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https://www.readbyqxmd.com/read/28720739/-disorder-of-gastric-myoelectric-activity-in-patients-with-cerebral-infarction-electrogastrographic-assessment
#1
Fumihiko Kinekawa, Noboru Sasaoka, Kazuya Matsuda, Yuko Kita, Ryoichi Okura, Ryota Nakabayashi, Akiko Ohara, Katsuyuki Nakao, Toshihiko Inoue, Michiaki Tokuda, Yohei Kokudo, Tsutomu Masaki
In this study, gastric myoelectric activity in patients with acute cerebral infarction was investigated using electrogastrography. The patients were divided into four groups; those with mild brainstem infarction(group A, n=13, men:8, women:5, 75±2 years old), severe brainstem infarction(group B, n=6, men:4, women:2, 79±4 years old), mild non-brainstem infarction(group C, n=14, men:7, women:7, 76±3 years old), and severe non-brainstem infarction(group D, n=9, men:3, women:6, 87±2 years old). In group B, the% ratio of normogastria(2...
July 2017: No Shinkei Geka. Neurological Surgery
https://www.readbyqxmd.com/read/28713810/a-biomechanical-comparison-of-proportional-electromyography-control-to-biological-torque-control-using-a-powered-hip-exoskeleton
#2
Aaron J Young, Hannah Gannon, Daniel P Ferris
BACKGROUND: Despite a large increase in robotic exoskeleton research, there are few studies that have examined human performance with different control strategies on the same exoskeleton device. Direct comparison studies are needed to determine how users respond to different types of control. The purpose of this study was to compare user performance using a robotic hip exoskeleton with two different controllers: a controller that targeted a biological hip torque profile and a proportional myoelectric controller...
2017: Frontiers in Bioengineering and Biotechnology
https://www.readbyqxmd.com/read/28704209/robotic-hand-assisted-training-for-spinal-cord-injury-driven-by-myoelectric-pattern-recognition-a-case-report
#3
Zhiyuan Lu, Kai-Yu Tong, Henry Shin, Argyrios Stampas, Ping Zhou
A 51-year-old man with an incomplete C6 spinal cord injury sustained 26 yrs ago attended twenty 2-hr visits over 10 wks for robot-assisted hand training driven by myoelectric pattern recognition. In each visit, his right hand was assisted to perform motions by an exoskeleton robot, while the robot was triggered by his own motion intentions. The hand robot was designed for this study, which can perform six kinds of motions, including hand closing/opening; thumb, index finger, and middle finger closing/opening; and middle, ring, and little fingers closing/opening...
July 12, 2017: American Journal of Physical Medicine & Rehabilitation
https://www.readbyqxmd.com/read/28698474/a-novel-spatial-feature-for-the-identification-of-motor-tasks-using-high-density-electromyography
#4
Mislav Jordanić, Mónica Rojas-Martínez, Miguel Angel Mañanas, Joan Francesc Alonso, Hamid Reza Marateb
Estimation of neuromuscular intention using electromyography (EMG) and pattern recognition is still an open problem. One of the reasons is that the pattern-recognition approach is greatly influenced by temporal changes in electromyograms caused by the variations in the conductivity of the skin and/or electrodes, or physiological changes such as muscle fatigue. This paper proposes novel features for task identification extracted from the high-density electromyographic signal (HD-EMG) by applying the mean shift channel selection algorithm evaluated using a simple and fast classifier-linear discriminant analysis...
July 8, 2017: Sensors
https://www.readbyqxmd.com/read/28697795/improved-prosthetic-hand-control-with-concurrent-use-of-myoelectric-and-inertial-measurements
#5
Agamemnon Krasoulis, Iris Kyranou, Mustapha Suphi Erden, Kianoush Nazarpour, Sethu Vijayakumar
BACKGROUND: Myoelectric pattern recognition systems can decode movement intention to drive upper-limb prostheses. Despite recent advances in academic research, the commercial adoption of such systems remains low. This limitation is mainly due to the lack of classification robustness and a simultaneous requirement for a large number of electromyogram (EMG) electrodes. We propose to address these two issues by using a multi-modal approach which combines surface electromyography (sEMG) with inertial measurements (IMs) and an appropriate training data collection paradigm...
