Unfortunately, falls are very common among the elderly population, which can lead to high health care costs and
mortality [1-3].
After a serious fall has occurred, the fear of future falling can also tax a heavy psychological toll on the patient, leading to functional declines and even eventually limit the person to be placed in an institution for the elderly [4].
Numerous researchers have performed fall detection using body-worn accelerometers [5-7]. Several accelerometer-based
fall detection reports use simple threshold values to differentiate between falls and activities of daily living (ADL)
for patients.
These systems mostly rely on a single threshold value to detect whether an activity is considered as a fall or
simply an ADL, therefore are prone to false positives.
In addition, an accelerometer-only system cannot measure minutes [3].
Such situations may have trapped the fallers in danger no matter the falling is severe or not.
The cost forecasting of medical care for elderly residents’ fall-related injury goes to $43.8 billion by 2020 [1].
No doubt it would be a great burden to the national health insurance system.