{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,28]],"date-time":"2026-02-28T04:30:49Z","timestamp":1772253049651,"version":"3.50.1"},"reference-count":34,"publisher":"MDPI AG","issue":"12","license":[{"start":{"date-parts":[[2022,6,11]],"date-time":"2022-06-11T00:00:00Z","timestamp":1654905600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"New Jersey Governor\u2019s Council for the Medical Research and Treatments of Autism","award":["CAUT17BSP024"],"award-info":[{"award-number":["CAUT17BSP024"]}]},{"name":"Nancy Lurie Marks Family Foundation","award":["CAUT17BSP024"],"award-info":[{"award-number":["CAUT17BSP024"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>Although interest in using wearable sensors to characterize movement disorders is growing, there is a lack of methodology for developing clinically interpretable biomarkers. Such digital biomarkers would provide a more objective diagnosis, capturing finer degrees of motor deficits, while retaining the information of traditional clinical tests. We aim at digitizing traditional tests of cognitive and memory performance to derive motor biometrics of pen-strokes and voice, thereby complementing clinical tests with objective criteria, while enhancing the overall characterization of Parkinson\u2019s disease (PD). 35 participants including patients with PD, healthy young and age-matched controls performed a series of drawing and memory tasks, while their pen movement and voice were digitized. We examined the moment-to-moment variability of time series reflecting the pen speed and voice amplitude. The stochastic signatures of the fluctuations in pen drawing speed and voice amplitude of patients with PD show a higher signal-to-noise ratio compared to those of neurotypical controls. It appears that contact motions of the pen strokes on a tablet evoke sensory feedback for more immediate and predictable control in PD, while voice amplitude loses its neurotypical richness. We offer new standardized data types and analytics to discover the hidden motor aspects within the cognitive and memory clinical assays.<\/jats:p>","DOI":"10.3390\/s22124434","type":"journal-article","created":{"date-parts":[[2022,6,13]],"date-time":"2022-06-13T02:01:44Z","timestamp":1655085704000},"page":"4434","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":5,"title":["Motor Signatures in Digitized Cognitive and Memory Tests Enhances Characterization of Parkinson\u2019s Disease"],"prefix":"10.3390","volume":"22","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-4073-8099","authenticated-orcid":false,"given":"Jihye","family":"Ryu","sequence":"first","affiliation":[{"name":"Department of Psychology, Rutgers University, New Brunswick, NJ 08854, USA"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-4011-3611","authenticated-orcid":false,"given":"Elizabeth B.","family":"Torres","sequence":"additional","affiliation":[{"name":"Rutgers University Center for Cognitive Science, Computational Biomedicine Imaging and Modeling Center at Computer Science Department, Psychology Department, Rutgers University, Piscataway, NJ 08854, USA"}]}],"member":"1968","published-online":{"date-parts":[[2022,6,11]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"388","DOI":"10.3389\/fneur.2017.00388","article-title":"Quantitative Assessment of the Arm\/Hand Movements in Parkinson\u2019s Disease Using a Wireless Armband Device","volume":"8","author":"Spasojevic","year":"2017","journal-title":"Front. 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