization; and (ii) A new expression for computing the fractional anisotropy from a HOT that does not suffer from singularities and spurious zeros. We also present an empirical evaluation of the proposed method relative to the two existing methods based on both synthetic and real human brain dMRI data. The results show that the proposed method yields more accurate estimation than the competing methods.
9.	Anderson, Rachele, et al. (author) Insights on Spectral Measures for HRV Based on a Novel Approach for Data Acquisition 2018 In: Annual International Conference of the IEEE Engineering in Medicine and Biology - Proceedings. - 1557-170X. ; 2018, s. 510-513 Journal article (peer-reviewed)abstract In this paper, we present new insights on classical spectral measures for heart rate variability (HRV), based on a novel method for HRV acquisition. A dynamic breathing task, where the test participants are asked to breathe following a metronome with slowly increasing frequency, allows for the acquisition of respiratory-related HRV-data covering the frequency range in which adults breathe in different everyday situations. We discuss how the use of a time-frequency representation, e.g. the spectrogram or the Wigner-Ville distribution, should be preferred to the traditional use of the periodogram, due to the non-stationarity of the data. We argue that this approach can highlight the correlation of spectral measures such as low-frequency and high-frequency HRV with relevant factors as age, gender and Body-Mass-Index, thanks to the improved quality of the spectral measures.
10.	Behjat, Hamid, et al. (author) Canonical cerebellar graph wavelets and their application to fMRI activation mapping 2014 In: [Host publication title missing]. - 1557-170X. ; , s. 1039-1042 Conference paper (peer-reviewed)abstract Wavelet-based statistical parametric mapping (WSPM) is an extension of the classical approach in fMRI activation mapping that combines wavelet processing with voxel-wise statistical testing. We recently showed how WSPM, using graph wavelets tailored to the full gray-matter (GM) structure of each individual’s brain, can improve brain activity detection compared to using the classical wavelets that are only suited for the Euclidian grid. However, in order to perform analysis on a subject-invariant graph, canonical graph wavelets should be designed in normalized brain space. We here introduce an approach to define a fixed template graph of the cerebellum, an essential component of the brain, using the SUIT cerebellar template. We construct a corresponding set of canonical cerebellar graph wavelets, and adopt them in the analysis of both synthetic and real data. Compared to classical SPM, WSPM using cerebellar graph wavelets shows superior type-I error control, an empirical higher sensitivity on real data, as well as the potential to capture subtle patterns of cerebellar activity.
11.	Brown, Shannon, et al. (author) Intarsia-sensorized band and textrodes for real-time myoelectric pattern recognition 2016 In: Engineering in Medicine and Biology Society (EMBC), 2016 IEEE 38th Annual International Conference of the. - : Institute of Electrical and Electronics Engineers (IEEE). - 1557-170X. - 9781457702204 ; , s. 6074-6077 Conference paper (peer-reviewed)abstract Surface Electromyography (sEMG) has applications in prosthetics, diagnostics and neuromuscular rehabilitation. Self-adhesive Ag/AgCl are the electrodes preferentially used to capture sEMG in short-term studies, however their long-term application is limited. In this study we designed and evaluated a fully integrated smart textile band with electrical connecting tracks knitted with intarsia techniques and knitted textile electrodes. Real-time myoelectric pattern recognition for motor volition and signal-to-noise ratio (SNR) were used to compare its sensing performance versus the conventional Ag-AgCl electrodes. After a comprehending measurement and performance comparison of the sEMG recordings, no significant differences were found between the textile and the Ag-AgCl electrodes in SNR and prediction accuracy obtained from pattern recognition classifiers.
12.	Caltenco, Héctor, et al. (author) TongueWise : tongue-computer interface software for people with tetraplegia 2010 In: International Conference of the IEEE Engineering in Medicine and Biology Society. - 1557-170X. - 9781424441235 ; 32, s. 4534-4537 Conference paper (peer-reviewed)abstract Many computer interfaces and assistive devices for people with motor disabilities limit the input dimensionality from user to system, in many cases leading to single switch interfaces where the user can only press one button. This can, either limit the level of direct access to the functionalities of the operating system, or slow down speed of interaction. In this paper we present TongueWise: a software developed for a tongue computer interface that can be activated with the tip of the tongue and that provides direct input that covers most of the standard keyboard and mouse commands.
13.	Candefjord, Stefan, 1981, et al. (author) Microwave technology for localization of traumatic intracranial bleedings—a numerical simulation study 2013 In: Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS. - 1557-170X. - 9781457702167 ; , s. 1948-1951 Conference paper (peer-reviewed)abstract Traumatic brain injury (TBI) is a major public health problem worldwide. Intracranial bleedings represents the most serious complication of TBI and need to be surgically evacuated promptly to save lives and mitigate injury. Microwave technology (MWT) is promising as a complement to computed tomography (CT) to be used in road and air ambulances for early detection of intracranial bleedings. In this study, we perform numerical simulations to investigate if a classification algorithm based on singular value decomposition can distinguish between bleedings at different positions adjacent to the skull bone for a similar but simplified problem. The classification accuracy is 94-100% for all classes, a result that encourages us to pursue our efforts with MWT for more realistic scenarios. This indicates that MWT has potential for localizing a detected bleeding, which would increase the diagnostic value of this technique.