July 11, 2017: Journal of Neuroengineering and Rehabilitation
https://www.readbyqxmd.com/read/28693533/classification-complexity-in-myoelectric-pattern-recognition
#6
Niclas Nilsson, Bo Håkansson, Max Ortiz-Catalan
BACKGROUND: Limb prosthetics, exoskeletons, and neurorehabilitation devices can be intuitively controlled using myoelectric pattern recognition (MPR) to decode the subject's intended movement. In conventional MPR, descriptive electromyography (EMG) features representing the intended movement are fed into a classification algorithm. The separability of the different movements in the feature space significantly affects the classification complexity. Classification complexity estimating algorithms (CCEAs) were studied in this work in order to improve feature selection, predict MPR performance, and inform on faulty data acquisition...
July 10, 2017: Journal of Neuroengineering and Rehabilitation
https://www.readbyqxmd.com/read/28692959/dedicated-entropy-measures-for-early-assessment-of-pregnancy-progression-from-single-channel-electrohysterography
#7
Massimo Mischi, Chuan Chen, Tanya Ignatenko, Hinke de Lau, Beijing Ding, Guid S Oei, Chiara Rabotti
OBJECTIVE: Preterm birth is a large-scale clinical problem involving over 10% infants. Diagnostic means for timely risk assessment are lacking and the underlying physiological mechanisms unclear. To improve the evaluation of pregnancy before term, we introduce dedicated entropy measures derived from a single-channel electrohysterogram (EHG). METHODS: The estimation of Approximate Entropy (ApEn) and Sample Entropy (SampEn) is adjusted to monitor variations in the regularity of single-channel EHG recordings, reflecting myoelectrical changes due to pregnancy progression...
July 10, 2017: IEEE Transactions on Bio-medical Engineering
https://www.readbyqxmd.com/read/28691694/context-dependent-adaptation-improves-robustness-of-myoelectric-control-for-upper-limb-prostheses
#8
Gauravkumar K Patel, Janne Mathias Hahne, Claudio Castellini, Dario Farina, Strahinja Dosen
OBJECTIVE: Dexterous upper-limb prostheses are available today to restore grasping, but an effective and reliable feed-forward control is still missing. The aim of this work was to improve the robustness and reliability of myoelectric control by using context information from sensors embedded within the prosthesis. APPROACH: We developed a context-driven myoelectric control scheme (cxMYO) that incorporates the inference of context information from proprioception (inertial measurement unit) and exteroception (force and grip aperture) sensors to modulate the outputs of myoelectric control...
July 10, 2017: Journal of Neural Engineering
https://www.readbyqxmd.com/read/28688293/a-new-parameter-for-quantifying-the-variability-of-surface-electromyographic-signals-during-gait-the-occurrence-frequency
#9
Francesco Di Nardo, Alessandro Mengarelli, Annachiara Strazza, Valentina Agostini, Marco Knaflitz, Laura Burattini, Sandro Fioretti
Natural variability of myoelectric activity during walking was recently analyzed considering hundreds of strides. This allowed assessing a parameter seldom considered in classic surface EMG (sEMG) studies: the occurrence frequency, defined as the frequency each muscle activation occurs with, quantified by the number of strides when a muscle is recruited with that specific activation modality. Aim of present study was to propose the occurrence frequency as a new parameter for assessing sEMG-signal variability during walking...
June 30, 2017: Journal of Electromyography and Kinesiology
https://www.readbyqxmd.com/read/28684214/skill-assessment-in-upper-limb-myoelectric-prosthesis-users-validation-of-a-clinically-feasible-method-for-characterising-upper-limb-temporal-and-amplitude-variability-during-the-performance-of-functional-tasks
#10
Sibylle B Thies, Laurence Pj Kenney, Mohammad Sobuh, Adam Galpin, Peter Kyberd, Rebecca Stine, Matthew J Major
Upper limb myoelectric prostheses remain challenging to use and are often abandoned. A proficient user must be able to plan/execute arm movements while activating the residual muscle(s), accounting for delays and unpredictability in prosthesis response. There is no validated, low cost measure of skill in performing such actions. Trial-trial variability of joint angle trajectories measured during functional task performance, linearly normalised by time, shows promise. However, linear normalisation of time introduces errors, and expensive camera systems are required for joint angle measurements...
