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SMARTAR: Augmented reality platform for increasing mobility and independence of Parkinson's patients

Parkinson's disease is a progressive, neurological condition that affects over 6 million people worldwide.  Half of Parkinson’s patients suffer from a condition called Freezing of Gait (FOG), where they feel as if their feet are "glued" to the ground.  This sensation can occur when they start to walk, or while walking, and may last from several seconds to minutes.  In the UK there are 145,000 people with Parkinson's and over 72,000 people who suffer from Freezing of Gait (FOG).  This contributes not only to falls and related injuries but also compromises quality of life ,as people often avoid engaging in functional daily activities, both inside and outside the home.

SMARTAR focused on developing an augmented reality (AR) platform for increasing the mobility and independence of Parkinson's disease patients.  Taking the form of AR glasses, through the use of sensors, SMARTAR monitors a person's gait, detecting if a freezing incident occurs.  It then uses proven techniques of giving the user a visual focus point of parallel lines on the ground to "step over".

SMARTAR is a portable solution that works both inside and outside, allowing the user to keep their mobility and be more independent, and less reliant on family members or caretakers.  This is in contrast to other solutions addressing freezing in Parkinson’s patients which require the user to turn them on/off or to always be on, and they can also be very noticeable, drawing unwanted attention to the person with Parkinson's.

The main challenge addressed by Brunel University London (TWI's partner in the Brunel Innovation Centre) was to develop a suite of methodologies and algorithms for gait characterisation in Parkinson's patients.  The team successfully delivered deep learning models with variable computational requirements for maximum compatibility with multiple devices for gait and action characterisation, such as walking, standing and sitting, and a novel methodology for automatic retraining to allow fast and easy calibration to new patients by using five minutes of data for a new patient.  Gait analysis algorithms have been developed in the past using similar sensors, but the sensors were attached to arms, legs and waist, making them invasive and disruptive to everyday life.

Partners: EMTEQ Ltd, The Imagination Factory and Brunel Innovation Centre (Brunel University London).

SMARTAR secured funding from Innovate UK.

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