There are great deals of research into fall. It is generally accepted that falls may cause severe injuries, which contributes function decline and disability. Fall is, however, preventable with regularly risk factor assessing and appropriate muscle training. Since prolonged monitor of physical activity (PA) provides evidences to the tendency of health and predictive of risk of falling, a personal PA monitoring system is desirable to record all daytime activities. Our objective is to develop a system to evaluate the risk of fall for adults with intellectual disability in a nursing home.
A compact data logging system which comprised with a MCU, buzzer, rechargeable battery, mini-SD memory card, and tri-axis’s accelerometer was developed and embedded inside a transfer belt, which was worn by 10 subjects selected by physical therapists from the nursing home. The belts were then worn by subjects during all daytime activities planned by the social workers for 12 weeks with 5 days per week. All falls occurred were reported by the social workers in documentation with time and causes.
Detection of fall and PA monitoring are factors in understanding and preventing fall. The systems successfully recorded all activities data and captured a few falls which were confirmed by observations. These data clearly show walking time and number of step. These were furnished to the physical therapist for further study and planning exercise. The subject’s walking frequency pattern can, however, change from time to time. An adaptive step enumerated algorithm will be implemented in next trial to improve the step enumeration.