July 3, 2017: Medical Engineering & Physics
https://www.readbyqxmd.com/read/28676749/preliminary-evidence-for-training-induced-changes-of-morphology-and-phantom-limb-pain
#11
Sandra Preißler, Désirée Thielemann, Caroline Dietrich, Gunther O Hofmann, Wolfgang H R Miltner, Thomas Weiss
The aim of this study was to investigate whether a special prosthetic training in phantom limb pain patients aimed at increasing the functional use of the prosthesis leads to neural morphological plasticity of brain structures and a reduction in phantom limb pain. For chronic pain disorders, it was shown that morphological alterations due to pain might become at least partially reversed by pain therapies. Phantom limb pain is a chronic pain disorder that is frequently followed by neural plasticity of anatomical brain structures...
2017: Frontiers in Human Neuroscience
https://www.readbyqxmd.com/read/28667260/user-adaptation-in-myoelectric-man-machine-interfaces
#12
Janne M Hahne, Marko Markovic, Dario Farina
State of the art clinical hand prostheses are controlled in a simple and limited way that allows the activation of one function at a time. More advanced laboratory approaches, based on machine learning, offer a significant increase in functionality, but their clinical impact is limited, mainly due to lack of reliability. In this study, we analyse two conceptually different machine learning approaches, focusing on their robustness and performance in a closed loop application. A classification (finite number of classes) and a regression (continuous mapping) based projection of EMG into external commands were applied while artificially introducing non-stationarities in the EMG signals...
June 30, 2017: Scientific Reports
https://www.readbyqxmd.com/read/28659825/brain-activation-by-h1-antihistamines-challenges-conventional-view-of-their-mechanism-of-action-in-motion-sickness-a-behavioral-c-fos-and-physiological-study-in-suncus-murinus-house-musk-shrew
#13
Longlong Tu, Zengbing Lu, Karolina Dieser, Christina Schmitt, Sze Wa Chan, Man P Ngan, Paul L R Andrews, Eugene Nalivaiko, John A Rudd
Motion sickness occurs under a variety of circumstances and is common in the general population. It is usually associated with changes in gastric motility, and hypothermia, which are argued to be surrogate markers for nausea; there are also reports that respiratory function is affected. As laboratory rodents are incapable of vomiting, Suncus murinus was used to model motion sickness and to investigate changes in gastric myoelectric activity (GMA) and temperature homeostasis using radiotelemetry, whilst also simultaneously investigating changes in respiratory function using whole body plethysmography...
2017: Frontiers in Physiology
https://www.readbyqxmd.com/read/28650804/limb-position-tolerant-pattern-recognition-for-myoelectric-prosthesis-control-with-adaptive-sparse-representations-from-extreme-learning
#14
Joseph L Betthauser, Christopher L Hunt, Luke E Osborn, Matthew R Masters, Gyorgy Levay, Rahul Reddy Kaliki, Nitish V Thakor
Myoelectric signals can be used to predict the intended movements of an amputee for prosthesis control. However, untrained effects like limb position changes influence myoelectric signal characteristics, hindering the ability of pattern recognition algorithms to discriminate among motion classes. Despite frequent and long training sessions, these deleterious conditional influences may result in poor performance and device abandonment. GOAL: We present a robust sparsity-based adaptive classification method that is significantly less sensitive to signal deviations resulting from untrained conditions...
June 23, 2017: IEEE Transactions on Bio-medical Engineering
https://www.readbyqxmd.com/read/28650213/visualisation-of-upper-limb-activity-using-spirals-a-new-approach-to-the-assessment-of-daily-prosthesis-usage
#15
Alix Chadwell, Laurence Kenney, Malcolm Granat, Sibylle Thies, John S Head, Adam Galpin
BACKGROUND: Current outcome measures used in upper limb myoelectric prosthesis studies include clinical tests of function and self-report questionnaires on real-world prosthesis use. Research in other cohorts has questioned both the validity of self-report as an activity assessment tool and the relationship between clinical functionality and real-world upper limb activity. Previously,(1) we reported the first results of monitoring upper limb prosthesis use. However, the data visualisation technique used was limited in scope...
