The challenge

Balance is the single most important factor in reducing falls in the elderly.

It is a fundamental motor skill and is needed to help maintain posture and mobile activities. A weakened balance control results in inevitable falls.

Elderly people at risk of fall need to be retrained on how to maintain their balance.

The proposed solution

Our Mobile Robotic Assistive Balance Trainer (MRABT) aims to administer standing and mobile balance control assistance and training for people with high to medium fall risk in the home or in a community setting.

MRABT is a follow-me robotic wheelchair with a robotic arm that provides balance assistance to the user only when the centre of mass of the body deviates beyond the predefined safety boundary. Think of it like the helping pair of hands of a parent when a toddler learns to walk.

Special attention has been paid to the timing of balance assistance intervention in the design of the control algorithm. To promote motor re-learning, the system allows the execution of a central nervous system controlled balance mechanism before the robot intervenes to provide balance assistance.

By allowing more balance practices in standing and mobile-assisted daily living activities without the danger of fall, we hypothesise that this approach will promote true recovery in motor skills dependent on balance ability and eventually lead to lower risk of fall.

The project aims to perform proof-of-concept trials on healthy elderly subjects before moving to patient trials in the future.