TY - GEN
T1 - Extracting features for cardiovascular disease classification based on ballistocardiography
AU - Song, Yalong
AU - Ni, Hongbo
AU - Zhou, Xingshe
AU - Zhao, Weichao
AU - Wang, Tianben
N1 - Publisher Copyright:
© 2015 IEEE.
PY - 2016/7/20
Y1 - 2016/7/20
N2 - Cardiovascular disease affects the health of people seriously in the world, especially in the elderly. This paper proposes an effective approach of detecting and analyzing the health status of the elderly. In this work, we continuously acquire Ballisto cardiography (BCG) signal with the micro-movement sensitive mattress (MSM) during non-intrusive sleep in home environment. In the paper, we propose a new method to extract heartbeat intervals (RR) based on Ensemble Empirical Mode Decomposition (EEMD), and extract the signal features by calculating the parameters of heart rate variability (HRV) from time domain analysis, frequency domain analysis and nonlinear analysis. A Naïve Bayesian Classification method is applied to classify the normal persons, hypertension patients and coronary heart disease (CHD) patients by using the obtained features. The proposed method is evaluated by using the BCG datasets from eighteen subjects, including eight females and ten males (age 40-72). The results are satisfactory and can provide a classification precision of 92.3%.
AB - Cardiovascular disease affects the health of people seriously in the world, especially in the elderly. This paper proposes an effective approach of detecting and analyzing the health status of the elderly. In this work, we continuously acquire Ballisto cardiography (BCG) signal with the micro-movement sensitive mattress (MSM) during non-intrusive sleep in home environment. In the paper, we propose a new method to extract heartbeat intervals (RR) based on Ensemble Empirical Mode Decomposition (EEMD), and extract the signal features by calculating the parameters of heart rate variability (HRV) from time domain analysis, frequency domain analysis and nonlinear analysis. A Naïve Bayesian Classification method is applied to classify the normal persons, hypertension patients and coronary heart disease (CHD) patients by using the obtained features. The proposed method is evaluated by using the BCG datasets from eighteen subjects, including eight females and ten males (age 40-72). The results are satisfactory and can provide a classification precision of 92.3%.
KW - Ballistocardiography
KW - Cardiovascular Disease
KW - EEMD
KW - Naïve Bayesian Classification
UR - http://www.scopus.com/inward/record.url?scp=84983416412&partnerID=8YFLogxK
U2 - 10.1109/UIC-ATC-ScalCom-CBDCom-IoP.2015.223
DO - 10.1109/UIC-ATC-ScalCom-CBDCom-IoP.2015.223
M3 - 会议稿件
AN - SCOPUS:84983416412
T3 - Proceedings - 2015 IEEE 12th International Conference on Ubiquitous Intelligence and Computing, 2015 IEEE 12th International Conference on Advanced and Trusted Computing, 2015 IEEE 15th International Conference on Scalable Computing and Communications, 2015 IEEE International Conference on Cloud and Big Data Computing, 2015 IEEE International Conference on Internet of People and Associated Symposia/Workshops, UIC-ATC-ScalCom-CBDCom-IoP 2015
SP - 1230
EP - 1235
BT - Proceedings - 2015 IEEE 12th International Conference on Ubiquitous Intelligence and Computing, 2015 IEEE 12th International Conference on Advanced and Trusted Computing, 2015 IEEE 15th International Conference on Scalable Computing and Communications, 2015 IEEE International Conference on Cloud and Big Data Computing, 2015 IEEE International Conference on Internet of People and Associated Symposia/Workshops, UIC-ATC-ScalCom-CBDCom-IoP 2015
A2 - Ma, Jianhua
A2 - Li, Ali
A2 - Ning, Huansheng
A2 - Yang, Laurence T.
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - Proceedings - 2015 IEEE 12th International Conference on Ubiquitous Intelligence and Computing, 2015 IEEE 12th International Conference on Advanced and Trusted Computing, 2015 IEEE 15th International Conference on Scalable Computing and Communications, 2015 IEEE International Conference on Cloud and Big Data Computing, 2015 IEEE International Conference on Internet of People and Associated Symposia/Workshops, UIC-ATC-ScalCom-CBDCom-IoP 2015
Y2 - 10 August 2015 through 14 August 2015
ER -
