TY - GEN
T1 - Challenges in Studying Falls of Community-Dwelling Older Adults in the Real World
AU - Hu, Xin
AU - Dor, Rahav
AU - Bosch, Steven
AU - Khoong, Anita
AU - Li, Jing
AU - Stark, Susan
AU - Lu, Chenyang
N1 - Publisher Copyright:
© 2017 IEEE.
PY - 2017/6/12
Y1 - 2017/6/12
N2 - Despite over a decade of research and development in fall detection systems, accurate and reliable systems in use are few. The existing fall detection approaches leave three major challenges unsolved: (1) insufficient fall data for model training process, (2) unreliable labeling of ground truth, and (3) resorting to artificial falls to model falls. In this paper we highlight these challenges in a clinical study with community-dwelling adults. The data collected from the real world reveal significant differences between artificial falls and actual falls, and also to illuminate the limitations of existing algorithms. We further make recommendations for future work, based on the challenges, experience, and lessons we learned from this study.
AB - Despite over a decade of research and development in fall detection systems, accurate and reliable systems in use are few. The existing fall detection approaches leave three major challenges unsolved: (1) insufficient fall data for model training process, (2) unreliable labeling of ground truth, and (3) resorting to artificial falls to model falls. In this paper we highlight these challenges in a clinical study with community-dwelling adults. The data collected from the real world reveal significant differences between artificial falls and actual falls, and also to illuminate the limitations of existing algorithms. We further make recommendations for future work, based on the challenges, experience, and lessons we learned from this study.
UR - http://www.scopus.com/inward/record.url?scp=85022344443&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85022344443&partnerID=8YFLogxK
U2 - 10.1109/SMARTCOMP.2017.7946993
DO - 10.1109/SMARTCOMP.2017.7946993
M3 - Conference contribution
AN - SCOPUS:85022344443
T3 - 2017 IEEE International Conference on Smart Computing, SMARTCOMP 2017
BT - 2017 IEEE International Conference on Smart Computing, SMARTCOMP 2017
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2017 IEEE International Conference on Smart Computing, SMARTCOMP 2017
Y2 - 29 May 2017 through 31 May 2017
ER -