{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,4]],"date-time":"2026-06-04T20:02:03Z","timestamp":1780603323311,"version":"3.54.1"},"reference-count":41,"publisher":"Elsevier BV","license":[{"start":{"date-parts":[[2026,9,1]],"date-time":"2026-09-01T00:00:00Z","timestamp":1788220800000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/tdm\/userlicense\/1.0\/"},{"start":{"date-parts":[[2026,9,1]],"date-time":"2026-09-01T00:00:00Z","timestamp":1788220800000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/legal\/tdmrep-license"},{"start":{"date-parts":[[2026,9,1]],"date-time":"2026-09-01T00:00:00Z","timestamp":1788220800000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-017"},{"start":{"date-parts":[[2026,9,1]],"date-time":"2026-09-01T00:00:00Z","timestamp":1788220800000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"},{"start":{"date-parts":[[2026,9,1]],"date-time":"2026-09-01T00:00:00Z","timestamp":1788220800000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-012"},{"start":{"date-parts":[[2026,9,1]],"date-time":"2026-09-01T00:00:00Z","timestamp":1788220800000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2026,9,1]],"date-time":"2026-09-01T00:00:00Z","timestamp":1788220800000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-004"}],"content-domain":{"domain":["elsevier.com","sciencedirect.com"],"crossmark-restriction":true},"short-container-title":["Biomedical Signal Processing and Control"],"published-print":{"date-parts":[[2026,9]]},"DOI":"10.1016\/j.bspc.2026.110639","type":"journal-article","created":{"date-parts":[[2026,5,23]],"date-time":"2026-05-23T21:26:06Z","timestamp":1779571566000},"page":"110639","update-policy":"https:\/\/doi.org\/10.1016\/elsevier_cm_policy","source":"Crossref","is-referenced-by-count":0,"special_numbering":"C","title":["Video-based hand pose estimation for Parkinsonian bradykinesia analysis and evaluation"],"prefix":"10.1016","volume":"124","author":[{"given":"Chenhui","family":"Wang","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-5958-2234","authenticated-orcid":false,"given":"Rui","family":"Wang","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Songqing","family":"Yao","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Xin","family":"Shi","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Mengmeng","family":"Fu","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Xiaohong","family":"Chen","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Xin","family":"Wang","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"78","reference":[{"issue":"1","key":"10.1016\/j.bspc.2026.110639_b1","first-page":"1","article-title":"Parkinson disease","volume":"3","author":"Poewe","year":"2017","journal-title":"Nat. Rev. Dis. Prim."},{"issue":"15","key":"10.1016\/j.bspc.2026.110639_b2","doi-asserted-by":"crossref","first-page":"2129","DOI":"10.1002\/mds.22340","article-title":"Movement disorder society-sponsored revision of the unified parkinson\u2019s disease rating scale (MDS-UPDRS): scale presentation and clinimetric testing results","volume":"23","author":"Goetz","year":"2008","journal-title":"Mov. Disord.: Off. J. Mov. Disord. Soc."},{"issue":"10","key":"10.1016\/j.bspc.2026.110639_b3","doi-asserted-by":"crossref","first-page":"1859","DOI":"10.1002\/mds.23740","article-title":"The modified bradykinesia rating scale for parkinson\u2019s disease: reliability and comparison with kinematic measures","volume":"26","author":"Heldman","year":"2011","journal-title":"Mov. Disorders"},{"issue":"6","key":"10.1016\/j.bspc.2026.110639_b4","doi-asserted-by":"crossref","first-page":"864","DOI":"10.1109\/TITB.2009.2033471","article-title":"Monitoring motor fluctuations in patients with parkinson\u2019s disease using wearable sensors","volume":"13","author":"Patel","year":"2009","journal-title":"IEEE Trans. Inf. Technol. Biomed."},{"issue":"3","key":"10.1016\/j.bspc.2026.110639_b5","doi-asserted-by":"crossref","first-page":"365","DOI":"10.1007\/s11517-010-0697-8","article-title":"Quantification of bradykinesia during clinical finger taps using a gyrosensor in patients with parkinson\u2019s disease","volume":"49","author":"Kim","year":"2011","journal-title":"Med. Biol. Eng. Comput."