14.	Chandra, Rohit, et al. (author) An Approach to Analyze the Movements of the Arms while Walking using Wearable Wireless Devices 2013 In: [Host publication title missing]. - 1557-170X. ; , s. 3435-3438 Conference paper (peer-reviewed)abstract Abstract—Rhythmic movement of the arms while walking is an important feature of human gait. In this paper, we present an approach to analyze the movements of the arms while walking by using three wearable wireless devices placed around the torso. One of the devices is transmitter placed at the back and the other two are symmetrically placed receivers that record the power variation due to movements of the arms while walking. We show that the power received by the receivers will have symmetrical variation if the arms’ swing is symmetrical. An analytical model has been used to calculate the position of the receivers. Full wave simulations on a walking phantom are done to confirm the results.
15.	Chandra, Rohit, et al. (author) Miniaturized antennas for link between binaural hearing aids 2010 In: Annual International Conference of the IEEE Engineering in Medicine and Biology Society.. - 1557-170X. ; 1, s. 688-691 Conference paper (peer-reviewed)abstract We have investigated the possibility of using the 2.45 GHz ISM band for communication between binaural hearing aids. The small size of a modern hearing aid makes it necessary to miniaturize the antennas to make this feasible. Two different types of hearing aid placements have been investigated: in the outer ear and in the ear canal. Both put strict demands on the size of the antenna, which have been miniaturized by applying disc loads and high permittivity materials. The investigations have been done by FDTD simulation of a modified SAM phantom head, where we have included a simple model of the ear canal. Simulations show that the outer ear placement is better, as it gives a total link loss of 48 dB. The placement in the ear canal gives a total link loss of 92 dB.
16.	Corino, V. D. A., et al. (author) A Gaussian mixture model for time-frequency analysis during atrial fibrillation electrocardiograms 2007 In: 29th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS 2007.. - 1557-170X. - 9781424407880 ; , s. 271-274 Conference paper (peer-reviewed)abstract During atrial fibrillation (AF), time-frequency analysis of atrial signal has been applied to describe fibrillatory frequency trends. Recently, temporal changes in spectral shape have been investigated using the spectral profile technique. This profile is computed recursively by fitting each short-time log-spectrum to a spectral template, using amplitude scaling and frequency shifting. The purpose of the present study was to develop a Gaussian mixture model of the spectral profile in order to characterize the shape of AF waveforms. A novel index is introduced, the so-called harmonic index (HI), which reflects properties of the fundamental frequency peak and related harmonics peaks as estimated from the model. The index was tested on recordings from 9 patients with persistent AF, obtained before and after exercise testing. The HI succeeded in monitoring the response to exercise, i.e. change in the spectral profile to a less harmonic pattern, which is consistent with a reduction in AF organization (HI: 0.61±0.11 vs. 0.50±0.19, rest vs. exercise; p≪0.05).
17.	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. ; , 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.
18.	Gavrilis, Dimitris, et al. (author) A One-Class Approach to Cardiotocogram Assessment 2015 In: 37th Annual International Conference of the IEEE Engineering in Medicine and Biology Society. - Piscataway, NJ : IEEE Communications Society. - 9781424492718 ; , s. 518-521 Conference paper (peer-reviewed)abstract Cardiotocogram (CTG) is the most widely used means for the assessment of fetal condition. CTG consists of two traces one depicting the Fetal Heart Rate (FHR), and the other the Uterine Contractions (UC) activity. Many automatic methods have been proposed for the interpretation of the CTG. Most of them rely either on a binary classification approach or on a multiclass approach to come up with a decision about the class that the tracing belongs to. This work investigates the use of a one-class approach to the assessment of CTGs building a model only for the healthy data. The preliminary results are promising indicating that normal traces could be used as part of an automatic system that can detect deviations from normality.
19.	Ge, Chenjie, 1991, et al. (author) Co-Saliency-Enhanced Deep Recurrent Convolutional Networks for Human Fall Detection in E-Healthcare 2018 In: Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS. - 1557-170X. ; , s. 1572-1575 Conference paper (peer-reviewed)abstract This paper addresses the issue of fall detection from videos for e-healthcare and assisted-living. Instead of using conventional hand-crafted features from videos, we propose a fall detection scheme based on co-saliency-enhanced recurrent convolutional network (RCN) architecture for fall detection from videos. In the proposed scheme, a deep learning method RCN is realized by a set of Convolutional Neural Networks (CNNs) in segment-levels followed by a Recurrent Neural Network (RNN), Long Short-Term Memory (LSTM), to handle the time-dependent video frames. The co-saliency-based method enhances salient human activity regions hence further improves the deep learning performance. The main contributions of the paper include: (a) propose a recurrent convolutional network (RCN) architecture that is dedicated to the tasks of human fall detection in videos; (b) integrate a co-saliency enhancement to the deep learning scheme for further improving the deep learning performance; (c) extensive empirical tests for performance analysis and evaluation under different network settings and data partitioning. Experiments using the proposed scheme were conducted on an open dataset containing multicamera videos from different view angles, results have shown very good performance (test accuracy 98.96%). Comparisons with two existing methods have provided further support to the proposed scheme.
