Heart Rate Variability Analysis by Multiscale Entropy for Autonomic Nervous System Identification
| Autor: | Toshitaka Yamakawa, Mahendrawathi Er, Faizal Mahananto, Afifah Nurrosyidah, Tomohiko Igasaki |
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| Rok vydání: | 2019 |
| Předmět: |
Heartbeat
business.industry Computer science 020206 networking & telecommunications Pattern recognition 02 engineering and technology body regions Identification (information) Autonomic nervous system Frequency domain Heart rate 0202 electrical engineering electronic engineering information engineering General Earth and Planetary Sciences Heart rate variability 020201 artificial intelligence & image processing Time domain Artificial intelligence business General Environmental Science |
| Zdroj: | