The use of wearable sensors is widely proposed in literature to assess human motion. Gait analysis methodology is supported by means of the use of inertial magnetic sensors (IMUs). In this work we propose an hybrid algorithm based on salience vector segmentation technique and a modified adaptive windowing search algorithm, to automatically detect gait events using a single triaxial accelerometer device. This method is tested on eight subject walking at self-selected speed. Accuracy and reliability level is assessed by comparing against baropodometric platform outcomes. Experimental results show the effectiveness and the accuracy of the proposed approach
An hybrid approach for automatic gait events detection using a triaxial accelerometer sensor
SGRO', FRANCESCO LUCIO;PALESI, MAURIZIO;LIPOMA, Mario
2014-01-01
Abstract
The use of wearable sensors is widely proposed in literature to assess human motion. Gait analysis methodology is supported by means of the use of inertial magnetic sensors (IMUs). In this work we propose an hybrid algorithm based on salience vector segmentation technique and a modified adaptive windowing search algorithm, to automatically detect gait events using a single triaxial accelerometer device. This method is tested on eight subject walking at self-selected speed. Accuracy and reliability level is assessed by comparing against baropodometric platform outcomes. Experimental results show the effectiveness and the accuracy of the proposed approachI documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