20.	Ge, Chenjie, 1991, et al. (author) Deep Learning and Multi-Sensor Fusion for Glioma Classification Using Multistream 2D Convolutional Networks 2018 In: Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS. - 1557-170X. ; , s. 5894-5897 Conference paper (peer-reviewed)abstract This paper addresses issues of brain tumor, glioma, grading from multi-sensor images. Different types of scanners (or sensors) like enhanced T1-MRI, T2-MRI and FLAIR, show different contrast and are sensitive to different brain tissues and fluid regions. Most existing works use 3D brain images from single sensor. In this paper, we propose a novel multistream deep Convolutional Neural Network (CNN) architecture that extracts and fuses the features from multiple sensors for glioma tumor grading/subcategory grading. The main contributions of the paper are: (a) propose a novel multistream deep CNN architecture for glioma grading; (b) apply sensor fusion from T1-MRI, T2-MRI and/or FLAIR for enhancing performance through feature aggregation; (c) mitigate overfitting by using 2D brain image slices in combination with 2D image augmentation. Two datasets were used for our experiments, one for classifying low/high grade gliomas, another for classifying glioma with/without 1p19q codeletion. Experiments using the proposed scheme have shown good results (with test accuracy of 90.87% for former case, and 89.39 % for the latter case). Comparisons with several existing methods have provided further support to the proposed scheme.
21.	Gu, Irene Yu-Hua, 1953, et al. (author) 3D Limb Movement Tracking and Analysis for Neurological Dysfunctions of Neonates Using Multi-Camera Videos 2016 In: Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS. - 1557-170X. - 9781457702204 ; 2016-October, s. 2395-2398 Conference paper (peer-reviewed)abstract Central nervous system dysfunction in infants may be manifested through inconsistent, rigid and abnormal limb movements. Detection of limb movement anomalies associated with such neurological dysfunctions in infants is the first step towards early treatment for improving infant development. This paper addresses the issue of detecting and quantifying limb movement anomalies in infants through non-invasive 3D image analysis methods using videos from multiple camera views. We propose a novel scheme for tracking 3D time trajectories of markers on infant’s limbs by video analysis techniques. The proposed scheme employ videos captured from three camera views. This enables us to detect a set of enhanced 3D markers through cross-view matching and to effectively handle marker self-occlusions by other body parts. We track a set of 3D trajectories of limb movements by a set of particle filters in parallel, enabling more robust 3D tracking of markers, and use the 3D model errors for quantifying abrupt limb movements. The proposed work makes a significant advancement to the previous work in [1] through employing tracking in 3D space, and hence overcome several main barriers that hinder real applications by using single camera-based techniques. To the best of our knowledge, applying such a multi-view video analysis approach for assessing neurological dysfunctions of infants through 3D time trajectories of markers on limbs is novel, and could lead to computer-aided tools for diagnosis of dysfunctions where early treatment may improve infant development. Experiments were conducted on multi-view neonate videos recorded in a clinical setting and results have provided further support to the proposed method.
22.	Gund, Anna, 1980, et al. (author) Design Evaluation of a Home-Based Telecare System for Chronic Heart Failure Patients 2008 In: Engineering in Medicine and Biology Society, 2008. EMBS 2008. 30th Annual International Conference of the IEEE. - : IEEE. - 1557-170X. - 9781424418145 ; , s. 5851-5854, s. 5851-5854 Conference paper (peer-reviewed)abstract In order to improve the care of Chronic Heart Failure (CHF) patients, a system has been developed for monitoring symptoms and document subjective judgments on health conditions in a home environment. Since system usability is an important issue, a two step evaluation of the solution was conducted. First a ten-patient survey was conducted, which was aimed at spotting possible problem areas. The second step involved a small trial in a home setting with CHF patients. The results are promising, indicating that the system is user friendly and easy to use, and that it is suitable as a prototype for the intended use.
23.	Herreros, Alberto, et al. (author) An Algorithm for Phase-Space Detection of the P Characteristic Points 2007 In: PROC. annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC2007). Lyon, France, Aug 23-26, 2007. - 1557-170X. ; 1, s. 2004-2007 Conference paper (peer-reviewed)abstract A new algorithm, based on embedding phase space, to detect the P-wave characteristic points of an ECG signal is reported in this paper. The multi-lead ECG is transformed into points of an embedding phase space where similar ECG morphologies are converted into phase space points that are close using some distance measure. The algorithm is robust with respect to the type of selected characteristic points (onset, peak and end), morphology changes, baseline oscillations and high frequency noise. The performance of the algorithm has been succesfully validated using both simulated and real ECG signals.