June 1, 2017: Prosthetics and Orthotics International
https://www.readbyqxmd.com/read/28639478/relation-between-capacity-and-performance-in-paediatric-upper-limb-prosthesis-users
#16
Helen Lindner, Ayako Hiyoshi, Liselotte Hermansson
BACKGROUND: The International Classification of functioning, disability and health refers capacity to what an individual can do in a standardised environment and describes performance as what an individual really does and whether the individual encounters any difficulty in the real-life environment. Measures of capacity and performance can help to determine if there is any gap between them that may restrict participation. The aim of this study was to explore the relationship between capacity scores obtained in a standardised clinical setting and proportional ease of performance obtained from a real-life environment...
June 1, 2017: Prosthetics and Orthotics International
https://www.readbyqxmd.com/read/28637983/repeatability-of-measurements-of-surface-electromyographic-variables-during-maximum-voluntary-contraction-of-temporalis-and-masseter-muscles-in-normal-adults
#17
Yeong-Gwan Im, Sang-Ho Han, Ji-Il Park, Hae-Soon Lim, Byung-Gook Kim, Jae-Hyung Kim
This study evaluated the intraexaminer repeatability of measurements of surface electromyography (EMG) variables and functional indices of the myoelectric signals from the masseter and temporalis muscles bilaterally in 15 healthy men. The test was repeated on two different days without templates. The resting muscle activity was recorded once, and two kinds of maximum voluntary contraction (MVC) tasks were performed and recorded three times. The two MVC tasks involved clenching the teeth and biting down on two cotton rolls bilaterally with the posterior teeth...
2017: Journal of Oral Science
https://www.readbyqxmd.com/read/28628379/visuomotor-behaviors-and-performance-in-a-dual-task-paradigm-with-and-without-vibrotactile-feedback-when-using-a-myoelectric-controlled-hand
#18
Eitan Raveh, Jason Friedman, Sigal Portnoy
Prosthesis users allocate visual attention to their prosthetic hand while performing activities of daily living (ADLs), due to absence of sensory feedback. Dual-task assignments present competition for visual attention and may affect the performance of ADLs. Vibrotactile feedback (VTF) is a frequently-used method to provide prosthesis users with tactile feedback. However, the effect of adding VTF on visual attention and performance in a motor dual-task paradigm has not been investigated. Our aim was to compare visual attention and performance during ADLs in a motor dual-task paradigm when using binary VTF and without using VTF...
June 19, 2017: Assistive Technology: the Official Journal of RESNA
https://www.readbyqxmd.com/read/28608824/a-novel-unsupervised-adaptive-learning-method-for-long-term-electromyography-emg-pattern-recognition
#19
Qi Huang, Dapeng Yang, Li Jiang, Huajie Zhang, Hong Liu, Kiyoshi Kotani
Performance degradation will be caused by a variety of interfering factors for pattern recognition-based myoelectric control methods in the long term. This paper proposes an adaptive learning method with low computational cost to mitigate the effect in unsupervised adaptive learning scenarios. We presents a particle adaptive classifier (PAC), by constructing a particle adaptive learning strategy and universal incremental least square support vector classifier (LS-SVC). We compared PAC performance with incremental support vector classifier (ISVC) and non-adapting SVC (NSVC) in a long-term pattern recognition task in both unsupervised and supervised adaptive learning scenarios...
June 13, 2017: Sensors
https://www.readbyqxmd.com/read/28607219/transcranial-direct-current-stimulation-versus-user-training-on-improving-online-myoelectric-control-for-amputees
#20
Lizhi Pan, Dingguo Zhang, Ning Jiang, Xinjun Sheng, Xiangyang Zhu
OBJECTIVE: Transcranial direct current stimulation (tDCS) and user training (UT) are two types of methods to improve myoelectric control performance for amputees. In this study, we compared the independent effect between tDCS and UT, and investigated the combined effect of tDCS and UT. APPROACH: An online paradigm of simultaneous and proportional control (SPC) based on electromyography (EMG) was adopted. The proposed experiments were conducted on six naïve unilateral trans-radial amputees...
June 13, 2017: Journal of Neural Engineering
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