A threshold-based algorithm, to distinguish between Activities of Daily Living (ADL) and falls
is described. A gyroscope based fall-detection sensor array is used. Using simulated-falls
performed by young volunteers under supervised conditions onto crash mats and ADL
performed by elderly subjects, the ability to discriminate between falls and ADL was
achieved using a bi-axial gyroscope sensor mounted on the trunk, measuring pitch and roll
angular velocities, and a threshold-based algorithm. Data analysis was performed using …

Using simulated falls performed under supervised conditions and activities of daily living
(ADL) performed by elderly subjects, the ability to discriminate between falls and ADL was
investigated using tri-axial accelerometer sensors, mounted on the trunk and thigh. Data
analysis was performed using MATLAB to determine the peak accelerations recorded during
eight different types of falls. These included; forward falls, backward falls and lateral falls left
and right, performed with legs straight and flexed. Falls detection algorithms were devised …