Skip to main content

Research Repository

Advanced Search

Learning to compare with few data for personalised human activity recognition. (2020)
Conference Proceeding
WIRATUNGA, N., WIJEKOON, A. and COOPER, K. 2020. Learning to compare with few data for personalised human activity recognition. In Watson, I and Weber, R. (eds.) Case-based reasoning research and development: proceedings of the 28th International conference on case-based reasoning research and development (ICCBR 2020), 8-12 June 2020, Salamanca, Spain [virtual conference]. Lecture notes in computer science, 12311. Cham: Springer [online], pages 3-14. Available from: https://doi.org/10.1007/978-3-030-58342-2_1

Recent advances in meta-learning provides interesting opportunities for CBR research, in similarity learning, case comparison and personalised recommendations. Rather than learning a single model for a specific task, meta-learners adopt a generalist... Read More about Learning to compare with few data for personalised human activity recognition..

Heterogeneous multi-modal sensor fusion with hybrid attention for exercise recognition. (2020)
Conference Proceeding
WIJEKOON, A., WIRATUNGA, N. and COOPER, K. 2020. Heterogeneous multi-modal sensor fusion with hybrid attention for exercise recognition. In Proceedings of the 2020 Institute of Electrical and Electronics Engineers (IEEE) International joint conference on neural networks (IEEE IJCNN 2020), part of the 2020 IEEE World congress on computational intelligence (IEEE WCCI 2020) and co-located with the 2020 IEEE congress on evolutionary computation (IEEE CEC 2020) and the 2020 IEEE International fuzzy systems conference (FUZZ-IEEE 2020), 19-24 July 2020, [virtual conference]. Piscataway: IEEE [online], article ID 9206941. Available from: https://doi.org/10.1109/IJCNN48605.2020.9206941

Exercise adherence is a key component of digital behaviour change interventions for the self-management of musculoskeletal pain. Automated monitoring of exercise adherence requires sensors that can capture patients performing exercises and Machine Le... Read More about Heterogeneous multi-modal sensor fusion with hybrid attention for exercise recognition..

Learning to recognise exercises for the self-management of low back pain. (2020)
Conference Proceeding
WIJEKOON, A., WIRATUNGA, N., COOPER, K. and BACH, K. 2020. Learning to recognise exercises for the self-management of low back pain. In Barták, R. and Bell, E. (eds.). Proceedings of the 33rd International Florida Artificial Intelligence Research Society (FLAIRS) 2020 conference (FLAIRS-33), 17-20 May 2020, Miami Beach, USA. Palo Alto: AAAI Press [online], pages 347-352. Available from: https://aaai.org/ocs/index.php/FLAIRS/FLAIRS20/paper/view/18460

Globally, Low back pain (LBP) is one of the top three contributors to years lived with disability. Self-management with an active lifestyle is the cornerstone for preventing and managing LBP. Digital interventions are introduced in the recent past to... Read More about Learning to recognise exercises for the self-management of low back pain..

A knowledge-light approach to personalised and open-ended human activity recognition. (2020)
Journal Article
WIJEKOON, A., WIRATUNGA, N., SANI, S. and COOPER, K. 2020. A knowledge-light approach to personalised and open-ended human activity recognition. Knowledge-based systems [online], 192, article ID 105651. Available from: https://doi.org/10.1016/j.knosys.2020.105651

Human Activity Recognition (HAR) is a core component of clinical decision support systems that rely on activity monitoring for self-management of chronic conditions such as Musculoskeletal Disorders. Deployment success of such applications in part de... Read More about A knowledge-light approach to personalised and open-ended human activity recognition..

Improving kNN for human activity recognition with privileged learning using translation models. (2018)
Conference Proceeding
WIJEKOON, A., WIRATUNGA, N., SANI, S., MASSIE, S. and COOPER, K. 2018. Improving kNN for human activity recognition with privileged learning using translation models. In Cox, M.T., Funk, P. and Begum, S. (eds.) Case-based reasoning research and development: proceedings of the 26th International conference on case-based reasoning (ICCBR 2018), 9-12 July 2018, Stockholm, Sweden. Lecture notes in computer science, 11156. Cham: Springer [online], pages 448-463. Available from: https://doi.org/10.1007/978-3-030-01081-2_30

Multiple sensor modalities provide more accurate Human Activity Recognition (HAR) compared to using a single modality, yet the latter is preferred by consumers as it is more convenient and less intrusive. This presents a challenge to researchers, as... Read More about Improving kNN for human activity recognition with privileged learning using translation models..