Noyce, A;
(2021)
Domotics, smart homes and Parkinson’s disease.
Journal of Parkinson's Disease
10.3233/JPD-202398.
(In press).
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Abstract
Technology has an increasing presence and role in the management of Parkinson’s disease. Whether embraced or rebuffed by patients and clinicians, this is an undoubtedly growing area. Wearable sensors have received most of the attention so far. This review will focus on technology integrated into the home setting; from fixed sensors to automated appliances, which are able to capture information and have the potential to respond in an unsupervised manner. Domotics also have the potential to provide ‘real world’ context to kinematic data and therapeutic opportunities to tackle challenging motor and non-motor symptoms. Together with wearable technology, domotics have the ability to gather long-term data and record discrete events, changing the model of the cross-sectional outpatient assessment. As clinicians, our ultimate goal is to maximise quality of life, promote autonomy, and personalisation of care. In these respects, domotics may play an essential role in the coming years.
| Type: | Article |
|---|---|
| Title: | Domotics, smart homes and Parkinson’s disease |
| Open access status: | An open access version is available from UCL Discovery |
| DOI: | 10.3233/JPD-202398 |
| Publisher version: | https://doi.org/10.3233/JPD-202398 |
| Language: | English |
| Additional information: | © 2021 – The authors. Published by IOS Press. This is an Open Access article distributed under the terms of the Creative Commons Attribution-NonCommercial License (CC BY-NC 4.0). |
| Keywords: | Domotics, smart home, technology, unsupervised monitoring, Parkinson’s disease |
| UCL classification: | UCL UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Brain Sciences UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Brain Sciences > UCL Queen Square Institute of Neurology |
| URI: | https://discovery.ucl.ac.uk/id/eprint/10120797 |
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