Visual Intelligence applies Ai technology, designed to prevent falls and promote wellbeing in elderly patients in primary care home environments.

Health Problem Falls form a large cost to the public purse.

They are one of the biggest reasons for elderly people taken into A&E, with more than 250,000 hospital admissions in the over 65s every year. £4.4 Billion are associated with fragility fractures alone, where elderly people can deteriorate into poor physical health, hospitalisation and place a heavy requirement on the adult social care system.

Falls lead to a downward spiral in health, accelerate other conditions and can result in premature death. This will only become compounded by our increasing ageing population resulting in greater patient inflows. Run with the problem or.....

Machine learning algorithms have been chosen as the perfect technology partner in reducing the associated costs of falls in the UK.

Our cameras act as optical sensory devices feeding pixelated video images to algorithms which can detect early movement in beds and chairs where patients are moving towards a transition to standing.

Alerts are sent immediately to care teams via handheld devices allowing for targeted intervention by carers to prevent falls.

The on screen fall risk assessments can activate appropriate levels of support from each algorithm providing bespoke patient care. 30 seconds of pre-fall video is automatically saved so that route causation can be determined promptly, promoting better patient outcomes.

Since mid 2022, POC testing of the fall prevention / detection algorithms have been conducted in lab settings and proved effective in identifying patient movement to transition. We are now ready to take the first steps into a real world trial, including our pressure care algorithm. Over the last 12 months we have engaged with care managers and frontline staff at an intermediate care home.

As stakeholders they are keen to see the technology implemented as they have recognised the potential for early patient outcomes.