Renjie Li, Guan Huang, Xinyi Wang, Katherine Lawler, Lynette R Goldberg, Eddy Roccati, Rebecca J St George, Mimieveshiofuo Aiyede, Anna E King, Aidan D Bindoff, James C Vickers, Quan Bai, Jane Alty
{"title":"用于早期检测阿尔茨海默病和帕金森病的智能手机自动运动和语音分析:在 20 种不同设备上验证 TapTalk。","authors":"Renjie Li, Guan Huang, Xinyi Wang, Katherine Lawler, Lynette R Goldberg, Eddy Roccati, Rebecca J St George, Mimieveshiofuo Aiyede, Anna E King, Aidan D Bindoff, James C Vickers, Quan Bai, Jane Alty","doi":"10.1002/dad2.70025","DOIUrl":null,"url":null,"abstract":"<p><strong>Introduction: </strong>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-level 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-standard measures.</p><p><strong>Methods: </strong>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 Hz) and a microphone acquired simultaneous movement and voice data, respectively.</p><p><strong>Results: </strong>TapTalk video and audio outcomes were comparable to gold-standard data: 90.3% of video, and 98.3% of audio, data recorded tapping/speech frequencies within ± 1 Hz of the gold-standard measures.</p><p><strong>Discussion: </strong>Validation of TapTalk across a range of devices is an important step in the development of smartphone-based telemedicine and was achieved in this study.</p><p><strong>Highlights: </strong>TapTalk evaluates hand motor and speech functions across a wide range of smartphones.Data showed 90.3% motor and 98.3% speech accuracy within +/-1 Hz of gold standards.Validation advances smartphone-based telemedicine for neurodegenerative diseases.</p>","PeriodicalId":53226,"journal":{"name":"Alzheimer''s and Dementia: Diagnosis, Assessment and Disease Monitoring","volume":"16 4","pages":"e70025"},"PeriodicalIF":4.0000,"publicationDate":"2024-10-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11496774/pdf/","citationCount":"0","resultStr":"{\"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.\",\"authors\":\"Renjie Li, Guan Huang, Xinyi Wang, Katherine Lawler, Lynette R Goldberg, Eddy Roccati, Rebecca J St George, Mimieveshiofuo Aiyede, Anna E King, Aidan D Bindoff, James C Vickers, Quan Bai, Jane Alty\",\"doi\":\"10.1002/dad2.70025\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><strong>Introduction: </strong>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-level 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-standard measures.</p><p><strong>Methods: </strong>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 Hz) and a microphone acquired simultaneous movement and voice data, respectively.</p><p><strong>Results: </strong>TapTalk video and audio outcomes were comparable to gold-standard data: 90.3% of video, and 98.3% of audio, data recorded tapping/speech frequencies within ± 1 Hz of the gold-standard measures.</p><p><strong>Discussion: </strong>Validation of TapTalk across a range of devices is an important step in the development of smartphone-based telemedicine and was achieved in this study.</p><p><strong>Highlights: </strong>TapTalk evaluates hand motor and speech functions across a wide range of smartphones.Data showed 90.3% motor and 98.3% speech accuracy within +/-1 Hz of gold standards.Validation advances smartphone-based telemedicine for neurodegenerative diseases.</p>\",\"PeriodicalId\":53226,\"journal\":{\"name\":\"Alzheimer''s and Dementia: Diagnosis, Assessment and Disease Monitoring\",\"volume\":\"16 4\",\"pages\":\"e70025\"},\"PeriodicalIF\":4.0000,\"publicationDate\":\"2024-10-23\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11496774/pdf/\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Alzheimer''s and Dementia: Diagnosis, Assessment and Disease Monitoring\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1002/dad2.70025\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"2024/10/1 0:00:00\",\"PubModel\":\"eCollection\",\"JCR\":\"Q1\",\"JCRName\":\"CLINICAL NEUROLOGY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Alzheimer''s and Dementia: Diagnosis, Assessment and Disease Monitoring","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1002/dad2.70025","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2024/10/1 0:00:00","PubModel":"eCollection","JCR":"Q1","JCRName":"CLINICAL NEUROLOGY","Score":null,"Total":0}
Smartphone automated motor and speech analysis for early detection of Alzheimer's disease and Parkinson's disease: Validation of TapTalk across 20 different devices.
Introduction: 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-level 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-standard measures.
Methods: 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 Hz) and a microphone acquired simultaneous movement and voice data, respectively.
Results: TapTalk video and audio outcomes were comparable to gold-standard data: 90.3% of video, and 98.3% of audio, data recorded tapping/speech frequencies within ± 1 Hz of the gold-standard measures.
Discussion: Validation of TapTalk across a range of devices is an important step in the development of smartphone-based telemedicine and was achieved in this study.
Highlights: TapTalk evaluates hand motor and speech functions across a wide range of smartphones.Data showed 90.3% motor and 98.3% speech accuracy within +/-1 Hz of gold standards.Validation advances smartphone-based telemedicine for neurodegenerative diseases.
期刊介绍:
Alzheimer''s & Dementia: Diagnosis, Assessment & Disease Monitoring (DADM) is an open access, peer-reviewed, journal from the Alzheimer''s Association® that will publish new research that reports the discovery, development and validation of instruments, technologies, algorithms, and innovative processes. Papers will cover a range of topics interested in the early and accurate detection of individuals with memory complaints and/or among asymptomatic individuals at elevated risk for various forms of memory disorders. The expectation for published papers will be to translate fundamental knowledge about the neurobiology of the disease into practical reports that describe both the conceptual and methodological aspects of the submitted scientific inquiry. Published topics will explore the development of biomarkers, surrogate markers, and conceptual/methodological challenges. Publication priority will be given to papers that 1) describe putative surrogate markers that accurately track disease progression, 2) biomarkers that fulfill international regulatory requirements, 3) reports from large, well-characterized population-based cohorts that comprise the heterogeneity and diversity of asymptomatic individuals and 4) algorithmic development that considers multi-marker arrays (e.g., integrated-omics, genetics, biofluids, imaging, etc.) and advanced computational analytics and technologies.