TY - GEN
T1 - eCushion
T2 - 8th International Conference on Body Sensor Networks, BSN 2011
AU - Xu, Wenyao
AU - Li, Zhinan
AU - Huang, Ming Chun
AU - Amini, Navid
AU - Sarrafzadeh, Majid
PY - 2011
Y1 - 2011
N2 - Sitting posture analysis is critical for daily applications in biomedical, education and healthcare fields. However, it remains unclear how to monitor sitting posture economically and comfortably. To this end, we presented an eTextile device, called eCushion, in this paper, which can analyze the sitting posture of human being accurately and non-invasively. First, we discussed the implementation of eCushion and design challenges of sensing data, such as scale, offset, rotation and crosstalk. Then, several effective techniques have been proposed to improve the recognition rate of sitting posture. Our experimental results show that the recognition rate of our eCushion system could achieve 92% for object-oriented cases and 79% for general cases.
AB - Sitting posture analysis is critical for daily applications in biomedical, education and healthcare fields. However, it remains unclear how to monitor sitting posture economically and comfortably. To this end, we presented an eTextile device, called eCushion, in this paper, which can analyze the sitting posture of human being accurately and non-invasively. First, we discussed the implementation of eCushion and design challenges of sensing data, such as scale, offset, rotation and crosstalk. Then, several effective techniques have been proposed to improve the recognition rate of sitting posture. Our experimental results show that the recognition rate of our eCushion system could achieve 92% for object-oriented cases and 79% for general cases.
UR - https://www.scopus.com/pages/publications/80051991374
U2 - 10.1109/BSN.2011.24
DO - 10.1109/BSN.2011.24
M3 - Conference contribution
AN - SCOPUS:80051991374
SN - 9780769544311
T3 - Proceedings - 2011 International Conference on Body Sensor Networks, BSN 2011
SP - 194
EP - 199
BT - Proceedings - 2011 International Conference on Body Sensor Networks, BSN 2011
Y2 - 23 May 2011 through 25 May 2011
ER -