{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,20]],"date-time":"2026-10-20T01:06:45Z","timestamp":1792458405160,"version":"4.5.0"},"reference-count":76,"publisher":"IOP Publishing","issue":"1","license":[{"start":{"date-parts":[[2024,6,26]],"date-time":"2024-06-26T00:00:00Z","timestamp":1719360000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/publishingsupport.iopscience.iop.org\/iop-standard\/v1"},{"start":{"date-parts":[[2024,6,26]],"date-time":"2024-06-26T00:00:00Z","timestamp":1719360000000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/iopscience.iop.org\/info\/page\/text-and-data-mining"}],"content-domain":{"domain":["iopscience.iop.org"],"crossmark-restriction":false},"short-container-title":["Med. Eng. Phys."],"published-print":{"date-parts":[[2024,8,1]]},"DOI":"10.1016\/j.medengphy.2024.104198","type":"journal-article","created":{"date-parts":[[2024,6,26]],"date-time":"2024-06-26T03:00:02Z","timestamp":1719370802000},"page":"104198","update-policy":"https:\/\/doi.org\/10.1088\/crossmark-policy","source":"Crossref","is-referenced-by-count":4,"title":["Feature evaluation for myoelectric pattern recognition of multiple nearby reaching targets"],"prefix":"10.1088","volume":"130","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-6864-4756","authenticated-orcid":true,"given":"Fatemeh","family":"Davarinia","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-2405-4164","authenticated-orcid":true,"given":"Ali","family":"Maleki","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"266","published-online":{"date-parts":[[2024,6,26]]},"reference":[{"key":"bib0001","first-page":"1070","type":"other","article-title":"Extracting simultaneous and proportional neural control information for multiple-DOF prostheses from the surface electromyographic signal","volume":"56","author":"Jiang","year":"2009"},{"key":"bib0002","first-page":"541","type":"other","article-title":"Myoelectric signal processing for control of powered limb prostheses","volume":"16","author":"Parker","year":"2006"},{"key":"bib0003","first-page":"3169","author":"Ruhunage","year":"2017","type":"other"},{"key":"bib0004","first-page":"325","type":"other","article-title":"Customized interactive robotic treatment for stroke: eMG-triggered therapy","volume":"13","author":"Dipietro","year":"2005"},{"key":"bib0005","doi-asserted-by":"crossref","DOI":"10.1155\/2017\/3908135","type":"other","article-title":"Hand rehabilitation robotics on poststroke motor recovery","author":"Yue","year":"2017"},{"key":"bib0006","first-page":"1064","type":"other","article-title":"An EMG-based control for an upper-limb power-assist exoskeleton robot","volume":"42","author":"Kiguchi","year":"2012"},{"key":"bib0007","first-page":"448","type":"other","article-title":"An investigation into time domain features of surface electromyography to estimate the elbow joint angle","volume":"15","author":"Triwiyanto","year":"2017"},{"key":"bib0008","first-page":"284","type":"other","article-title":"Muscle fatigue compensation of the electromyography signal for elbow joint angle estimation using adaptive feature","volume":"71","author":"Triwiyanto","year":"2018"},{"key":"bib0009","first-page":"243","type":"other","article-title":"Towards an SEMG-based tele-operated robot for masticatory rehabilitation","volume":"75","author":"Kalani","year":"2016"},{"key":"bib0010","first-page":"1613","type":"other","article-title":"Current trends and confounding factors in myoelectric control: limb position and contraction intensity","volume":"20","author":"Campbell","year":"2020"},{"key":"bib0011","doi-asserted-by":"crossref","DOI":"10.1016\/j.knosys.2021.107165","type":"other","article-title":"Metric learning for novel motion rejection in high-density myoelectric pattern recognition","author":"Wu","year":"2021"},{"key":"bib0012","first-page":"1071","type":"other","article-title":"Adaptive hybrid classifier for myoelectric pattern recognition against the interferences of outlier motion, muscle fatigue, and electrode doffing","volume":"27","author":"Ding","year":"2019"},{"key":"bib0013","type":"other","article-title":"The role of muscle synergies in myoelectric control: trends and challenges for simultaneous multifunction control","volume":"11","author":"Ison","year":"2014"},{"key":"bib0014","first-page":"4832","type":"other","article-title":"EMG feature evaluation for improving myoelectric pattern recognition robustness","volume":"40","author":"Phinyomark","year":"2013"},{"key":"bib0015","first-page":"157","type":"other","article-title":"Evaluating convolutional neural networks as a method of EEG\u2013EMG fusion","author":"Tryon","year":"2021"},{"key":"bib0016","first-page":"5012","type":"other","article-title":"Classification of task weight during dynamic motion using EEG\u2013EMG fusion","volume":"21","author":"Tryon","year":"2020"},{"key":"bib0017","type":"other","article-title":"A