This paper describes Tiresias, a low-cost, unobtrusive networked radar system designed to monitor vulnerable patients in domestic environments and provide high quality behavioural and health data. Dementia is a disease that affects millions worldwide and progressively degrades an individual's ability to care for themselves. Eventually most people living with dementia will need to reside in assisted living facilities as they become unable to care for themselves. Understanding the effects dementia has on ability to self-care and extending the length of time people living with dementia can remain living independently are key goals of dementia research and care. The networked radar system proposed in this paper is designed to provide high quality behavioural and health data from domestic environments. This is achieved using multiple radar sensors networked together with their data outputs integrated and processed to produce high confidence measures of position and movement. It is hoped the data produced by this system will both provide insights into how dementia progresses, and also help monitor vulnerable individuals in their own homes, allowing them to remain independent longer than would otherwise be possible.Radar, UWB, indoor tracking, networked sensing, longterm monitoring, dementia, integrated care.
I. INTRODUCTIONDementia progressively reduces the ability of those affected by it to live independently. Affecting around 50 million people worldwide [1], the effects of dementia place a heavy toll on healthcare systems and remains a leading cause of patients requiring residence in assisted living facilities. Long-term monitoring of the behaviour and well-being of patients with dementia can allow clinicians to assess both disease progression, and the effects of any interventions or changes in circumstance.High quality behavioural data can be generated by monitoring patients with video cameras using computer vision or manual behavioural labelling. However, this approach is extremely obtrusive, comes with many privacy concerns, and would be very unlikely to be acceptable to many people living with dementia [2], [3]. On the other end of the obtrusiveness scale are sensor systems for individual actions, such as use of appliances, opening of doors and windows, or presence in a [4]. Unfortunately, with the unobtrusiveness of these systems comes a reduction in the quality of the data