TY - GEN
T1 - Care-Chair
T2 - 2nd IEEE International Conference on Smart Computing, SMARTCOMP 2016
AU - Kumar, Rakesh
AU - Bayliff, Alec
AU - De, Debraj
AU - Evans, Adam
AU - Das, Sajal K.
AU - Makos, Mignon
N1 - Publisher Copyright:
© 2016 IEEE.
PY - 2016/6/28
Y1 - 2016/6/28
N2 - A large majority of population spend substantial amount of time each day in sedentary positions, which make the chairs potentially rich source of information and insight about people daily activities and behavior patterns. These information, which often gets under-utilized, can reveal valuable knowledge about the users's wellness level and quality of life. Considering this we have designed Care-Chair, a simple and cost effective smart sensing system with just four pressure sensors on the backrest of a chair, equipped with intelligent data analytics. Our proposed Care-Chair system has been able to classify among large number of 19 fine-grained and complex user sedentary activities. To best of our knowledge this is the first work to detect user functional activities and user emotion based activities (in addition to static and movement based sedentary activities and postures) with just 4 pressure sensors on chair and sensor data analytics. The performance is validated with 5 users combined dataset (thus considering user specific variations) with 86% overall accuracy. Our system is also validated to achieve precise measurement in user breathing rate during relatively static sedentary postures.
AB - A large majority of population spend substantial amount of time each day in sedentary positions, which make the chairs potentially rich source of information and insight about people daily activities and behavior patterns. These information, which often gets under-utilized, can reveal valuable knowledge about the users's wellness level and quality of life. Considering this we have designed Care-Chair, a simple and cost effective smart sensing system with just four pressure sensors on the backrest of a chair, equipped with intelligent data analytics. Our proposed Care-Chair system has been able to classify among large number of 19 fine-grained and complex user sedentary activities. To best of our knowledge this is the first work to detect user functional activities and user emotion based activities (in addition to static and movement based sedentary activities and postures) with just 4 pressure sensors on chair and sensor data analytics. The performance is validated with 5 users combined dataset (thus considering user specific variations) with 86% overall accuracy. Our system is also validated to achieve precise measurement in user breathing rate during relatively static sedentary postures.
UR - http://www.scopus.com/inward/record.url?scp=84979581513&partnerID=8YFLogxK
U2 - 10.1109/SMARTCOMP.2016.7501682
DO - 10.1109/SMARTCOMP.2016.7501682
M3 - Conference contribution
AN - SCOPUS:84979581513
T3 - 2016 IEEE International Conference on Smart Computing, SMARTCOMP 2016
BT - 2016 IEEE International Conference on Smart Computing, SMARTCOMP 2016
PB - Institute of Electrical and Electronics Engineers Inc.
Y2 - 18 May 2016 through 20 May 2016
ER -