Who
are we?
We are a group of Researchers from National University of Singapore (NUS) under the School of Mechanical Engineering (ME) led by Associate Professor Francis Tay Eng Hock. Our research interest is in solving the problem of the greying population by tackling problems related to Elderly and Geriatric Care.
What are we doing?
Our
MEMSWear smart shirt is capable of detecting falls at 100% rate. This will
inform caregiver (relatives / nurses) via mobile phones of a detected fall,
allowing a quick response action to prevent further suffering.
While this could minimise extended suffering, injury suffered may not be reversible. Therefore, what we are doing now is to go a step back by predicting a possible fall, preventing it if possible and if a fall is inevitable, minimise any possible injuries. At this stage, the original fall detection capabilities of MEMSWear smart shirt will kick in.
Why are we doing this?
Think of your parents, grandparents, uncles, will you be there to take care of them when you go to work? Do you feel worried that they may fall repeatedly while you are not there to attend to them? What if they go unconscious and are unable to obtain the immediate attention they need?
The problem is yours, mine, and everyone else who have elderly to care for. With the increase in elderly population led by the baby boom in the mid of last century and a hectic pace of life, the elderly may not get the attention they require. This problem will grow further in the next two or three decade as a larger population enters the greying population.
Whom are we targeting?
Our
main target is YOU, people who have elderly to care for. At the same
time, we are also targeting hospitals and elderly homes, not to replace
nurses and caregivers, but to assist them by keeping track the movement of
the patients. This research may even spin off to other industries in the
future.
|
Function |
Objectives |
Work needed |
Skill set required |
|
Fall Prediction |
· Fall prediction model · MEMS BP/ECG sensors |
· Establish fall prediction model · Design of sensors and circuits |
· C / C++ programming · Embedded System Design · PCB Design / Fabrication · Algorithm design & analysis · Knowledge in Mechatronics/ Electrical/ Medicine/ MEMS |
|
Fall prevention |
· Increment of lead time · Muscle constriction device (MCD) |
· Achieve lead time increment · Design of MCD |
|
|
Injury Min. |
· Inflatable hip protector (IHP) |
· Design of IHP |
How can you contribute?
If you have the skills that we need, you can join us and be part of our dynamic team. If you are interested in the area that we are working in, we can always collaborate, exchange ideas, and grow together. Finally, you can always contribute by showing interest in our research. If you are excited, we are excited and it will help spur us on.
For further enquiries, drop by our website at http://memswear.webhop.net/