|Partners||St Luke's Elder Care, and Tan Tock Seng Hospital|
|Focus||Assisted Ability, Assistive Robots, Novel Robotic Systems|
|Principal Investigator||Prof ANG Wei Tech|
Executive Director, Rehabilitation Research Institute of Singapore
School of Mechanical & Aerospace Engineering and LKC School of Medicine
Nanyang Technological University
|Collaborators||Dr Kenny TAN|
Chief Executive Officer, St Luke's ElderCare
Dr WEE Seng Kwee
Principal Physiotherapist, Rehabilitation Centre, Tan Tock Seng Hospital
A study of all elderly aged 65 years and older seen for trauma in an emergency department in Singapore over a six-month period revealed that, of the 720 seen, 85.3 percent of the injuries were due to falls and 49.9 percent of the patients were admitted to hospital.*
This is an increasing problem as the Singapore population continues to age. Fall prevention is gaining importance due to its prevalence and propensity to cause death. However, traditional walking sticks and frames, crutches and wheelchairs do not offer the desired solution as they only serve to decrease or limit mobility and, more importantly, overlook the need to intervene before the fall occurs.
The proposed solution
Our soft exo-suit project aims to design and develop a wearable soft exo-suit system that is capable of detecting a fall and providing timely balance recovery assistance to the user.
The exo-suit consists of:
- a fall detection system – consists of 5 inertial measurement units measuring the body kinematics data. The data is passed in real-time to the fall detection algorithm based on a single Hidden Markov Model (HMM) that has been trained with normal activities of daily living.
- a balance recovery assistance system – which brings the centre of mass to within the base of stability before the fall impact. In other words, it detects an imminent fall and corrects the user’s centre of balance to prevent the fall.