{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,2,21]],"date-time":"2025-02-21T14:35:23Z","timestamp":1740148523754,"version":"3.37.3"},"reference-count":44,"publisher":"Wiley","license":[{"start":{"date-parts":[[2015,1,1]],"date-time":"2015-01-01T00:00:00Z","timestamp":1420070400000},"content-version":"unspecified","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by\/3.0\/"}],"funder":[{"name":"Australian Federal and Victoria State Governments"},{"DOI":"10.13039\/501100000923","name":"Australian Research Council","doi-asserted-by":"publisher","id":[{"id":"10.13039\/501100000923","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Journal of Sensors"],"published-print":{"date-parts":[[2015]]},"abstract":"<jats:p>Effective telerehabilitation technologies enable patients with certain physiological disabilities to engage in rehabilitative exercises for performing Activities of Daily Living (ADLs). Therefore, training and assessment scenarios for the performance of ADLs are vital for the promotion for telerehabilitation. In this paper we investigate quantitatively and automatically assessing patient\u2019s kinematic ability to perform functional upper extremity reaching tasks. The shape of the movement trajectory and the instantaneous acceleration of kinematically crucial body parts, such as wrists, are used to compute the approximate entropy of the motions to represent stability (smoothness) in addition to the duration of the activity. Computer simulations were conducted to illustrate the consistency, sensitivity and robustness of the proposed method. A preliminary experiment with kinematic data captured from healthy subjects mimicking a reaching task with dyskinesia showed a high degree of correlation (Cohen\u2019s kappa 0.85 with<mml:math xmlns:mml=\"http:\/\/www.w3.org\/1998\/Math\/MathML\" id=\"M1\"><mml:mi>p<\/mml:mi><mml:mo>&lt;<\/mml:mo><mml:mn>0.05<\/mml:mn><\/mml:math>) between a human observer and the proposed automatic classification tool in terms of assigning the datasets to various levels to represent the subjects\u2019 kinematic abilities to perform reaching tasks. This study supported the use of Microsoft Kinect to quantitatively evaluate the ability of individuals with involuntary movements to perform an upper extremity reaching task.<\/jats:p>","DOI":"10.1155\/2015\/236474","type":"journal-article","created":{"date-parts":[[2015,6,17]],"date-time":"2015-06-17T18:32:56Z","timestamp":1434565976000},"page":"1-13","source":"Crossref","is-referenced-by-count":5,"title":["Quantitative Assessment of ADL: A Pilot Study of Upper Extremity Reaching Tasks"],"prefix":"10.1155","volume":"2015","author":[{"given":"Saiyi","family":"Li","sequence":"first","affiliation":[{"name":"School of Engineering, Deakin University, Waurn Ponds, VIC 3216, Australia"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Pubudu N.","family":"Pathirana","sequence":"additional","affiliation":[{"name":"School of Engineering, Deakin University, Waurn Ponds, VIC 3216, Australia"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Mary 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