{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,19]],"date-time":"2026-10-19T08:23:55Z","timestamp":1792398235407,"version":"4.4.0"},"reference-count":40,"publisher":"Wiley","issue":"4","license":[{"start":{"date-parts":[[2024,10,23]],"date-time":"2024-10-23T00:00:00Z","timestamp":1729641600000},"content-version":"vor","delay-in-days":22,"URL":"http:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":["alz-journals.onlinelibrary.wiley.com"],"crossmark-restriction":true},"short-container-title":["Alz &amp;amp; Dem Diag Ass &amp;amp; Dis Mo"],"published-print":{"date-parts":[[2024,10]]},"abstract":"<jats:title>Abstract<\/jats:title><jats:sec><jats:title>INTRODUCTION<\/jats:title><jats:p>Smartphones are proving useful in assessing movement and speech function in Alzheimer's disease and other neurodegenerative conditions. Valid outcomes across different smartphones are needed before population\u2010level tests are deployed. This study introduces the TapTalk protocol, a novel app designed to capture hand and speech function and validate it in smartphones against gold\u2010standard measures.<\/jats:p><\/jats:sec><jats:sec><jats:title>METHODS<\/jats:title><jats:p>Twenty different smartphones collected video data from motor tests and audio data from speech tests. Features were extracted using Google Mediapipe (movement) and Python audio analysis packages (speech). Electromagnetic sensors (60\u00a0Hz) and a microphone acquired simultaneous movement and voice data, respectively.<\/jats:p><\/jats:sec><jats:sec><jats:title>RESULTS<\/jats:title><jats:p>TapTalk video and audio outcomes were comparable to gold\u2010standard data: 90.3% of video, and 98.3% of audio, data recorded tapping\/speech frequencies within\u00a0\u00b1\u00a01\u00a0Hz of the gold\u2010standard measures.<\/jats:p><\/jats:sec><jats:sec><jats:title>DISCUSSION<\/jats:title><jats:p>Validation of TapTalk across a range of devices is an important step in the development of smartphone\u2010based telemedicine and was achieved in this study.<\/jats:p><\/jats:sec><jats:sec><jats:title>Highlights<\/jats:title><jats:p><jats:list list-type=\"bullet\">\n<jats:list-item><jats:p>TapTalk evaluates hand motor and speech\u00a0functions across a wide range of smartphones.<\/jats:p><\/jats:list-item>\n<jats:list-item><jats:p>Data showed 90.3% motor and 98.3% speech accuracy within +\/\u20131\u00a0Hz of gold standards.<\/jats:p><\/jats:list-item>\n<jats:list-item><jats:p>Validation advances smartphone\u2010based telemedicine for neurodegenerative diseases.<\/jats:p><\/jats:list-item>\n<\/jats:list><\/jats:p><\/jats:sec>","DOI":"10.1002\/dad2.70025","type":"journal-article","created":{"date-parts":[[2024,10,23]],"date-time":"2024-10-23T03:43:56Z","timestamp":1729655036000},"update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":4,"title":["Smartphone automated motor and speech analysis for early detection of Alzheimer's disease and Parkinson's disease: Validation of TapTalk across 20 different devices"],"prefix":"10.1002","volume":"16","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-2374-5067","authenticated-orcid":false,"given":"Renjie","family":"Li","sequence":"first","affiliation":[{"name":"Wicking Dementia Research and Education Centre University of Tasmania  Hobart Tasmania Australia"},{"name":"School of ICT University of 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