},{"issue":"2","key":"10.1016\/j.bspc.2026.110639_b6","doi-asserted-by":"crossref","first-page":"203","DOI":"10.3390\/s17020203","article-title":"Quantification of finger-tapping angle based on wearable sensors","volume":"17","author":"Djuri\u0107-Jovi\u010di\u0107","year":"2017","journal-title":"Sensors"},{"issue":"11","key":"10.1016\/j.bspc.2026.110639_b7","doi-asserted-by":"crossref","first-page":"2644","DOI":"10.3390\/s19112644","article-title":"An expert system for quantification of bradykinesia based on wearable inertial sensors","volume":"19","author":"Bobi\u0107","year":"2019","journal-title":"Sensors"},{"issue":"8","key":"10.1016\/j.bspc.2026.110639_b8","doi-asserted-by":"crossref","first-page":"3848","DOI":"10.1109\/JBHI.2022.3162386","article-title":"Vision-based finger tapping test in patients with parkinson\u2019s disease via spatial-temporal 3D hand pose estimation","volume":"26","author":"Guo","year":"2022","journal-title":"IEEE J. Biomed. Health Inform."},{"issue":"6","key":"10.1016\/j.bspc.2026.110639_b9","doi-asserted-by":"crossref","first-page":"875","DOI":"10.1002\/mdc3.12536","article-title":"Optical hand tracking: a novel technique for the assessment of bradykinesia in parkinson\u2019s disease","volume":"4","author":"Bank","year":"2017","journal-title":"Mov. Disord. Clin. Pr."},{"issue":"10","key":"10.1016\/j.bspc.2026.110639_b10","doi-asserted-by":"crossref","first-page":"1952","DOI":"10.1109\/TNSRE.2019.2939596","article-title":"Vision-based method for automatic quantification of parkinsonian bradykinesia","volume":"27","author":"Liu","year":"2019","journal-title":"IEEE Trans. Neural Syst. Rehabil. Eng."},{"key":"10.1016\/j.bspc.2026.110639_b11","doi-asserted-by":"crossref","first-page":"260","DOI":"10.1016\/j.neucom.2021.02.011","article-title":"Automated assessment of parkinsonian finger-tapping tests through a vision-based fine-grained classification model","volume":"441","author":"Li","year":"2021","journal-title":"Neurocomputing"},{"issue":"3","key":"10.1016\/j.bspc.2026.110639_b12","doi-asserted-by":"crossref","first-page":"351","DOI":"10.1007\/s40846-022-00701-y","article-title":"An automatic evaluation method for parkinson\u2019s dyskinesia using finger tapping video for small samples","volume":"42","author":"Li","year":"2022","journal-title":"J. Med. Biological Eng."},{"key":"10.1016\/j.bspc.2026.110639_b13","series-title":"2019 41st Annual International Conference of the IEEE Engineering in Medicine and Biology Society","first-page":"3408","article-title":"Improving automatic tremor and movement motor disorder severity assessment for parkinson\u2019s disease with deep joint training","author":"Chang","year":"2019"},{"key":"10.1016\/j.bspc.2026.110639_b14","doi-asserted-by":"crossref","DOI":"10.1016\/j.jneumeth.2019.108576","article-title":"Automatic detection and quantification of hand movements toward development of an objective assessment of tremor and bradykinesia in parkinson\u2019s disease","volume":"333","author":"Pang","year":"2020","journal-title":"J. Neurosci. Methods"},{"issue":"10","key":"10.1016\/j.bspc.2026.110639_b15","doi-asserted-by":"crossref","DOI":"10.1371\/journal.pone.0275490","article-title":"Automatic extraction of upper-limb kinematic activity using deep learning-based markerless tracking during deep brain stimulation implantation for parkinson\u2019s disease: A proof of concept study","volume":"17","author":"Baker","year":"2022","journal-title":"Plos One"},{"key":"10.1016\/j.bspc.2026.110639_b16","doi-asserted-by":"crossref","DOI":"10.3389\/fneur.2021.742654","article-title":"Remote evaluation of parkinson\u2019s disease using a conventional webcam and artificial intelligence","volume":"12","author":"Monje","year":"2021","journal-title":"Front. Neurol."},{"key":"10.1016\/j.bspc.2026.110639_b17","doi-asserted-by":"crossref","DOI":"10.1016\/j.artmed.2020.101966","article-title":"Supervised classification of bradykinesia in parkinson\u2019s disease from smartphone videos","volume":"110","author":"Williams","year":"2020","journal-title":"Artif. Intell. Med."