Projects per year
Abstract
The majority of the Ambient Assisted Living (AAL) systems, designed for home or lab settings, monitor one participant at a time -- this is to avoid the complexities of pre-fusion correspondence of different sensors since carers, guests, and visitors may be involved in real world scenarios.
Previous work from [Masullo2020] presented a solution to this problem that involves matching video sequences of silhouettes to accelerations from wearable sensors to identify members of a household while respecting their privacy.
In this work, we elevate this approach to the next stage by improving its architecture and combining it with a tracking functionality that makes it possible to be deployed in real-world homes. We present experiments on a new dataset recorded in participants' own houses, which includes multiple participants visited by guests, and show an auROC score of 90.2%. We also show a novel first example of subject-tailored health monitoring measurement by applying our methodology to a sit-to-stand detector to generate clinically relevant rehabilitation trends.
Previous work from [Masullo2020] presented a solution to this problem that involves matching video sequences of silhouettes to accelerations from wearable sensors to identify members of a household while respecting their privacy.
In this work, we elevate this approach to the next stage by improving its architecture and combining it with a tracking functionality that makes it possible to be deployed in real-world homes. We present experiments on a new dataset recorded in participants' own houses, which includes multiple participants visited by guests, and show an auROC score of 90.2%. We also show a novel first example of subject-tailored health monitoring measurement by applying our methodology to a sit-to-stand detector to generate clinically relevant rehabilitation trends.
| Original language | English |
|---|---|
| Publication status | Accepted/In press - 2021 |
| Event | 16th International Conference on Computer Vision Theory and Applications - Online, Austria Duration: 8 Feb 2021 → 10 Feb 2021 Conference number: 16 http://www.visapp.visigrapp.org/Home.aspx |
Conference
| Conference | 16th International Conference on Computer Vision Theory and Applications |
|---|---|
| Abbreviated title | VISAPP |
| Country/Territory | Austria |
| Period | 8/02/21 → 10/02/21 |
| Internet address |
Research Groups and Themes
- SPHERE
Fingerprint
Dive into the research topics of 'No Need for a Lab: Towards Multi-Sensory Fusion for Ambient Assisted Living in Real-World Living Homes'. Together they form a unique fingerprint.Projects
- 1 Finished
-
SPHERE2
Craddock, I. J. (Principal Investigator), Mirmehdi, M. (Co-Investigator), Piechocki, R. J. (Co-Investigator), Flach, P. A. (Co-Investigator), Oikonomou, G. (Co-Investigator), Burghardt, T. (Co-Investigator), Damen, D. (Co-Investigator), Santos-Rodriguez, R. (Co-Investigator), O'Kane, A. A. (Co-Investigator), McConville, R. (Co-Investigator), Masullo, A. (Co-Investigator) & Gooberman-Hill, R. (Co-Investigator)
1/10/18 → 31/01/23
Project: Research, Parent