The design and development of a long-term fall detection system incorporated into a custom vest for the elderly.
A fall detection system and algorithm, incorporated into a custom designed garment has been developed. The developed fall detection system uses a tri-axial accelerometer, microcontroller, battery and Bluetooth module. This sensor is attached to a custom designed vest, designed to be worn by the elderly person under clothing. The fall detection algorithm was developed and incorporates both impact and posture detection capability. The vest and fall algorithm was tested on young healthy subjects performing normal activities of daily living (ADL) and falls onto crash mats, while wearing the best and sensor. Results show that falls can de distinguished from normal activities with a sensitivity >90% and a specificity of >99%, from a total data set of 264 falls and 165 normal ADL. By incorporating the fall-detection sensor into a custom designed garment it is anticipated that greater compliance when wearing a fall-detection system can be achieved and will help reduce the incidence of the long-lie, when falls occur in the elderly population. However further long-term testing using elderly subjects is required to validate the systems performance.
Bourke
Alan K
AK
CAALYX FP6 project, Wireless Access Research Centre, Department of Electronic and Computer Engineering, University of Limerick, Ireland. alan.bourke@ul.ie
van de Ven
Pepijn W J
PW
Chaya
Amy E
AE
OLaighin
Gearóid M
GM
Nelson
John
J
D000054:Acceleration; D000058:Accidental Falls / Q000517:prevention & control*; D000203:Activities of Daily Living; D000328:Adult; D000368:Aged; D000465:Algorithms; D001696:Biomechanical Phenomena; D003020:Clothing; D004867:Equipment Design; D006801:Humans; D008297:Male; D008422:Materials Testing; D018670:Monitoring, Ambulatory / Q000379:methods*; D009068:Movement / Q000502:physiology*; D012815:Signal Processing, Computer-Assisted