TY - JOUR
T1 - Sensor Technologies for Fall Detection Systems
T2 - A Review
AU - Singh, Anuradha
AU - Rehman, Saeed Ur
AU - Yongchareon, Sira
AU - Chong, Peter Han Joo
PY - 2020/7/1
Y1 - 2020/7/1
N2 - The risk of falls in older adults restrict their social life and independent living. The assisted living devices help older adults to live independently in their home, giving a psychological boost, and releasing the burden on the caregiver and the healthcare providers. A robust and accurate fall detection system is essential to provide immediate help and to reduce the severe post-fall consequences, and the associated medical care cost significantly. This review aims to provide a comprehensive technical insight into the existing fall detection system, to classify various approaches and the challenges encountered during implementation. The fall detectors are broadly classified into three categories, namely wearable, ambiance-based, and hybrid sensing detectors, which are further explored by the sensor technology. This review provides a comprehensive overview of each competing sensor technology ranging from an accelerometer, pressure sensor, and radar to camera-based and their infusion into a complete fall detection system. It outlines the strength and limitations of different sensor fall detection systems in terms of feature extraction, classification, performance, and experimental dataset. The user adaptability, installation complexity, and power requirement of the systems are the main areas, which are not addressed adequately in the literature. In the end, the review provides a basic framework in deciding the technology for a specific scenario or location according to the prerequisites for the deployment.
AB - The risk of falls in older adults restrict their social life and independent living. The assisted living devices help older adults to live independently in their home, giving a psychological boost, and releasing the burden on the caregiver and the healthcare providers. A robust and accurate fall detection system is essential to provide immediate help and to reduce the severe post-fall consequences, and the associated medical care cost significantly. This review aims to provide a comprehensive technical insight into the existing fall detection system, to classify various approaches and the challenges encountered during implementation. The fall detectors are broadly classified into three categories, namely wearable, ambiance-based, and hybrid sensing detectors, which are further explored by the sensor technology. This review provides a comprehensive overview of each competing sensor technology ranging from an accelerometer, pressure sensor, and radar to camera-based and their infusion into a complete fall detection system. It outlines the strength and limitations of different sensor fall detection systems in terms of feature extraction, classification, performance, and experimental dataset. The user adaptability, installation complexity, and power requirement of the systems are the main areas, which are not addressed adequately in the literature. In the end, the review provides a basic framework in deciding the technology for a specific scenario or location according to the prerequisites for the deployment.
KW - Assisted living
KW - elderly assisted living
KW - fall detection
KW - sensor technology
KW - smart homes
KW - wearable sensor
UR - http://www.scopus.com/inward/record.url?scp=85086247932&partnerID=8YFLogxK
U2 - 10.1109/JSEN.2020.2976554
DO - 10.1109/JSEN.2020.2976554
M3 - Review article
AN - SCOPUS:85086247932
SN - 1530-437X
VL - 20
SP - 6889
EP - 6919
JO - IEEE Sensors Journal
JF - IEEE Sensors Journal
IS - 13
ER -