A multi-state model to improve the design of an automated system to monitor the activity patterns of patients with bipolar disorder
2013
J Oper Res Soc
3
64
372-383
Journal_Article
Psychiatry
Simulation_Monte_carlo_methods||Probability_Markov_processes
Operational_Online
No
No
Article Link
Mohiuddin, S. G., Brailsford, S. C., James, C. J., Amor, J. D., Blum, J. M., Crowe, J. A., . . . Prociow, P. A. (2013). A multi-state model to improve the design of an automated system to monitor the activity patterns of patients with bipolar disorder. [Journal Article]. J Oper Res Soc, 64(3), 372-383.
This paper describes the role of mathematical modelling in the design and evaluation of an automated system of wearable and environmental sensors called PAM (Personalised Ambient Monitoring) to monitor the activity patterns of patients with bipolar disorder (BD). The modelling work was part of an EPSRC-funded project, also involving biomedical engineers and computer scientists, to develop a prototype PAM system. BD is a chronic, disabling mental illness associated with recurrent severe episodes of mania and depression, interspersed with periods of remission. Early detection of the onset of an acute episode is crucial for effective treatment and control. The aim of PAM is to enable patients with BD to self-manage their condition, by identifying the person's normal