},{"issue":"2","key":"10.1016\/j.bspc.2026.110639_b18","first-page":"1","article-title":"Bradykinesia recognition in parkinson\u2019s disease via single RGB video","volume":"14","author":"Lin","year":"2020","journal-title":"ACM Trans. Knowl. Discov. Data (TKDD)"},{"key":"10.1016\/j.bspc.2026.110639_b19","doi-asserted-by":"crossref","unstructured":"Y. Chen, H. Ma, J. Wang, J. Wu, X. Wu, X. Xie, PD-Net: quantitative motor function evaluation for Parkinson\u2019s disease via automated hand gesture analysis, in: Proceedings of the 27th ACM SIGKDD Conference on Knowledge Discovery & Data Mining, 2021, pp. 2683\u20132691.","DOI":"10.1145\/3447548.3467130"},{"key":"10.1016\/j.bspc.2026.110639_b20","doi-asserted-by":"crossref","DOI":"10.1016\/j.eswa.2023.121093","article-title":"Parallel scale de-blur net for sharpening video images for remote clinical assessment of hand movements","volume":"235","author":"Li","year":"2024","journal-title":"Expert Syst. Appl."},{"issue":"20","key":"10.1016\/j.bspc.2026.110639_b21","doi-asserted-by":"crossref","first-page":"7992","DOI":"10.3390\/s22207992","article-title":"Video-based hand movement analysis of parkinson patients before and after medication using high-frame-rate videos and MediaPipe","volume":"22","author":"G\u00fcney","year":"2022","journal-title":"Sensors"},{"key":"10.1016\/j.bspc.2026.110639_b22","doi-asserted-by":"crossref","unstructured":"S.-E. Wei, V. Ramakrishna, T. Kanade, Y. Sheikh, Convolutional pose machines, in: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2016, pp. 4724\u20134732.","DOI":"10.1109\/CVPR.2016.511"},{"key":"10.1016\/j.bspc.2026.110639_b23","series-title":"European Conference on Computer Vision","first-page":"483","article-title":"Stacked hourglass networks for human pose estimation","author":"Newell","year":"2016"},{"key":"10.1016\/j.bspc.2026.110639_b24","doi-asserted-by":"crossref","unstructured":"B. Xiao, H. Wu, Y. Wei, Simple baselines for human pose estimation and tracking, in: Proceedings of the European Conference on Computer Vision, ECCV, 2018, pp. 466\u2013481.","DOI":"10.1007\/978-3-030-01231-1_29"},{"key":"10.1016\/j.bspc.2026.110639_b25","doi-asserted-by":"crossref","unstructured":"K. Sun, B. Xiao, D. Liu, J. Wang, Deep high-resolution representation learning for human pose estimation, in: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, 2019, pp. 5693\u20135703.","DOI":"10.1109\/CVPR.2019.00584"},{"key":"10.1016\/j.bspc.2026.110639_b26","doi-asserted-by":"crossref","DOI":"10.1016\/j.jvcir.2022.103461","article-title":"Optimized convolutional pose machine for 2D hand pose estimation","volume":"83","author":"Pan","year":"2022","journal-title":"J. Vis. Commun. Image Represent."},{"issue":"11","key":"10.1016\/j.bspc.2026.110639_b27","doi-asserted-by":"crossref","first-page":"3258","DOI":"10.1109\/TCSVT.2018.2879980","article-title":"Mask-pose cascaded cnn for 2d hand pose estimation from single color image","volume":"29","author":"Wang","year":"2018","journal-title":"IEEE Trans. Circuits Syst. Video Technol."},{"key":"10.1016\/j.bspc.2026.110639_b28","doi-asserted-by":"crossref","unstructured":"Y. Chen, H. Ma, D. Kong, X. Yan, J. Wu, W. Fan, X. Xie, Nonparametric structure regularization machine for 2d hand pose estimation, in: Proceedings of the IEEE\/CVF Winter Conference on Applications of Computer Vision, 2020, pp. 381\u2013390.","DOI":"10.1109\/WACV45572.2020.9093271"},{"key":"10.1016\/j.bspc.2026.110639_b29","series-title":"Adaptive graphical model network for 2D handpose estimation","author":"Kong","year":"2019"},{"key":"10.1016\/j.bspc.2026.110639_b30","doi-asserted-by":"crossref","unstructured":"F. Zhang, X. Zhu, H. Dai, M. Ye, C. Zhu, Distribution-aware coordinate representation for human pose estimation, in: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, 2020, pp. 7093\u20137102.","DOI":"10.1109\/CVPR42600.2020.00712"},{"key":"10.1016\/j.bspc.2026.110639_b31","doi-asserted-by":"crossref","unstructured":"A. Rajagopalan, et al., Improving robustness of semantic segmentation to motion-blur using class-centric augmentation, in: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, 2023, pp. 10470\u201310479.","DOI":"10.1109\/CVPR52729.2023.01009"},{"issue":"8","key":"10.1016\/j.bspc.2026.110639_b32","doi-asserted-by":"crossref","first-page":"3502","DOI":"10.1109\/TIP.2012.2192126","article-title":"Modeling the performance of image restoration from motion blur","volume":"21","author":"Boracchi","year":"2012","journal-title":"IEEE Trans. Image Process."