TIHM: An open dataset for remote healthcare monitoring in dementia
Abstract Dementia is a progressive condition that affects cognitive and functional abilities. There is a need for reliable and continuous health monitoring of People Living with Dementia (PLWD) to improve their quality of life and support their independent living. Healthcare services often focus on...
| Main Authors: | , , , , , , , , , , , , |
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| Format: | Article |
| Language: | English |
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Nature Portfolio
2023-09-01
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| Series: | Scientific Data |
| Online Access: | https://doi.org/10.1038/s41597-023-02519-y |
| _version_ | 1827724701653270528 |
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| author | Francesca Palermo Yu Chen Alexander Capstick Nan Fletcher-Loyd Chloe Walsh Samaneh Kouchaki Jessica True Olga Balazikova Eyal Soreq Gregory Scott Helen Rostill Ramin Nilforooshan Payam Barnaghi |
| author_facet | Francesca Palermo Yu Chen Alexander Capstick Nan Fletcher-Loyd Chloe Walsh Samaneh Kouchaki Jessica True Olga Balazikova Eyal Soreq Gregory Scott Helen Rostill Ramin Nilforooshan Payam Barnaghi |
| author_sort | Francesca Palermo |
| collection | DOAJ |
| description | Abstract Dementia is a progressive condition that affects cognitive and functional abilities. There is a need for reliable and continuous health monitoring of People Living with Dementia (PLWD) to improve their quality of life and support their independent living. Healthcare services often focus on addressing and treating already established health conditions that affect PLWD. Managing these conditions continuously can inform better decision-making earlier for higher-quality care management for PLWD. The Technology Integrated Health Management (TIHM) project developed a new digital platform to routinely collect longitudinal, observational, and measurement data, within the home and apply machine learning and analytical models for the detection and prediction of adverse health events affecting the well-being of PLWD. This work describes the TIHM dataset collected during the second phase (i.e., feasibility study) of the TIHM project. The data was collected from homes of 56 PLWD and associated with events and clinical observations (daily activity, physiological monitoring, and labels for health-related conditions). The study recorded an average of 50 days of data per participant, totalling 2803 days. |
| first_indexed | 2024-03-10T22:19:05Z |
| format | Article |
| id | doaj.art-228e36dac52d42f9b565ae106f3375fd |
| institution | Directory Open Access Journal |
| issn | 2052-4463 |
| language | English |
| last_indexed | 2024-03-10T22:19:05Z |
| publishDate | 2023-09-01 |
| publisher | Nature Portfolio |
| record_format | Article |
| series | Scientific Data |
| spelling | doaj.art-228e36dac52d42f9b565ae106f3375fd2023-11-19T12:20:12ZengNature PortfolioScientific Data2052-44632023-09-0110111010.1038/s41597-023-02519-yTIHM: An open dataset for remote healthcare monitoring in dementiaFrancesca Palermo0Yu Chen1Alexander Capstick2Nan Fletcher-Loyd3Chloe Walsh4Samaneh Kouchaki5Jessica True6Olga Balazikova7Eyal Soreq8Gregory Scott9Helen Rostill10Ramin Nilforooshan11Payam Barnaghi12Imperial College London, Department of Brain SciencesImperial College London, Department of Brain SciencesImperial College London, Department of Brain SciencesImperial College London, Department of Brain SciencesImperial College London, Department of Brain SciencesThe UK Dementia Research Institute, Care Research and Technology CentreSurrey and Borders Partnership NHS TrustSurrey and Borders Partnership NHS TrustImperial College London, Department of Brain SciencesImperial College London, Department of Brain SciencesImperial College London, Department of Brain SciencesImperial College London, Department of Brain SciencesImperial College London, Department of Brain SciencesAbstract Dementia is a progressive condition that affects cognitive and functional abilities. There is a need for reliable and continuous health monitoring of People Living with Dementia (PLWD) to improve their quality of life and support their independent living. Healthcare services often focus on addressing and treating already established health conditions that affect PLWD. Managing these conditions continuously can inform better decision-making earlier for higher-quality care management for PLWD. The Technology Integrated Health Management (TIHM) project developed a new digital platform to routinely collect longitudinal, observational, and measurement data, within the home and apply machine learning and analytical models for the detection and prediction of adverse health events affecting the well-being of PLWD. This work describes the TIHM dataset collected during the second phase (i.e., feasibility study) of the TIHM project. The data was collected from homes of 56 PLWD and associated with events and clinical observations (daily activity, physiological monitoring, and labels for health-related conditions). The study recorded an average of 50 days of data per participant, totalling 2803 days.https://doi.org/10.1038/s41597-023-02519-y |
| spellingShingle | Francesca Palermo Yu Chen Alexander Capstick Nan Fletcher-Loyd Chloe Walsh Samaneh Kouchaki Jessica True Olga Balazikova Eyal Soreq Gregory Scott Helen Rostill Ramin Nilforooshan Payam Barnaghi TIHM: An open dataset for remote healthcare monitoring in dementia Scientific Data |
| title | TIHM: An open dataset for remote healthcare monitoring in dementia |
| title_full | TIHM: An open dataset for remote healthcare monitoring in dementia |
| title_fullStr | TIHM: An open dataset for remote healthcare monitoring in dementia |
| title_full_unstemmed | TIHM: An open dataset for remote healthcare monitoring in dementia |
| title_short | TIHM: An open dataset for remote healthcare monitoring in dementia |
| title_sort | tihm an open dataset for remote healthcare monitoring in dementia |
| url | https://doi.org/10.1038/s41597-023-02519-y |
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