novel attention-based hybrid CNN-RNN architecture for sEMG-based gesture recognition","volume":"13","author":"Hu","year":"2018"},{"key":"bib0018","first-page":"6824","type":"other","article-title":"Two-Step biometrics using electromyogram signal based on convolutional neural network-long short-term memory networks","volume":"11","author":"Kim","year":"2021"},{"key":"bib0019","first-page":"2650","type":"other","article-title":"Toward deep generalization of peripheral emg-based human-robot interfacing: a hybrid explainable solution for neurorobotic systems","volume":"6","author":"Gulati","year":"2021"},{"key":"bib0020","first-page":"E272","type":"other","article-title":"Sensor fusion for myoelectric control based on deep learning with recurrent convolutional neural networks","volume":"42","author":"Wang","year":"2018"},{"key":"bib0021","first-page":"45","type":"other","article-title":"EMG-based online classification of gestures with recurrent neural networks","volume":"128","author":"Sim\u00e3o","year":"2019"},{"key":"bib0022","first-page":"1","type":"other","article-title":"Efficient deep neural network model for classification of grasp types using sEMG signals","author":"Coskun","year":"2021"},{"key":"bib0023","type":"other"},{"key":"bib0024","first-page":"8733","type":"other","article-title":"Supervised myoelectrical hand gesture recognition in post-acute stroke patients with upper limb paresis on affected and non-affected sides","volume":"22","author":"Anastasiev","year":"2022"},{"key":"bib0025","type":"other","article-title":"SSVEP-gated EMG-based decoding of elbow angle during goal-directed reaching movement","volume":"71","author":"Davarinia","year":"2022"},{"key":"bib0026","first-page":"512","type":"other","article-title":"Deep learning for EMG-based human-machine interaction: a review","volume":"8","author":"Xiong","year":"2021"},{"key":"bib0027","first-page":"88","type":"other","article-title":"A deep Kalman filter network for hand kinematics estimation using sEMG","volume":"143","author":"Bao","year":"2021"},{"key":"bib0028","first-page":"0460d3","type":"other","article-title":"MuscleNET: mapping electromyography to kinematic and dynamic biomechanical variables by machine learning","volume":"18","author":"Nasr","year":"2021"},{"key":"bib0029","article-title":"Comparing the efficiency of artificial neural networks in sEMG-based simultaneous and continuous estimation of hand kinematics","author":"Batayneh","year":"2021","type":"other"},{"key":"bib0030","first-page":"17986","type":"other","article-title":"Continuous estimation of human upper limb joint angles by using PSO-LSTM model","volume":"9","author":"Tang","year":"2020"},{"key":"bib0031","type":"other","article-title":"Continuous estimation of upper limb joint angle from sEMG signals based on SCA-LSTM deep learning approach","volume":"61","author":"Ma","year":"2020"},{"key":"bib0032","first-page":"3192","type":"other","article-title":"Deep learning movement intent decoders trained with dataset aggregation for prosthetic limb control","volume":"66","author":"Dantas","year":"2019"},{"key":"bib0033","first-page":"103","type":"other","article-title":"Multi\u2013joint angles estimation of forearm motion using a regression model","author":"Qin","year":"2021"},{"key":"bib0034","first-page":"1","type":"other","article-title":"Neuro-musculoskeletal mapping for man-machine interfacing","volume":"10","author":"Kapelner","year":"2020"},{"key":"bib0035","first-page":"264","type":"other","article-title":"Estimation and early prediction of grip force based on sEMG signals and deep recurrent neural networks","volume":"45","author":"Ghorbani Siavashani","year":"2023"},{"key":"bib0036","first-page":"365","type":"other","article-title":"Myoelectric pattern recognition for controlling a robotic hand: a feasibility study in stroke","volume":"66","author":"Lu","year":"2018"},{"key":"bib0037","first-page":"285","type":"other","article-title":"Toward a bio-inspired rehabilitation aid: sEMG-CPG approach for online generation of jaw trajectories for a chewing robot","volume":"51","author":"Kalani","year":"2019"},{"key":"bib0038","first-page":"1","type":"other","article-title":"Comparative effects of EMG-driven robot-assisted therapy versus task-oriented training on motor and daily function in patients with stroke: a randomized cross-over trial","volume":"19","author":"Chen","year":"2022"},{"key":"bib0039","first-page":"1948","type":"other","article-title":"A low-cost real-time research platform for EMG pattern recognition-based prosthetic hand","volume":"20","author":"Geethanjali","year":"2014"},{"key":"bib0040","first-page":"229","type":"other","article-title":"A low-cost transradial prosthesis controlled by the intention of muscular