Sadiq Sani
SelfBACK: Activity recognition for self-management of low back pain.
Sani, Sadiq; Wiratunga, Nirmalie; Massie, Stewart; Cooper, Kay
Authors
Professor Nirmalie Wiratunga n.wiratunga@rgu.ac.uk
Professor
Dr Stewart Massie s.massie@rgu.ac.uk
Reader
Professor Kay Cooper k.cooper@rgu.ac.uk
Clinical Professor
Contributors
Max Bramer
Editor
Miltos Petridis
Editor
Abstract
Low back pain (LBP) is the most significant contributor to years lived with disability in Europe and results in significant financial cost to European economies. Guidelines for the management of LBP have self-management at their cornerstone, where patients are advised against bed rest, and to remain active. In this paper, we introduce SelfBACK, a decision support system used by the patients themselves to improve and reinforce self-management of LBP. SelfBACK uses activity recognition from wearable sensors in order to automatically determine the type and level of activity of a user. This is used by the system to automatically determine how well users adhere to prescribed physical activity guidelines. Important parameters of an activity recognition system include windowing, feature extraction and classification. The choices of these parameters for the SelfBACK system are supported by empirical comparative analysis which are presented in this paper. In addition, two approaches are presented for detecting step counts for ambulation activities (e.g. walking and running) which help to determine activity intensity. Evaluation shows the SelfBACK system is able to distinguish between five common daily activities with 0.9 macro-averaged F1 and detect step counts with 6.4 and 5.6 root mean squared error for walking and running respectively.
Citation
SANI, S., WIRATUNGA, N., MASSIE, S. and COOPER, K. 2016. SelfBACK: Activity recognition for self-management of low back pain. In Bramer, M. and Petridis, M. (eds.) 2016. Research and development in intelligent systems XXXIII: incorporating applications and innovations in intelligent systems XXIV: proceedings of the 36th SGAI nternational conference on innovative techniques and applications of artificial intelligence (SGAI 2016), 13-15 December 2016, Cambridge, UK. Cham: Springer [online], pages 281-294. Available from: https://doi.org/10.1007/978-3-319-47175-4_21
Conference Name | 36th SGAI International conference on innovative techniques and applications of artificial intelligence (AI-2016) |
---|---|
Conference Location | Cambridge, UK |
Start Date | Dec 13, 2016 |
End Date | Dec 15, 2016 |
Acceptance Date | Jul 11, 2016 |
Online Publication Date | Nov 5, 2016 |
Publication Date | Nov 5, 2016 |
Deposit Date | Nov 11, 2016 |
Publicly Available Date | Nov 6, 2017 |
Publisher | Springer |
Pages | 281-294 |
ISBN | 9783319471747 |
DOI | https://doi.org/10.1007/978-3-319-47175-4 |
Keywords | Low back pain (LBP); SelfBACK; Selfmanagement |
Public URL | http://hdl.handle.net/10059/1973 |
Files
SANI 2016 Selfback activity recognition
(1.1 Mb)
PDF
Publisher Licence URL
https://creativecommons.org/licenses/by-nc-nd/4.0/
You might also like
Reasoning with counterfactual explanations for code vulnerability detection and correction.
(2021)
Conference Proceeding
Memory efficient federated deep learning for intrusion detection in IoT networks.
(2021)
Conference Proceeding
Improving kNN for human activity recognition with privileged learning using translation models.
(2018)
Conference Proceeding