The cameras can also detect the arrival time of light at the sensor with very high precision and at very high frame rates. The combination of these features enables the measurement of both macro-movement (in a similar fashion to more common cameras) and micro-movement (not currently possible with current, low-cost or low form-factor cameras). Micro-movement detection is sufficiently precise to capture nanometric variations in skin/body shape and thus directly detect blood flow, monitoring the precise shape and variations of heart beat. Future, very ambitious plans, include extending this capability to the brain. Our cameras can also be combined with RF technology to provide richer data, e.g. Doppler signals directly related to speed of movement.

All these indicators will be fed into machine learning models that monitor, learn and are updated over time and, most importantly, adapt to the individuals inhabiting the home environment. Thus, the systems will quickly adapt and evolve for bespoke individuals, providing precision healthcare monitoring and feedback.

Alongside the engineers and computer scientists working on the sensors and data analysis, our programme involves clinicians who will provide the interpretation models for our data and also partners who will give us access to new-generation intelligent homes inhabited by users who are already beta-testing sensors monitoring for example gross movement.