{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,9,16]],"date-time":"2026-09-16T19:26:23Z","timestamp":1789586783271,"version":"build-2803163510"},"reference-count":34,"publisher":"Frontiers Media SA","license":[{"start":{"date-parts":[[2023,5,10]],"date-time":"2023-05-10T00:00:00Z","timestamp":1683676800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":["frontiersin.org"],"crossmark-restriction":true},"short-container-title":["Front. Neurosci."],"abstract":"<jats:sec><jats:title>Introduction<\/jats:title><jats:p>Compensatory movements usually occur in stroke survivors with hemiplegia, which is detrimental to recovery. This paper proposes a compensatory movement detection method based on near-infrared spectroscopy (NIRS) technology and verifies its feasibility using a machine learning algorithm. We present a differential-based signal improvement (DBSI) method to enhance NIRS signal quality and discuss its effect on improving detection performance.<\/jats:p><\/jats:sec><jats:sec><jats:title>Method<\/jats:title><jats:p>Ten healthy subjects and six stroke survivors performed three common rehabilitation training tasks while the activation of six trunk muscles was recorded using NIRS sensors. After data preprocessing, DBSI was applied to the NIRS signals, and two time-domain features (mean and variance) were extracted. An SVM algorithm was used to test the effect of the NIRS signal on compensatory behavior detection.<\/jats:p><\/jats:sec><jats:sec><jats:title>Results<\/jats:title><jats:p>Classification results show that NIRS signals have good performance in compensatory detection, with accuracy rates of 97.76% in healthy subjects and 97.95% in stroke survivors. After using the DBSI method, the accuracy improved to 98.52% and 99.47%, respectively.<\/jats:p><\/jats:sec><jats:sec><jats:title>Discussion<\/jats:title><jats:p>Compared with other compensatory motion detection methods, our proposed method based on NIRS technology has better classification performance. The study highlights the potential of NIRS technology for improving stroke rehabilitation and warrants further investigation.<\/jats:p><\/jats:sec>","DOI":"10.3389\/fnins.2023.1153252","type":"journal-article","created":{"date-parts":[[2023,5,10]],"date-time":"2023-05-10T15:03:25Z","timestamp":1683731005000},"update-policy":"https:\/\/doi.org\/10.3389\/crossmark-policy","source":"Crossref","is-referenced-by-count":5,"title":["Compensatory movement detection by using near-infrared spectroscopy technology based on signal improvement method"],"prefix":"10.3389","volume":"17","author":[{"given":"Xiang","family":"Chen","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"YinJin","family":"Shao","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"LinFeng","family":"Zou","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"SiMin","family":"Tang","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Zhiwei","family":"Lai","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"XiaoBo","family":"Sun","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"FaWen","family":"Xie","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Longhan","family":"Xie","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jun","family":"Luo","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Dongxia","family":"Hu","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1965","published-online":{"date-parts":[[2023,5,10]]},"reference":[{"key":"B1","doi-asserted-by":"publisher","first-page":"104","DOI":"10.1186\/s12984-018-0451-2","article-title":"Kinect-based assessment of proximal arm non-use after a stroke","volume":"15","author":"Bakhti","year":"2018","journal-title":"J. NeuroEng. Rehabil"},{"key":"B2","doi-asserted-by":"publisher","first-page":"80300","DOI":"10.1109\/ACCESS.2019.2923077","article-title":"Automatic detection of compensatory movement patterns by a pressure distribution mattress using machine learning methods: a pilot study","volume":"7","author":"Cai","year":"","journal-title":"IEEE Access"},{"key":"B3","doi-asserted-by":"publisher","first-page":"131","DOI":"10.1186\/s12984-019-0609-6","article-title":"Detecting compensatory movements of stroke survivors using pressure distribution data and machine learning algorithms","volume":"16","author":"Cai","year":"","journal-title":"J. NeuroEng. Rehabil"},{"key":"B4","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1145\/1961189.1961199","article-title":"Libsvm: A library for support vector machines","volume":"2","author":"Chang","year":"2011","journal-title":"ACM Trans. Intell. Syst. Technol"},{"key":"B5","doi-asserted-by":"publisher","first-page":"102345","DOI":"10.1016\/j.bspc.2020.102345","article-title":"Trunk compensation electromyography features purification and classification model using generative adversarial