24.	Hill, Andrew, et al. (author) Edge intensity normalization as a bias field correction during balloon snake segmentation of breast MRI 2008 In: Proc. 2008 Annual International Conference of the IEEE Engineering in Medicine and Biology Society. - 1557-170X. ; , s. 3040 - 3043 Conference paper (peer-reviewed)abstract Segmentation of fat suppressed dynamic contrast enhanced MRI (DCE-MRI) image data can pose significant problems because of the inherently poor signal-to-noise ratio (SNR) and intensity variations due to the bias field. Segmentation methods such as balloon snakes, while able to operate in a poor SNR environment, are sensitive to variations in edge intensity, which are regularly encountered within DCE-MRI due to the bias field. In order to overcome the effects of the bias field, an intensity normalization based on the strength of the strongest edge, i.e. the skin-air-boundary, is proposed and evaluated. This normalization allows balloon segmentations to be run three times faster while maintaining, or even improving accuracy.
25.	Ivica, Nedjeljka, et al. (author) Design of a high-density multi-channel electrode for multi-structure parallel recordings in rodents 2014 In: 2014 36th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC). - 1557-170X. ; , s. 393-396 Conference paper (peer-reviewed)abstract In neurophysiology, investigating brain connectivity within and between different brain structures is of fundamental importance for understanding nervous system function and its relation to behavior. Yet, parallel recordings in multiple brain structures is highly challenging, especially in rodents, which are most commonly employed in neurophysiological research but rather small in size. In this study, the design and manufacturing of a high-density multi-channel electrode for chronic, multi-structure parallel recordings in rats is presented and exemplified with functional neuronal recordings from 128 recording channels, placed bilaterally in eight different brain structures, in an awake, freely moving animal.
26.	Johansson, Rolf, et al. (author) Adaptation of Multi-Joint Movements during Postural Disturbances. 2004 In: Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Conference. - 1557-170X. - 0780384393 ; 1, s. 149-152 Conference paper (peer-reviewed)abstract The objective was to investigate the adaptation ofthe multi-segmented body movements induced over time byvibratory proprioceptive stimulation of the calf muscles and by galvanic vestibular stimulation. Twelve normal subjects were with eyes open or eyes closed exposed to vibratory stimulation of two different amplitudes and frequencies, or to simultaneously applied galvanic and vibratory stimulation. Multi-input multi-output system identification methods as well as quantitative analysis were applied to the biomechanical experimental data of anteroposterior and lateral body movements and torques induced towards the ground. The immediate adaptive response to the stimulation onset was that the subjects adopted a more rigid posture with coordinated movements of primarily head-shoulder and headhip body segments. The body-movement amplitudes at allmeasured sites as well as the amplitudes of the ground support forces decreased over time as a result of another, somewhat slower adaptation process. The subjects required more time to adapt to a rigid movement pattern when the subjects were simultaneously exposed to both galvanic and vibratorystimulation. Moreover, the accuracy of the MIMO model andcorrelation analysis between measured torque variance andhead; shoulder; hip and knee movement variance suggests thatforce platform recordings reflect both in anteroposterior and lateral direction the body movements at these sites.
27.	Kanitz, Gunter, et al. (author) Decoding of individuated finger movements using surface EMG and input optimization applying a genetic algorithm. 2011 In: [Host publication title missing]. - 1557-170X. - 9781424441211 ; , s. 1608-1611 Conference paper (peer-reviewed)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.
28.	Karlsson, M, et al. (author) Wireless system for real-time recording of heart rate variability for home nursing. 2005 In: Conference proceedings : ... Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Conference. - 1557-170X. ; 4, s. 3717-9 Journal article (peer-reviewed)abstract Modern wireless communication technologies offer new possibilities for patient monitoring in hospitals, as well as at home or in outdoor environments. In this paper, we present a wireless system for ECG recordings and real-time analysis of heart rate variability (HRV). The system also makes it possible for distance consultation, for example with a specialist in cardiology, with the help of a WEB-solution.
29.	Klang, Marcus, et al. (author) Using Operative Reports to Predict Heart Transplantation Survival 2022 In: 44th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2022. - 1557-170X. - 9781728127828 ; 2022-July, s. 2258-2261 Conference paper (peer-reviewed)abstract Heart transplantation is a difficult procedure compared with other surgical operations, with a greater outcome uncertainty such as late rejection and death. We can model the success of heart transplants from predicting factors such as the age, sex, diagnosis, etc., of the donor and recipient. Although predictions can mitigate the uncertainty on the transplantation outcome, their accuracy is far from perfect. In this paper, we describe a new method to predict the outcome of a transplantation from textual operative reports instead of traditional tabular data. We carried out an experiment on 300 surgical reports to determine the survival rates at one year and five years. Using a truncated TF-IDF vectorization of the texts and logistic regression, we could reach a macro Fl of 59.1 %, respectively, 54.9% with a five-fold cross validation. While the size of the corpus is relatively small, our experiments show that the operative textual sources can discriminate the transplantation outcomes and could be a valuable additional input to existing prediction systems. Clinical Relevance- Heart transplantation involves a significant number of written reports including in the preoperative examinations and operative documentation. In this paper, we show that these written reports can predict the outcome of the transplantation at one and five years with macro 1s of 59.1 % and 54.9 %, respectively and complement existing prediction methods.