},{"key":"10.1016\/j.bspc.2026.110639_b33","doi-asserted-by":"crossref","unstructured":"M. Sayed, G. Brostow, Improved handling of motion blur in online object detection, in: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, 2021, pp. 1706\u20131716.","DOI":"10.1109\/CVPR46437.2021.00175"},{"key":"10.1016\/j.bspc.2026.110639_b34","doi-asserted-by":"crossref","unstructured":"L. Ke, M.-C. Chang, H. Qi, S. Lyu, Multi-scale structure-aware network for human pose estimation, in: Proceedings of the European Conference on Computer Vision, ECCV, 2018, pp. 713\u2013728.","DOI":"10.1007\/978-3-030-01216-8_44"},{"issue":"01","key":"10.1016\/j.bspc.2026.110639_b35","doi-asserted-by":"crossref","DOI":"10.1142\/S0218001423560220","article-title":"Multi-scale feature refined network for human pose estimation","volume":"38","author":"Yang","year":"2024","journal-title":"Int. J. Pattern Recognit. Artif. Intell."},{"issue":"4","key":"10.1016\/j.bspc.2026.110639_b36","doi-asserted-by":"crossref","first-page":"588","DOI":"10.3390\/a5040588","article-title":"An efficient algorithm for automatic peak detection in noisy periodic and quasi-periodic signals","volume":"5","author":"Scholkmann","year":"2012","journal-title":"Algorithms"},{"key":"10.1016\/j.bspc.2026.110639_b37","series-title":"Pattern Recognition and Machine Learning","author":"Bishop","year":"2006"},{"key":"10.1016\/j.bspc.2026.110639_b38","series-title":"The Elements of Statistical Learning: Data Mining, Inference, and Prediction","author":"Hastie","year":"2009"},{"key":"10.1016\/j.bspc.2026.110639_b39","doi-asserted-by":"crossref","unstructured":"T. Simon, H. Joo, I. Matthews, Y. Sheikh, Hand keypoint detection in single images using multiview bootstrapping, in: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2017, pp. 1145\u20131153.","DOI":"10.1109\/CVPR.2017.494"},{"key":"10.1016\/j.bspc.2026.110639_b40","doi-asserted-by":"crossref","unstructured":"C. Zimmermann, D. Ceylan, J. Yang, B. Russell, M. Argus, T. Brox, Freihand: A dataset for markerless capture of hand pose and shape from single rgb images, in: Proceedings of the IEEE\/CVF International Conference on Computer Vision, 2019, pp. 813\u2013822.","DOI":"10.1109\/ICCV.2019.00090"},{"key":"10.1016\/j.bspc.2026.110639_b41","article-title":"A unified approach to interpreting model predictions","volume":"30","author":"Lundberg","year":"2017","journal-title":"Adv. Neural Inf. Process. Syst."}],"container-title":["Biomedical Signal Processing and Control"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S1746809426011936?httpAccept=text\/xml","content-type":"text\/xml","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S1746809426011936?httpAccept=text\/plain","content-type":"text\/plain","content-version":"vor","intended-application":"text-mining"}],"deposited":{"date-parts":[[2026,6,4]],"date-time":"2026-06-04T19:38:52Z","timestamp":1780601932000},"score":1,"resource":{"primary":{"URL":"https:\/\/linkinghub.elsevier.com\/retrieve\/pii\/S1746809426011936"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,9]]},"references-count":41,"alternative-id":["S1746809426011936"],"URL":"https:\/\/doi.org\/10.1016\/j.bspc.2026.110639","relation":{},"ISSN":["1746-8094"],"issn-type":[{"value":"1746-8094","type":"print"}],"subject":[],"published":{"date-parts":[[2026,9]]},"assertion":[{"value":"Elsevier","name":"publisher","label":"This article is maintained by"},{"value":"Video-based hand pose estimation for Parkinsonian bradykinesia analysis and evaluation","name":"articletitle","label":"Article Title"},{"value":"Biomedical Signal Processing and Control","name":"journaltitle","label":"Journal Title"},{"value":"https:\/\/doi.org\/10.1016\/j.bspc.2026.110639","name":"articlelink","label":"CrossRef DOI link to publisher maintained version"},{"value":"article","name":"content_type","label":"Content Type"},{"value":"\u00a9 2026 Published by Elsevier Ltd.","name":"copyright","label":"Copyright"}],"article-number":"110639"}}