A study of the influence of the sensor sampling frequency on the performance of wearable fall detectors

• Published in: Measurement : journal of the International Measurement Confederation Vol. 193; p. 110945
• Main Authors: Antonio Santoyo-Ramón, José, Casilari, Eduardo, Manuel Cano-García, José
• Format: Journal Article
• Language: English
• Published: London Elsevier Ltd 01.04.2022; Elsevier Science Ltd
• Subjects: Accelerometer; Artificial neural networks; Convolutional Neural Network; Dataset; Deep Learning; Detectors; Fall detection; Fall Detection Systems; Human Activity Recognition; Inertial Sensors; Neural networks; Power consumption; Sampling; Sampling Rate; Sensors; Wearable computers; Wearable technology; Convolutional Neural Network; Dataset; Accelerometer; Sampling Rate; Inertial Sensors; Fall Detection Systems; Human Activity Recognition; Deep Learning

•Impact of sampling frequency on wearable fall detection system (based on accelerometer signals) is normally neglected.•Sampling rate is normally arbitrarily chosen although it can heavily impact on the battery lifetime of the wearable.•The paper assesses the influence of the sampling rate on the ef...