Back to Search
Start Over
Vesta: A digital health analytics platform for a smart home in a box
- Source :
- Mcconville, R, Archer, G, Craddock, I J, Kozlowski, M, Piechocki, R J, Pope, J & Santos-Rodriguez, R 2020, ' Vesta : A Digital Health Analytics Platform for a Smart Home in a Box ', Future Generation Computer Systems, vol. 114, pp. 106-119 . https://doi.org/10.1016/j.future.2020.07.046
- Publication Year :
- 2021
- Publisher :
- Elsevier BV, 2021.
-
Abstract
- This paper presents Vesta, a digital health platform composed of a smart home in a box for data collection and a machine learning based analytic system for deriving health indicators using activity recognition, sleep analysis and indoor localization. This system has been deployed in the homes of 40 patients undergoing a heart valve intervention in the United Kingdom (UK) as part of the EurValve project, measuring patients health and well-being before and after their operation. In this work a cohort of 20 patients are analyzed, and 2 patients are analyzed in detail as example case studies. A quantitative evaluation of the platform is provided using patient collected data, as well as a comparison using standardized Patient Reported Outcome Measures (PROMs) which are commonly used in hospitals, and a custom survey. It is shown how the ubiquitous in-home Vesta platform can increase clinical confidence in self-reported patient feedback. Demonstrating its suitability for digital health studies, Vesta provides deeper insight into the health, well-being and recovery of patients within their home.
- Subjects :
- Data collection
Computer Networks and Communications
business.industry
Computer science
020206 networking & telecommunications
02 engineering and technology
Data science
Health indicator
Digital health
Activity recognition
SPHERE
Hardware and Architecture
Analytics
Home automation
0202 electrical engineering, electronic engineering, information engineering
020201 artificial intelligence & image processing
Patient-reported outcome
business
Software
Subjects
Details
- ISSN :
- 0167739X
- Volume :
- 114
- Database :
- OpenAIRE
- Journal :
- Future Generation Computer Systems
- Accession number :
- edsair.doi.dedup.....a4eb3175aced7da02a68b85274d0ceae
- Full Text :
- https://doi.org/10.1016/j.future.2020.07.046