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.
Highlights
A significant challenge facing society today is how to better utilize technology to improve lives
Twomey et al [34] illustrate the vast array of features and algorithms typically used in the task of activity recognition
The collection of accelerometer data from a wrist-worn wearable, along with Received Signal Strength Indicator (RSSI) values at four points throughout the home, was outlined, and how this collects a large amount of valuable inhome data
Summary
A significant challenge facing society today is how to better utilize technology to improve lives One such method is the use of sensing technologies and the Internet of Things (IoT) to monitor health and well-being. Ambient Assisted Living (AAL) is vast and recently projects such as SPHERE [1] have been developing solutions for healthcare in the smart home environment. This typically involves the deployment of a myriad of sensors in the home, ranging from video cameras and wearable devices, to presence and energy sensors. Other systems include sensors that monitor computer activity, medication consumption and vehicle driving [2] The benefit of these systems to healthcare are clear [3,4]. With such systems, installation and cost is non-trivial; scaling such systems to large numbers of people quickly and efficiently remains a challenge [5]
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