network","volume":"65","author":"Chen","year":"2021","journal-title":"Biomed. Signal Process. Control"},{"key":"B6","doi-asserted-by":"publisher","first-page":"940","DOI":"10.1093\/brain\/123.5.940","article-title":"Compensatory strategies for reaching in stroke","volume":"123","author":"Cirstea","year":"2000","journal-title":"Brain"},{"key":"B7","doi-asserted-by":"publisher","first-page":"273","DOI":"10.1007\/BF00994018","article-title":"Support-vector networks","volume":"20","author":"Cortes","year":"1995","journal-title":"Mach. Learn"},{"key":"B8","doi-asserted-by":"publisher","first-page":"3039","DOI":"10.1016\/j.neuroimage.2009.11.050","article-title":"Functional near infrared spectroscopy (NIRS) signal improvement based on negative correlation between oxygenated and deoxygenated hemoglobin dynamics","volume":"49","author":"Cui","year":"2010","journal-title":"NeuroImage"},{"key":"B9","doi-asserted-by":"publisher","first-page":"921","DOI":"10.1016\/j.neuroimage.2012.03.049","article-title":"A brief review on the history of human functional near-infrared spectroscopy (fNIRS) development and fields of application","volume":"63","author":"Ferrari","year":"2012","journal-title":"NeuroImage"},{"key":"B10","doi-asserted-by":"publisher","first-page":"447","DOI":"10.1109\/JSEN.2015.2459067","article-title":"Development of a multi-channel compact-size wireless hybrid sEMG\/NIRS sensor system for prosthetic manipulation","volume":"16","author":"Guo","year":"2016","journal-title":"IEEE Sensors J"},{"key":"B11","doi-asserted-by":"publisher","first-page":"564","DOI":"10.1109\/THMS.2016.2641389","article-title":"Toward an enhanced human-machine interface for upper-limb prosthesis control with combined EMG and NIRS signals","volume":"47","author":"Guo","year":"2017","journal-title":"IEEE Trans. Hum. Mach. Syst"},{"key":"B12","doi-asserted-by":"publisher","first-page":"442","DOI":"10.3389\/fnhum.2016.00442","article-title":"Rehabilitation of motor function after stroke: a multiple systematic review focused on techniques to stimulate upper extremity recovery","volume":"10","author":"Hatem","year":"2016","journal-title":"Front. Hum. Neurosci"},{"key":"B13","doi-asserted-by":"publisher","first-page":"415","DOI":"10.1109\/72.991427","article-title":"A comparison of methods for multiclass support vector machines","volume":"13","author":"Hsu","year":"2002","journal-title":"IEEE Trans. Neural Netw"},{"key":"B14","doi-asserted-by":"publisher","first-page":"1650056","DOI":"10.1142\/S1793545816500565","article-title":"Combined surface electromyography, near-infrared spectroscopy and acceleration recordings of muscle contraction: the effect of motion","volume":"10","author":"Kauppi","year":"2017","journal-title":"J. Innov. Opt. Health Sci"},{"key":"B15","doi-asserted-by":"publisher","first-page":"1","DOI":"10.3390\/ijms21207609","article-title":"Pathophysiology and treatment of stroke: present status and future perspectives","volume":"21","author":"Kuriakose","year":"2020","journal-title":"Int. J. Mol. Sci"},{"key":"B16","doi-asserted-by":"publisher","first-page":"313","DOI":"10.1177\/1545968308328727","article-title":"What do motor \u201crecovery\u201d and \u201ccompensationg\u201d mean in patients following stroke?","volume":"23","author":"Levin","year":"2009","journal-title":"Neurorehabil. Neural Repair"},{"key":"B17","doi-asserted-by":"publisher","first-page":"768","DOI":"10.1109\/IAECST54258.2021.9695873","article-title":"\u201cA vision-based compensation detection approach during robotic stroke rehabilitation therapy,\u201d","author":"Lin","year":"2021","journal-title":"2021 3rd International Academic Exchange Conference on Science and Technology Innovation (IAECST)"},{"key":"B18","doi-asserted-by":"publisher","first-page":"1250","DOI":"10.3389\/fnins.2019.01250","article-title":"SEMG-based trunk compensation detection in rehabilitation training","volume":"13","author":"Ma","year":"2019","journal-title":"Front. Neurosci"},{"key":"B19","doi-asserted-by":"publisher","first-page":"6","DOI":"10.1186\/1743-0003-3-6","article-title":"The evolution of methods for the capture of human movement leading to markerless motion capture for biomechanical applications","volume":"3","author":"M\u00fcndermann","year":"2006","journal-title":"J. Neuroeng. Rehabil"},{"key":"B20","doi-asserted-by":"crossref","DOI":"10.1038\/nbt1206-1565","article-title":"What is a support vector machine?","author":"Noble","year":"2006"},{"key":"B21","doi-asserted-by":"publisher","first-page":"505","DOI":"10.3389\/fnhum.2018.00505","article-title":"Current status and issues regarding pre-processing of fNIRS neuroimaging data: an investigation of diverse signal filtering methods within a general linear model