TY - GEN
T1 - ICA for separation of respiratory motion and heart motion from chest surface motion
AU - Shafiq, Ghufran
AU - Wang, Yubo
AU - Tatinati, Sivanagaraja
AU - Veluvolu, Kalyana C.
PY - 2013
Y1 - 2013
N2 - Chest surface movement contains information of respiration and heart activity which are considered vital parameters. However, it is important to separate respiratory and cardiac information in order to perform further analysis. For this purpose, Independent Component Analysis (ICA) was applied to multiple simultaneously recorded chest surface movement signals. Successful separation of cardiac pattern is demonstrated and compared with ECG. This methodology can be used to further develop non-obtrusive ways to monitor vital physiological parameters in the form of wearable sensors.
AB - Chest surface movement contains information of respiration and heart activity which are considered vital parameters. However, it is important to separate respiratory and cardiac information in order to perform further analysis. For this purpose, Independent Component Analysis (ICA) was applied to multiple simultaneously recorded chest surface movement signals. Successful separation of cardiac pattern is demonstrated and compared with ECG. This methodology can be used to further develop non-obtrusive ways to monitor vital physiological parameters in the form of wearable sensors.
KW - Cardiography
KW - ICA
KW - Respiration motion
KW - Vital parameters
UR - https://www.scopus.com/pages/publications/84893359739
U2 - 10.1007/978-3-642-42051-1_73
DO - 10.1007/978-3-642-42051-1_73
M3 - Conference contribution
AN - SCOPUS:84893359739
SN - 9783642420504
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 592
EP - 599
BT - Neural Information Processing - 20th International Conference, ICONIP 2013, Proceedings
T2 - 20th International Conference on Neural Information Processing, ICONIP 2013
Y2 - 3 November 2013 through 7 November 2013
ER -