A wearable sit-to-stand detection system based on angle tracking and lower limb EMG

Sit-to-stand (STS) failures represent one type of fall accidents caused by loss of balance on senior citizens when they are trying to make body movement from sitting to standing. For effective detection of STS failures, a wearable STS detection system was proposed and developed in this study, based on the combination of the angle change data collected from people's upper trunk and the electromyography (EMG) data acquired from quadriceps. The developed STS detection system will raise an alarm when the user (such as elderly people or people with disabilities) tries to stand up or at least intend to stand up without proper care or necessary assistance. In such a case, the caregiver will be promptly notified and can come to provide necessary assistance to the user before STS failure happens. Experimental results showed that the developed system can work successfully on different human subjects with the FAR (false accept rate) and FRR (false reject rate) below 5%. It has been demonstrated that the proposed approach holds the advantages in terms of early alarms (i.e., reported at early stage of STS procedure), accurate detection, low false alarm rate, low cost, as well as ease-of-use, all of which have made the proposed system suitable for being adopted and integrated in other pervasive healthcare applications.