framework","volume":"12","author":"Pinti","year":"2019","journal-title":"Front. Hum. Neurosci"},{"key":"B22","doi-asserted-by":"publisher","first-page":"2222","DOI":"10.1088\/1361-6579\/aa9835","article-title":"Identifying compensatory movement patterns in the upper extremity using a wearable sensor system","volume":"38","author":"Ranganathan","year":"2017","journal-title":"Physiol. Measure"},{"key":"B23","doi-asserted-by":"publisher","first-page":"84","DOI":"10.1186\/1479-5868-9-84","article-title":"Validity of activity monitors in health and chronic disease: a systematic review systematic review introduction","volume":"9","author":"Remoortel","year":"2012","journal-title":"Int. J. Behav. Nutr. Phys. Act"},{"key":"B24","doi-asserted-by":"publisher","first-page":"6","DOI":"10.1016\/j.neuroimage.2013.05.004","article-title":"A review on continuous wave functional near-infrared spectroscopy and imaging instrumentation and methodology","volume":"85","author":"Scholkmann","year":"2014","journal-title":"NeuroImage"},{"key":"B25","doi-asserted-by":"publisher","first-page":"3702","DOI":"10.1109\/JSEN.2020.3023742","article-title":"Toward an integrated multi-modal SEMG\/MMG\/NIRS sensing system for human-machine interface robust to muscular fatigue","volume":"21","author":"Sheng","year":"2021","journal-title":"IEEE Sensors J"},{"key":"B26","doi-asserted-by":"publisher","first-page":"2535","DOI":"10.3390\/s21072535","article-title":"Near infrared spectroscopy for muscle specific analysis of intensity and fatigue during cross-country skiing competition\u2013a case report","volume":"21","author":"St\u00f6ggl","year":"2021","journal-title":"Sensors"},{"key":"B27","doi-asserted-by":"publisher","first-page":"13","DOI":"10.1177\/1545968312449695","article-title":"Arm motor recovery using a virtual reality intervention in chronic stroke: randomized control trial","volume":"27","author":"Subramanian","year":"2013","journal-title":"Neurorehabil. Neural Repair"},{"key":"B28","doi-asserted-by":"publisher","first-page":"1607","DOI":"10.1109\/BioRob.2012.6290668","article-title":"\u201cVision-based posture assessment to detect and categorize compensation during robotic rehabilitation therapy,\u201d","author":"Taati","year":"2012","journal-title":"2012 4th IEEE RAS & EMBS International Conference on Biomedical Robotics and Biomechatronics (BioRob)"},{"key":"B29","doi-asserted-by":"publisher","first-page":"985","DOI":"10.3389\/fphys.2017.00985","article-title":"Interpreting signal amplitudes in surface electromyography studies in sport and rehabilitation sciences","volume":"8","author":"Vigotsky","year":"2018","journal-title":"Front. Physiol"},{"key":"B30","doi-asserted-by":"publisher","first-page":"20","DOI":"10.1186\/s12984-017-0229-y","article-title":"Interactive wearable systems for upper body rehabilitation: a systematic review","volume":"14","author":"Wang","year":"2017","journal-title":"J. Neuroeng. Rehabil"},{"key":"B31","doi-asserted-by":"publisher","first-page":"e34307","DOI":"10.2196\/preprints.34307","article-title":"Technology-based compensation assessment and detection of upper extremity activities of stroke survivors: systematic review","volume":"24","author":"Wang","year":"2022","journal-title":"J. Med. Internet Res"},{"key":"B32","doi-asserted-by":"publisher","first-page":"22714","DOI":"10.1109\/JSEN.2022.3216351","article-title":"Development of a wireless multichannel near-infrared spectroscopy sensor system for monitoring muscle activity","volume":"22","author":"Xie","year":"2022","journal-title":"IEEE Sensors J"},{"key":"B33","doi-asserted-by":"publisher","first-page":"568","DOI":"10.1016\/j.neucom.2016.05.038","article-title":"Surface EMG based handgrip force predictions using gene expression programming","volume":"207","author":"Yang","year":"2015","journal-title":"Neurocomputing"},{"key":"B34","doi-asserted-by":"publisher","first-page":"2100107","DOI":"10.1109\/JTEHM.2017.2780836","article-title":"Automatic detection of compensation during robotic stroke rehabilitation therapy","volume":"6","author":"Zhi","year":"2017","journal-title":"IEEE J. Transl. Eng. Health Med"}],"container-title":["Frontiers in Neuroscience"],"original-title":[],"link":[{"URL":"https:\/\/www.frontiersin.org\/articles\/10.3389\/fnins.2023.1153252\/full","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2023,5,10]],"date-time":"2023-05-10T15:03:28Z","timestamp":1683731008000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.frontiersin.org\/articles\/10.3389\/fnins.2023.1153252\/full"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2023,5,10]]},"references-count":34,"alternative-id":["10.3389\/fnins.2023.1153252"],"URL":"https:\/\/doi.org\/10.3389\/fnins.2023.1153252","relation":{},"ISSN":["1662-453X"],"issn-type":[{"value":"1662-453X","type":"electronic"}],"subject":[],"published":{"date-parts":[[2023,5,10]]},"article-number":"1153252"}}