Smartphone automated motor and speech analysis for early detection of Alzheimer's disease and Parkinson's disease: Validation of TapTalk across 20 different devices
Abstract 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 prot...
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| Format: | Article |
| Language: | English |
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Wiley
2024-10-01
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| Series: | Alzheimer’s & Dementia: Diagnosis, Assessment & Disease Monitoring |
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| Online Access: | https://doi.org/10.1002/dad2.70025 |
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| author | 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 |
| author_facet | 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 |
| author_sort | Renjie Li |
| collection | DOAJ |
| description | Abstract 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. |
| format | Article |
| id | doaj-art-c7d2de4a5af54147908a9a2b889f63a5 |
| institution | Kabale University |
| issn | 2352-8729 |
| language | English |
| publishDate | 2024-10-01 |
| publisher | Wiley |
| record_format | Article |
| series | Alzheimer’s & Dementia: Diagnosis, Assessment & Disease Monitoring |
| spelling | doaj-art-c7d2de4a5af54147908a9a2b889f63a52024-12-27T13:08:30ZengWileyAlzheimer’s & Dementia: Diagnosis, Assessment & Disease Monitoring2352-87292024-10-01164n/an/a10.1002/dad2.70025Smartphone automated motor and speech analysis for early detection of Alzheimer's disease and Parkinson's disease: Validation of TapTalk across 20 different devicesRenjie Li0Guan Huang1Xinyi Wang2Katherine Lawler3Lynette R. Goldberg4Eddy Roccati5Rebecca J. St George6Mimieveshiofuo Aiyede7Anna E. King8Aidan D. Bindoff9James C. Vickers10Quan Bai11Jane Alty12Wicking Dementia Research and Education Centre University of Tasmania Hobart Tasmania AustraliaWicking Dementia Research and Education Centre University of Tasmania Hobart Tasmania AustraliaWicking Dementia Research and Education Centre University of Tasmania Hobart Tasmania AustraliaWicking Dementia Research and Education Centre University of Tasmania Hobart Tasmania AustraliaWicking Dementia Research and Education Centre University of Tasmania Hobart Tasmania AustraliaWicking Dementia Research and Education Centre University of Tasmania Hobart Tasmania AustraliaSchool of Psychological Sciences University of Tasmania Hobart Tasmania AustraliaWicking Dementia Research and Education Centre University of Tasmania Hobart Tasmania AustraliaWicking Dementia Research and Education Centre University of Tasmania Hobart Tasmania AustraliaWicking Dementia Research and Education Centre University of Tasmania Hobart Tasmania AustraliaWicking Dementia Research and Education Centre University of Tasmania Hobart Tasmania AustraliaSchool of ICT University of Tasmania Hobart Tasmania AustraliaWicking Dementia Research and Education Centre University of Tasmania Hobart Tasmania AustraliaAbstract 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.https://doi.org/10.1002/dad2.70025biomarkersdementiaMediapipemotor–cognitivepreclinical |
| spellingShingle | 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 Smartphone automated motor and speech analysis for early detection of Alzheimer's disease and Parkinson's disease: Validation of TapTalk across 20 different devices Alzheimer’s & Dementia: Diagnosis, Assessment & Disease Monitoring biomarkers dementia Mediapipe motor–cognitive preclinical |
| 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 |
| title_full | Smartphone automated motor and speech analysis for early detection of Alzheimer's disease and Parkinson's disease: Validation of TapTalk across 20 different devices |
| title_fullStr | Smartphone automated motor and speech analysis for early detection of Alzheimer's disease and Parkinson's disease: Validation of TapTalk across 20 different devices |
| title_full_unstemmed | Smartphone automated motor and speech analysis for early detection of Alzheimer's disease and Parkinson's disease: Validation of TapTalk across 20 different devices |
| title_short | Smartphone automated motor and speech analysis for early detection of Alzheimer's disease and Parkinson's disease: Validation of TapTalk across 20 different devices |
| title_sort | smartphone automated motor and speech analysis for early detection of alzheimer s disease and parkinson s disease validation of taptalk across 20 different devices |
| topic | biomarkers dementia Mediapipe motor–cognitive preclinical |
| url | https://doi.org/10.1002/dad2.70025 |
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