contraction","volume":"44","author":"Prakash","year":"2021"},{"key":"bib0041","first-page":"978","type":"other","article-title":"A myoelectric control interface for upper-limb robotic rehabilitation following spinal cord injury","volume":"28","author":"McDonald","year":"2020"},{"key":"bib0042","first-page":"236","type":"other","article-title":"Classification of electromyographic hand gesture signals using machine learning techniques","volume":"401","author":"Jia","year":"2020"},{"key":"bib0043","first-page":"59","type":"other","article-title":"Controlling object hand-over in human\u2013robot collaboration via natural wearable sensing","volume":"49","author":"Wang","year":"2018"},{"key":"bib0044","first-page":"987","type":"other","article-title":"Deep back propagation\u2013long short-term memory network based upper-limb sEMG signal classification for automated rehabilitation","volume":"40","author":"Wang","year":"2020"},{"key":"bib0045","first-page":"83","type":"other","article-title":"Evaluation of surface EMG-based recognition algorithms for decoding hand movements","volume":"58","author":"Abbaspour","year":"2020"},{"key":"bib0046","first-page":"1526","type":"other","article-title":"Multiday evaluation of techniques for EMG-based classification of hand motions","volume":"23","author":"Waris","year":"2018"},{"key":"bib0047","type":"other","article-title":"Myoelectric pattern recognition of hand motions for stroke rehabilitation","volume":"57","author":"Castiblanco","year":"2020"},{"key":"bib0048","first-page":"2964","type":"other","article-title":"Surface-electromyography-based gesture recognition by multi-view deep learning","volume":"66","author":"Wei","year":"2019"},{"key":"bib0049","first-page":"95","type":"other","article-title":"A newly-designed wearable robotic hand exoskeleton controlled by EMG signals and ROS embedded systems","volume":"12","author":"Abdallah","year":"2023"},{"key":"bib0050","first-page":"2645","type":"other","article-title":"Predicting targets of human reaching motions using different sensing technologies","volume":"60","author":"Novak","year":"2013"},{"key":"bib0051","first-page":"465","type":"other","article-title":"Modifying kinect placement to improve upper limb joint angle measurement accuracy","volume":"29","author":"Seo","year":"2016"},{"key":"bib0052","first-page":"1","type":"other","article-title":"EMG-based pattern recognition approach in post stroke robot-aided rehabilitation: a feasibility study","volume":"10","author":"Cesqui","year":"2013"},{"key":"bib0053","first-page":"10","type":"other","article-title":"Muscle synergies control during hand-reaching tasks in multiple directions post-stroke","author":"Israely","year":"2018"},{"key":"bib0054","first-page":"7055","type":"other","article-title":"Kinematic assessment to measure change in impairment during active and active-assisted type of robotic rehabilitation for patients with stroke","volume":"21","author":"Hwang","year":"2021"},{"key":"bib0055","first-page":"307","type":"other","article-title":"Home-based movement therapy in neonatal brachial plexus palsy: a case study","volume":"28","author":"Brown","year":"2015"},{"key":"bib0056","first-page":"141","type":"other","article-title":"Evaluation of upper extremity reachable workspace in children with brachial plexus birth injury","volume":"49","author":"Richardson","year":"2024"},{"key":"bib0057","first-page":"123","type":"other","article-title":"Multimodal decoding and congruent sensory information enhance reaching performance in subjects with cervical spinal cord injury","volume":"8","author":"Corbett","year":"2014"},{"key":"bib0058","first-page":"303","type":"other","article-title":"A hybrid approach to EMG pattern analysis for classification of arm movements using statistical and fuzzy techniques","volume":"21","author":"Micera","year":"1999"},{"key":"bib0059","first-page":"128","author":"Irastorza-Landa","year":"2017","type":"other"},{"key":"bib0060","author":"Tortora","year":"2018","type":"other"},{"key":"bib0061","type":"other","article-title":"Navigating features: a topologically informed chart of electromyographic features space","volume":"14","author":"Phinyomark","year":"2017"},{"key":"bib0062","first-page":"247","type":"other","article-title":"Feature extraction of the first difference of EMG time series for EMG pattern recognition","volume":"117","author":"Phinyomark","year":"2014"},{"key":"bib0063","first-page":"27","type":"other","article-title":"Using a feature subset selection method and support vector machine to address curse of dimensionality and redundancy in hyperion hyperspectral data classification","volume":"21","author":"Salimi","year":"2018"},{"key":"bib0064","first-page":"283","type":"other","article-title":"Introduction to the special issue on the SENIAM European concerted action","volume":"10","author":"Merletti","year":"2000"},{"key":"bib0065","first-page":"158","type":"other","article-title":"Interpreting