{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,22]],"date-time":"2026-06-22T15:14:58Z","timestamp":1782141298093,"version":"3.54.5"},"reference-count":40,"publisher":"MDPI AG","issue":"16","license":[{"start":{"date-parts":[[2020,8,13]],"date-time":"2020-08-13T00:00:00Z","timestamp":1597276800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>An inexperienced therapist lacks the analysis of a patient\u2019s movement. In addition, the patient does not receive objective feedback from the therapist due to the visual subjective judgment. The aim is to provide a guide for in-depth rehabilitation therapy in virtual space by continuously tracking the user\u2019s wrist joint during Leap Motion Controller (LMC) activities and present the basic data to confirm steady therapy results in real-time. The conventional Box and Block Test (BBT) is commonly used in upper extremity rehabilitation therapy. It was modeled in proportion to the actual size and Auto Desk Inventor was used to perform the 3D modeling work. The created 3D object was then implemented in C # through Unity5.6.2p4 based on LMC. After obtaining a wrist joint motion value, the motion was analyzed by 3D graph. Healthy subjects (23 males and 25 females, n = 48) were enrolled in this study. There was no statistically significant counting difference between conventional BBT and system BBT. This indicates the possibility of effective diagnosis and evaluation of hemiplegic patients post-stroke. We can keep track of wrist joints, check real-time continuous feedback in the implemented virtual space, and provide the basic data for an LMC-based quantitative rehabilitation therapy guide.<\/jats:p>","DOI":"10.3390\/s20164548","type":"journal-article","created":{"date-parts":[[2020,8,14]],"date-time":"2020-08-14T08:28:35Z","timestamp":1597393715000},"page":"4548","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":8,"title":["Development of a Diagnosis and Evaluation System for Hemiplegic Patients Post-Stroke Based on Motion Recognition Tracking and Analysis of Wrist Joint Kinematics"],"prefix":"10.3390","volume":"20","author":[{"given":"Subok","family":"Kim","sequence":"first","affiliation":[{"name":"Department of Computer Science &amp; Engineering, Graduate School, Soonchunhyang University, 22 Soonchunhyang-ro, Asan 31538, Korea"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Seoho","family":"Park","sequence":"additional","affiliation":[{"name":"Department of Medical IT Engineering, College of Medical Sciences, Soonchunhyang University, 22 Soonchunhyang-ro, Asan 31538, Korea"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-3696-9353","authenticated-orcid":false,"given":"Onseok","family":"Lee","sequence":"additional","affiliation":[{"name":"Department of Computer Science &amp; Engineering, Graduate School, Soonchunhyang University, 22 Soonchunhyang-ro, Asan 31538, Korea"},{"name":"Department of Medical IT Engineering, College of Medical Sciences, Soonchunhyang University, 22 Soonchunhyang-ro, Asan 31538, Korea"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2020,8,13]]},"reference":[{"key":"ref_1","first-page":"2619","article-title":"Interactive Metronome Applied in the Rehabilitative Treatment of the Central Nervous System","volume":"21","author":"Liu","year":"2017","journal-title":"Chin. 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