This paper presents the new design and development of a wearable-based fall detection system using an Accelerometer and Gyroscope as motion sensors for detecting body orientation and movement. The Threshold Based and Artificial Neural Networks (ANN) algorithm were developed to differentiate between Activities of Daily Living (ADL). Results indicated the possibility of using the new threshold-based method with ANN algorithm to reduce the number of false positive (false alarm) outcomes and improve the accuracy of fall detection system.