deep learning features for myoelectric control: a comparison with handcrafted features","volume":"8","author":"C\u00f4t\u00e9-Allard","year":"2020"},{"key":"bib0066","type":"other","article-title":"Neighborhood component analysis and relieff based survival recognition methods for Hepatocellular carcinoma","volume":"540","author":"Tuncer","year":"2020"},{"key":"bib0067","first-page":"18","type":"other","article-title":"Classification of focal and non-focal EEG signals using neighborhood component analysis and machine learning algorithms","volume":"113","author":"Raghu","year":"2018"},{"key":"bib0068","type":"other","article-title":"Muscle network topology analysis for the classification of chronic neck pain based on EMG biomarkers extracted during walking","volume":"16","author":"Jim\u00e9nez-Grande","year":"2021"},{"key":"bib0069","first-page":"31","type":"other","article-title":"Fast neighborhood component analysis","volume":"83","author":"Yang","year":"2012"},{"key":"bib0070","first-page":"2663","type":"other","article-title":"Feature dimensionality reduction: a review","volume":"8","author":"Jia","year":"2022"},{"key":"bib0071","type":"other","article-title":"Surface EMG signal classification using ternary pattern and discrete wavelet transform based feature extraction for hand movement recognition","volume":"58","author":"Tuncer","year":"2020"},{"key":"bib0072","type":"other","article-title":"Pattern recognition of EMG signals for low level grip force classification","volume":"7","author":"Khan","year":"2021"},{"key":"bib0073","first-page":"5190","type":"other","article-title":"Channel and feature selection for a surface electromyographic pattern recognition task","volume":"41","author":"Mesa","year":"2014"},{"key":"bib0074","first-page":"189","type":"other","article-title":"A comprehensive survey on support vector machine classification: applications, challenges and trends","volume":"408","author":"Cervantes","year":"2020"},{"key":"bib0075","type":"other","article-title":"Stress detection using ECG and EMG signals: a comprehensive study","volume":"193","author":"Pourmohammadi","year":"2020"},{"key":"bib0076","type":"other","article-title":"Deep cross-user models reduce the training burden in myoelectric control","volume":"15","author":"Campbell","year":"2021"}],"container-title":["Medical Engineering &amp; Physics"],"original-title":[],"link":[{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S1350453324000997?httpAccept=text\/xml","content-type":"text\/xml","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S1350453324000997?httpAccept=text\/plain","content-type":"text\/plain","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/iopscience.iop.org\/article\/10.1016\/j.medengphy.2024.104198","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/iopscience.iop.org\/article\/10.1016\/j.medengphy.2024.104198\/pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/iopscience.iop.org\/article\/10.1016\/j.medengphy.2024.104198\/pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"syndication"},{"URL":"https:\/\/iopscience.iop.org\/article\/10.1016\/j.medengphy.2024.104198\/pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,1,22]],"date-time":"2026-01-22T15:04:36Z","timestamp":1769094276000},"score":1,"resource":{"primary":{"URL":"https:\/\/iopscience.iop.org\/article\/10.1016\/j.medengphy.2024.104198"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024,6,26]]},"references-count":76,"journal-issue":{"issue":"1","published-online":{"date-parts":[[2024,6,26]]},"published-print":{"date-parts":[[2024,8,1]]}},"URL":"https:\/\/doi.org\/10.1016\/j.medengphy.2024.104198","relation":{},"ISSN":["1350-4533","1873-4030"],"issn-type":[{"value":"1350-4533","type":"print"},{"value":"1873-4030","type":"electronic"}],"subject":[],"published":{"date-parts":[[2024,6,26]]},"assertion":[{"value":"Feature evaluation for myoelectric pattern recognition of multiple nearby reaching targets","name":"article_title","label":"Article Title"},{"value":"Medical Engineering & Physics","name":"journal_title","label":"Journal Title"},{"value":"paper","name":"article_type","label":"Article Type"},{"value":"\u00a9 2024 Institute of Physics and Engineering in Medicine. All rights, including for text and data mining, AI training, and similar technologies, are reserved.","name":"copyright_information","label":"Copyright Information"},{"value":"2023-09-22","name":"date_received","label":"Date Received","group":{"name":"publication_dates","label":"Publication dates"}},{"value":"2024-06-25","name":"date_accepted","label":"Date Accepted","group":{"name":"publication_dates","label":"Publication dates"}},{"value":"2024-06-26","name":"date_epub","label":"Online publication date","group":{"name":"publication_dates","label":"Publication dates"}}]}}