30.	Köhler, Per, et al. (author) Flexible multi electrode brain-machine interface for recording in the cerebellum. 2009 In: IEEE Engineering in Medicine and Biology Society. Conference Proceedings. - 1557-170X. ; 1, s. 536-538 Journal article (peer-reviewed)abstract A new type of chip based microelectrode for acute electrophysiological recordings in the CNS has been developed. It's designed to be adaptable to a multitude of specific neuronal environments, in this study the cerebellar cortex of rat and cat. Photolithographically patternened SU-8 is used to yield flexible and biocompatible penetrating shanks with gold leads. Electrodes with an impedance of about 300 kOmega at 1kHz have excellent signal to noise ratio in acute recordings in cat cerebellum.
31.	Larsson, Linnéa, et al. (author) Discrimination of fixations and smooth pursuit movements in high-speed eye-tracking data 2014 In: [Host publication title missing]. - 1557-170X. ; , s. 3797-3800 Conference paper (peer-reviewed)
32.	Lawand, N.S., et al. (author) An improved system approach towards future cochlear implants 2013 In: Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS. - 1557-170X. ; , s. 5163-5166 Conference paper (peer-reviewed)abstract Cochlear implants (CIs) have been used for many years to restore hearing for deaf patients. Unfortunately, today's CIs are still bulky devices and uncomfortable to wear. In this paper we present three innovations that ultimately should pave the way to a fully implantable bionic ear. First a microfabrication process used to fabricate the polymer metal microelectrode array for auditory nerve stimulation is discussed. Subsequently, a compact biphasic programmable stimulator chip to be used along with this electrode array is presented. By using a double loop feedback circuit topology, the circuit provides a precise stimulation current while requiring only little voltage headroom. The resulting low power consumption and reduced chip area allow for integration of the electronic circuitry onto the electrode array. Finally, as reliability and data transmission rate are two of the most critical issues in CI devices, we propose a software method to improve both data rate and reliability of transmitting digital data from the external part of the CI to the internal part with negligible power consumption. © 2013 IEEE.
33.	Lendaro, Eva, 1989, et al. (author) Classification of non-weight bearing lower limb movements: Towards a potential treatment for phantom limb pain based on myoelectric pattern recognition 2016 In: Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS. - 1557-170X. ; 2016-October, s. 5457-5460 Conference paper (peer-reviewed)abstract Research in myoelectric pattern recognition (MPR) for the prediction of motor volition has primarily focused on the upper limbs. Recent studies in the lower limbs have mainly concentrated on prosthetic control, while MPR for lower limb rehabilitation purposes has received little attention. In this work we investigated the viability of a MPR system for the prediction of four degrees of freedom controlled in a near natural or physiologically appropriate fashion. We explored three different electrode configurations for acquiring electromyographic (EMG) signals: two targeted (bipolar and monopolar) and one untargeted (electrodes equally spaced axially). The targeted monopolar configuration yielded overall lower signal-to-noise ratios (SNR) but similar accuracy than those of the targeted bipolar configuration. The targeted bipolar and untargeted monopolar configurations were comparable in terms of SNR and offline accuracy when the same number of channels was used. However, the untargeted configuration tested with twice the channels yielded the best results in terms of accuracy. An advantage of the untargeted configuration is that it offers a simpler and more practical electrode placement. This work is the first step in our long-term goal of implementing a phantom limb pain (PLP) treatment for lower limb amputees based on MPR and augmented/virtual reality.
34.	Lendaro, Eva, 1989, et al. (author) Common Spatial Pattern EEG decomposition for Phantom Limb Pain detection 2021 In: Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS. - 1557-170X. ; , s. 726-729 Conference paper (peer-reviewed)abstract Phantom Limb Pain (PLP) is a chronic condition frequent among individuals with acquired amputation. PLP has been often investigated with the use of functional MRI focusing on the changes that take place in the sensorimotor cortex after amputation. In the present study, we investigated whether a different type of data, namely electroencephalographic (EEG) recordings, can be used to study the condition. We acquired resting state EEG data from people with and without PLP and then used machine learning for a binary classification task that differentiates the two. Common Spatial Pattern (CSP) decomposition was used as the feature extraction method and two validation schemes were followed for the classification task. Six classifiers (LDA, Log, QDA, LinearSVC, SVC and RF) were optimized through grid search and their performance compared. Two validation approaches, namely all-subjects validation and leave-one-out cross-validation (LOOCV), resulted in high classification accuracy. Most notably, the 93.7% accuracy achieved with SVC in LOOCV holds promise for good diagnostic capabilities using EEG biomarkers. In conclusion, our findings indicate that EEG data is a promising target for future research aiming at elucidating the neural mechanisms underlying PLP and its diagnosis.
