TY - GEN
T1 - Adaptive filtering for respiration influence reduction on Heart Rate Variability
AU - Cassani, Raymundo
AU - Mejia, Patricia
AU - Antonio Tavares, Jose
AU - Sanchez, Juan Carlos
AU - Martinez, Raul
PY - 2011
Y1 - 2011
N2 - In this paper it is described an adaptive method for Heart Rate Variability (HRV) signal filtering, which uses a noise canceller structure formed by a Finite Impulse Response (FIR) filter together with the Least Mean Squares (LMS) adaptation algorithm in order to reduce respiration influence on HRV information. Respiration and electrocardiogram (ECG) signals were obtained simultaneously using 240Hz sampling frequency during 5-minutes experiments. Respiration signal was acquired by mechanic methods whereas ECG signal was obtained using one lead electrocardiograph. After data acquisition, a tachogram was derived from ECG measurement in order to obtain the HRV signal; then Adaptive Noise Cancelling (ANC) filtering was applied, reducing artifacts due to respiration from HRV signal. This method was evaluated for spontaneous and controlled respiration frequency by comparing results from the Power Spectral Density (PSD) of HRV signal before and after filtering. At the results, it is observed that frequency components related to respiration are cancelled in the HRVs PSD, reaching an appropriate estimation of the control exerted by the Autonomic Nervous System (ANS) in the cardiac activity.
AB - In this paper it is described an adaptive method for Heart Rate Variability (HRV) signal filtering, which uses a noise canceller structure formed by a Finite Impulse Response (FIR) filter together with the Least Mean Squares (LMS) adaptation algorithm in order to reduce respiration influence on HRV information. Respiration and electrocardiogram (ECG) signals were obtained simultaneously using 240Hz sampling frequency during 5-minutes experiments. Respiration signal was acquired by mechanic methods whereas ECG signal was obtained using one lead electrocardiograph. After data acquisition, a tachogram was derived from ECG measurement in order to obtain the HRV signal; then Adaptive Noise Cancelling (ANC) filtering was applied, reducing artifacts due to respiration from HRV signal. This method was evaluated for spontaneous and controlled respiration frequency by comparing results from the Power Spectral Density (PSD) of HRV signal before and after filtering. At the results, it is observed that frequency components related to respiration are cancelled in the HRVs PSD, reaching an appropriate estimation of the control exerted by the Autonomic Nervous System (ANS) in the cardiac activity.
KW - Adaptive Filtering
KW - Adaptive Noise Canceller
KW - ECG
KW - HRV
KW - RSA
KW - Respiration
UR - http://www.scopus.com/inward/record.url?scp=84855803681&partnerID=8YFLogxK
U2 - 10.1109/ICEEE.2011.6106707
DO - 10.1109/ICEEE.2011.6106707
M3 - Contribución a la conferencia
AN - SCOPUS:84855803681
SN - 9781457710117
T3 - CCE 2011 - 2011 8th International Conference on Electrical Engineering, Computing Science and Automatic Control, Program and Abstract Book
BT - CCE 2011 - 2011 8th International Conference on Electrical Engineering, Computing Science and Automatic Control, Program and Abstract Book
T2 - 2011 8th International Conference on Electrical Engineering, Computing Science and Automatic Control, CCE 2011
Y2 - 26 October 2011 through 28 October 2011
ER -