TY - GEN
T1 - Screening of Non-overlapping Apnea and Non-apnea from Single Lead ECG-apnea Recordings using Time-Frequency Approach
AU - Fahruzi, Iman
AU - Ketut Eddy Purnama, I.
AU - Purnomo, Mauridhi H.
N1 - Publisher Copyright:
© 2019 IEEE.
PY - 2019/11
Y1 - 2019/11
N2 - This study focused on extracting to finding differences between apnea events and non-apnea events using time-frequency approach. This approach is of particular relevance to obtain the efficiency and accuracy of the support system for the classification model. Heart rate variability(HRV) was calculated using the statistic and frequency approach based on the time-frequency domain. The analysis of HRV, about the occurrence of the short recording, was performed selecting two segments: a class of apnea events and a class of non-apnea events. The experiment findings of the statistical analysis of our feature extraction showed time-domain feature estimation with Heart rate means (BPM) slightly higher for non-apnea events about mean ± standard deviation (72(±4)). The frequency-domain features, at VLF, LF and HF power of apnea events, are monitored over time with non-apnea events. The overall experiment indicates a significantly different feature value in the heart rate during examining apnea events and non-apnea events.
AB - This study focused on extracting to finding differences between apnea events and non-apnea events using time-frequency approach. This approach is of particular relevance to obtain the efficiency and accuracy of the support system for the classification model. Heart rate variability(HRV) was calculated using the statistic and frequency approach based on the time-frequency domain. The analysis of HRV, about the occurrence of the short recording, was performed selecting two segments: a class of apnea events and a class of non-apnea events. The experiment findings of the statistical analysis of our feature extraction showed time-domain feature estimation with Heart rate means (BPM) slightly higher for non-apnea events about mean ± standard deviation (72(±4)). The frequency-domain features, at VLF, LF and HF power of apnea events, are monitored over time with non-apnea events. The overall experiment indicates a significantly different feature value in the heart rate during examining apnea events and non-apnea events.
KW - apnea
KW - hrv
KW - non-apnea
KW - qrs complex
KW - spectrogram
UR - http://www.scopus.com/inward/record.url?scp=85082760382&partnerID=8YFLogxK
U2 - 10.1109/CENIM48368.2019.8973250
DO - 10.1109/CENIM48368.2019.8973250
M3 - Conference contribution
AN - SCOPUS:85082760382
T3 - 2019 International Conference on Computer Engineering, Network, and Intelligent Multimedia, CENIM 2019 - Proceeding
BT - 2019 International Conference on Computer Engineering, Network, and Intelligent Multimedia, CENIM 2019 - Proceeding
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2nd International Conference on Computer Engineering, Network, and Intelligent Multimedia, CENIM 2019
Y2 - 19 November 2019 through 20 November 2019
ER -