35.	Lendaro, Eva, 1989, et al. (author) Differential Activation of Biceps Brachii Muscle Compartments for Human-Machine Interfacing 2018 In: Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS. - 1557-170X. ; 2018-July, s. 4705-4709 Conference paper (peer-reviewed)abstract A central challenge for myoelectric limb prostheses resides in the fact that, as the level of amputation becomes more proximal, the number of functions to be replaced increases, while the number of muscles available to collect input signals for control decreases. Differential activation of compartments from a single muscle could provide additional control sites. However, such feat is not naturally under voluntary control. In this study, we investigated the feasibility of learning to differentially activate the two heads of the bicep brachii muscle (BBM), by using biofeedback via high-density surface electromyography (HD-sEMG). Using a one degree of freedom Fitts' law test, we observed that eight subjects could learn to control the center of gravity of BBM's myoelectric activity. In addition, we examined the activations patterns of BBM that allow for the decoding of distal hand movements. These patterns were found highly individual, but different enough to allow for decoding of motor volition of distal joints. These findings represent promising venues to increase the functionality of myoelectrically controlled upper limb prostheses.
36.	Lendaro, Eva, 1989, et al. (author) Seamless Integrated Textrode-Band for Real-time Lower Limb Movements Classification to Facilitate Self-Administrated Phantom Limb Pain Treatment 2019 In: Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS. - 1557-170X. ; :July, s. 1753-1756 Conference paper (peer-reviewed)abstract Phantom Motor Execution (PME) is a mechanism-based approach for the treatment of Phantom Limb Pain (PLP), which could potentially be self-administered in the home environment. However, the placement of electrodes aimed to acquire myoelectric signals from the residual stump muscles can be regarded as a difficult and time-consuming process by the patient. Thus, to increase patient compliance, the process must be made easier, faster, and cost effective. In this study, we developed and investigated a seamless integrated textrode-band for myoelectric recordings. The textrode-band can be easily donned/doffed, is reusable and washable. We demonstrated the viability of such concept by analyzing the signal-to-noise ratio (SNR), as well as offline and real time motion decoding performance, that in our experience are compatible with the PME treatment.
37.	Lund, Morten E., et al. (author) Inductive tongue control of powered wheelchairs 2010 In: International Conference of the IEEE Engineering in Medicine and Biology Society. - 1557-170X. - 9781424441235 ; , s. 3361-3364 Conference paper (peer-reviewed)abstract Alternative and effective methods for controlling powered wheelchairs are important to individuals with tetraplegia and similar impairments whom are unable to use the standard joystick. This paper describes a system where tongue movements are used to control a powered wheelchair thus providing users, with high level spinal cord injuries, full control of their wheelchair. The system is based on an inductive tongue control system developed at Center for Sensory-Motor Interaction (SMI), Aalborg University. The system emulates a standard analog joystick in order to interface the wheelchair, thus ensuring that the system works with almost any wheelchair. The total embedment of the tongue interface into the mouth makes the control practically invisible. A fuzzy system combining 8 sensors for directional control allows for multidirectional control of the wheelchair. Preliminary test results show navigation abilities, which are highly competitive when compared to other tongue control system.
38.	Löfgren, N., et al. (author) On evaluation of spectrum estimators for EEG 2004 In: Proceedings Of The 26th Annual International Conference Of The IEEE Engineering In Medicine And Biology Society. - : IEEE. - 0780384393 ; 1, s. 305-9 Conference paper (peer-reviewed)abstract In the search for how neonatal EEG is affected by asphyxia it is of importance to find reliable estimates of EEG power spectra. Several spectral estimation methods do exist, but since the true spectra are unknown it is hard to tell how well the estimators perform. Therefore a model to generate simulated EEG with known spectrum is proposed and the model is used to evaluate performance of several parametric and Fourier based spectral estimators.
39.	Löfhede, Johan, et al. (author) Comparing a Supervised and an Unsupervised Classification Method for Burst Detection in Neonatal EEG 2008 In: Proceedings of Engineering in Medicine and Biology Society, EMBS 2008. 30th Annual International Conference of the IEEE, 20-24 August, 2008. - : IEEE. - 1557-170X. - 9781424418145 ; , s. 3836-3839 Conference paper (peer-reviewed)abstract Hidden Markov Models (HMM) and Support Vector Machines (SVM) using unsupervised and supervised training, respectively, were compared with respect to their ability to correctly classify burst and suppression in neonatal EEG. Each classifier was fed five feature signals extracted from EEG signals from six full term infants who had suffered from perinatal asphyxia. Visual inspection of the EEG by an experienced electroencephalographer was used as the gold standard when training the SVM, and for evaluating the performance of both methods. The results are presented as receiver operating characteristic (ROC) curves and quantified by the area under the curve (AUC). Our study show that the SVM and the HMM exhibit similar performance, despite their fundamental differences.
