This chapter presents an elderly fall-detection monitoring solution that implements both accelerometer and sound-based detection algorithm. The accelerometer-based fall detection is instrumental in the detection of a valid fall occurrence. However, it has been shown that using accelerometer alone is insufficient to accurately detect a fall, as the accelerometer tends to misinterpret some of the daily motion activities and misclassified them as valid falls. The sound sensor is introduced to detect the sound pressure generated from a resultant fall, but sound pressure cannot by itself be used as a reliable indicator of a fall. Thus a fuzzy logic–based fall-detection algorithm is developed to process the output signals from the accelerometer and sound sensor, where a valid fall activity detected by the accelerometer, coupled with a detected sound pressure from the resultant fall, can infer an occurrence of a valid fall. This chapter demonstrates the proposed algorithm is able to improve the accuracy of detecting a valid fall as compared to the accelerometer only fall-detection algorithm by minimizing false fall detections per day from high of 1.37 to low of 0.06.
Elsevier, Assistive Technology for the Elderly 2020, Pages 81-105