Health Informatics Group

Quantified-self and remote patient monitoring

Collecting biological data (e.g. heart rate, blood pressure) for diagnosis and for monitoring efficacy of treatments can be time-consuming and expensive in terms of staff resources. With growing health needs globally, there needs to be a more sustainable and participatory approach to the collection of biological data so that medical staff can focus their time on helping patients.

We are developing a quantified-self approach within the context of a ‘carer network’, an online social network that includes patients, healthcare professionals, and informal caregivers for gathering biological data for diagnosis and treatment.

Recent Publications

Fang, L, Liu, X, Su, X, Ye, J, Dobson, S, Hui, P & Tarkoma, S 2021, Bayesian inference federated learning for heart rate prediction. in J Ye, MJ O’Grady, G Civitarese & K Yordanova (eds), Wireless Mobile Communication and Healthcare: 9th EAI International Conference, MobiHealth 2020, Virtual Event, November 19, 2020, Proceedings. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, vol. 362 LNICST, Springer, Cham, pp. 116-130. https://doi.org/10.1007/978-3-030-70569-5_8

Ye, J, Dobson, SA & Zambonelli, F 2020, ‘XLearn: learning activity labels across heterogeneous datasets‘, ACM Transactions on Intelligent Systems and Technology, vol. 11, no. 2, 17. https://doi.org/10.1145/3368272

Fang, L, Ye, J & Dobson, SA 2019, Distributed self-monitoring sensor networks via Markov switching Dynamic Linear Models. in Proceedings 2019 IEEE 13th International Conference on Self-Adaptive and Self-Organizing Systems (SASO 2019)., 8780572, IEEE Computer Society, pp. 33-42, 13th IEEE International Conference on Self-Adaptive and Self-Organizing Systems (SASO 2019), Umeå, Sweden, 16/06/19. https://doi.org/10.1109/SASO.2019.00014

Fang, L, Ye, J & Dobson, SA 2019, Sensor-based human activity mining using Dirichlet process mixtures of directional statistical models. in Proceedings of the 6th IEEE International Conference on Data Science and Advanced Analytics (DSAA’19). IEEE Computer Society, 6th IEEE International Conference on Data Science and Advanced Analytics (DSAA’19), Washington DC, United States, 5/10/19.
Pirzada, P, Wilde, AG & Harris-Birtill, DCC 2019, ‘Smart Homes for elderly to promote their health and wellbeing‘, womENcourage 2019, Rome, Italy, 16/09/19 – 18/09/19.