40.	Löfhede, Johan, 1978, et al. (author) Comparison of Three Methods for Classifying Burst and Suppression in the EEG of Post Asphyctic Newborns 2007 In: Engineering in Medicine and Biology Society, 2007. EMBS 2007. 29th Annual International Conference of the IEEE. - : IEEE. - 1557-170X. - 9781424407880 - 9781424407873 ; , s. 5136-5139 Conference paper (peer-reviewed)abstract Fisher's linear discriminant, a feed-forward neural network (NN) and a support vector machine (SVM) are compared with respect to their ability to distinguish bursts from suppression in burst-suppression electroencephalogram (EEG) signals using five features inherent in the EEG as input. The study is based on EEG signals from six full term infants who have suffered from perinatal asphyxia, and the methods have been trained with reference data classified by an experienced electroencephalographer. The results are summarized as area under the curve (AUC) values derived from receiver operating characteristic (ROC) curves for the three methods, and show that the SVM is slightly better than the others, at the cost of a higher computational complexity.
41.	Löfhede, Johan, 1978, et al. (author) Detection of bursts in the EEG of post asphyctic newborns 2006 In: 2006 28th Annual International Conference of the IEEE Engineering in Medicine and Biology Society. - 1557-170X. - 9781424400324 ; , s. 2179-2182, s. 5-6 Conference paper (peer-reviewed)abstract Eight features inherent in the electroencephalogram (EEG) have been extracted and evaluated with respect to their ability to distinguish bursts from suppression in burst-suppression EEG. The study is based on EEG from six full term infants who had suffered from lack of oxygen during birth. The features were used as input in a neural network, which was trained on reference data segmented by an experienced electroencephalographer. The performance was then evaluated on validation data for each feature separately and in combinations. The results show that there are significant variations in the type of activity found in burst-suppression EEG from different subjects, and that while one or a few features seem to be sufficient for most patients in this group, some cases require specific combinations of features for good detection to be possible.
42.	Martinez, J P, et al. (author) Accuracy of QT Measurement in the EASI-derived 12-lead ECG 2006 In: Conference proceedings (IEEE Engineering in Medicine and Biology Society. Conf.). - 1557-170X. ; 1, s. 3986-3989 Conference paper (peer-reviewed)abstract The purpose of this study is to assess QT interval measurements from the EASI 12-lead ECG as compared to the standard 12-lead ECG. The QT interval was automatically measured in simultaneously recorded standard and EASI 12- lead ECGs, using a validated wavelet-based delineator. The agreement between the two sets of measurements was quantified both on a lead-by-lead basis and a multilead basis. The results show an acceptable agreement between QT measurements in the two lead systems, with correlation coefficients (CC) 0.91-0.98 depending on the lead. Standard deviations range from 9.2 ms to 26.4 ms depending on the selected lead. In a few patients large inter-system differences were found, mainly due to different T wave morphologies. Using a multilead delineation, QT intervals were considerably more stable than single-lead measurements and resulted in a much better agreement between the two lead systems (CC: 0.98, QT difference: 1.1 ms ± 9.8 ms). Thus, EASI-derived 12- lead ECG may be used for reliable QT monitoring when the multilead delineation approach is adopted.
43.	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.
44.	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.
45.	Medved, Dennis, et al. (author) Predicting the Outcome for Patients in a Heart Transplantation Queue using Deep Learning 2017 In: 2017 39th Annual International Conference of the IEEE Engineering in Medicine and Biology Society : Smarter Technology for a Healthier World, EMBC 2017 - Proceedings - Smarter Technology for a Healthier World, EMBC 2017 - Proceedings. - 1557-170X. - 9781509028092 ; , s. 74-77 Conference paper (peer-reviewed)abstract Heart transplantations have made it possible to extend the median survival time to 12 years for patients with end-stage heart diseases. This operation is unfortunately limited by the availability of donor organs and patients have to wait on average about 200 days in a waiting list before being operated. This waiting time varies considerably across the patients. In this paper, we studied the outcome for patients entering a transplantation waiting list using deep learning techniques. We implemented a model in the form of two-layer neural networks and we predicted the outcome as still waiting, transplanted or dead in the waiting list, at three different time points: 180 days, 365 days, and 730 days. As data source, we used the United Network for Organ Sharing (UNOS) registry, where we extracted adult patients (>17 years) from January 2000 to December 2011. We trained our model using the Keras framework, and we report F1 macro scores of respectively 0.674, 0.680, and 0.680 compared to a baseline of 0.271. We also applied a backward elimination procedure, using our neural network, to extract the 10 most significant parameters predicting the patient status for the three different time points.
46.	Medved, Dennis, et al. (author) Selection of an optimal feature set to predict heart transplantation outcomes 2016 In: 2016 38th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2016. - 1557-170X. - 9781457702204 ; 2016-October, s. 3290-3293 Conference paper (peer-reviewed)abstract Heart transplantation (HT) is a life saving procedure, but a limited donor supply forces the surgeons to prioritize the recipients. The understanding of factors that predict mortality could help the doctors with this task. The objective of this study is to find locally optimal feature sets to predict survival of HT patients for different time periods. To this end, we applied logistic regression together with a greedy forward and backward search. As data source, we used the United Network for Organ Sharing (UNOS) registry, where we extracted adult patients (>17 years) from January 1997 to December 2008. As methods to predict survival, we used the Index for Mortality Prediction After Cardiac Transplantation (IMPACT) and the International Heart Transplant Survival Algorithm (IHTSA). We used the LIBLINEAR library together with the Apache Spark cluster computing framework to carry out the computation and we found feature sets for 1, 5, and 10 year survival for which we obtained area under the ROC curves (AUROC) of 68%, 68%, and 76%, respectively.
47.	Moshavegh, Ramin, et al. (author) Automated segmentation of free-lying cell nuclei in Pap smears for malignancy-associated change analysis 2012 In: Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS. - 1557-170X. - 9781424441198 ; , s. 5372-5375 Conference paper (peer-reviewed)abstract This paper presents an automated algorithm for robustly detecting and segmenting free-lying cell nuclei in bright-field microscope images of Pap smears. This is an essential initial step in the development of an automated screening system for cervical cancer based on malignancy associated change (MAC) analysis. The proposed segmentation algorithm makes use of gray-scale annular closings to identify free-lying nuclei-like objects together with marker-based watershed segmentation to accurately delineate the nuclear boundaries. The algorithm also employs artifact rejection based on size, shape, and granularity to ensure only the nuclei of intermediate squamous epithelial cells are retained. An evaluation of the performance of the algorithm relative to expert manual segmentation of 33 fields-of-view from 11 Pap smear slides is also presented. The results show that the sensitivity and specificity of nucleus detection is 94.71% and 85.30% respectively, and that the accuracy of segmentation, measured using the Dice coefficient, of the detected nuclei is 97.30±1.3%.
48.	Munguia Mena, Marco, et al. (author) Characterisation of Arteriovenous Fistula’s sound recordings using principal component analysis 2009 In: [Host publication title missing]. - 1557-170X. ; , s. 5661-5664 Conference paper (peer-reviewed)abstract In this study, a signal analysis framework based on the Karhunen-Loève expansion and k-means clustering algorithm is proposed for the characterisation of arteriovenous (AV) fistula’s sound recordings. The Karhunen-Loève (KL) coefficients corresponding to the directions of maximum variance were used as classification features, which were clustered applying k-means algorithm. The results showed that one natural cluster was found for similar AV fistula’s state recordings. On the other hand, when stenotic and non-stenotic AV fistula’s recordings were processed together, the two most significant KL coefficients contain important information that can be used for classification or discrimination between these AV fistula’s states.
49.	Musolf, Brett M., et al. (author) Analysis and Design of a Bypass Socket for Transradial Amputations 2021 In: Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS. - 1557-170X. ; , s. 4611-4614 Conference paper (peer-reviewed)abstract The ability to measure functional performance of a prosthesis is hindered by the lack of an equalized mechanical platform to test from. Researchers and designers seeking to increase the pace of development have attempted novel mounts for prostheses so these can be used by able-bodied participants. Termed bypass sockets, these can increase the sampling pool during prosthetic evaluations. Here, we present an open-source, 3D printable prosthetic bypass socket for below-elbow (transradial) amputations. Methods to quantify the effectiveness of bypass sockets are limited and therefore we propose the use of a validated and clinically relevant evaluation tool, the Assessment of Capacity for Myoelectric Control (ACMC). We performed the ACMC in six able-bodied subjects with limited experience with myoelectric prostheses and found the participants to be rated from non- to somewhat capable using the ACMC interpretation scale. In addition, we conducted a secondary evaluation consisting of a subset of tasks of the Cybathlon competition aimed at eliciting fatigue in the participants. All participants completed said tasks, suggesting that the bypass socket is suitable for extended use during prosthesis development.Clinical Relevance - The design and validation of the bypass socket presented here can facilitate the development of upper limb prosthetic systems.
50.	Nissila, I, et al. (author) Auditory hemodynamic studies of newborn infants using near-infrared spectroscopic imaging 2004 In: IEEE Engineering in Medicine and Biology Society. Conference Proceedings. - 1557-170X. ; 2, s. 1244-1274 Journal article (peer-reviewed)abstract The noninvasive study of tissue blood volume and oxygenation using near-infrared light is a new and actively developing technology. We have used near-infrared spectroscopic imaging (NIRSI) to study hemodynamic responses on the auditory cortices evoked by auditory stimulation. Ten healthy newborn infants were studied. The otoacoustic emission hearing test was performed for each infant. Pulse oximetry was used to monitor the heart rate during the measurement, video recording was used to monitor motion artifacts, and the eye movements were noted in order to determine sleep stage. A 16-channel frequency-domain optical imaging system developed in our laboratory was used for NIRSI measurements. The stimuli were presented in trains of seven 1 kHz beeps with 700-ms inter-stimulus intervals. The stimulus trains were separated by 25-s silent periods in order to allow for the hemodynamic delay. In 3/8 cases, we obtained a clear bilateral increase in [HbO/sub 2/], and in two additional cases, a clear response on one hemisphere. The mean change in [HbO/sub 2/] was +0.9+/-0.9muM and the mean change in [Hb] was -0.3+/-0.4muM for those channels producing the largest response for each subject. No statistically significant response was found in 3/8 cases.

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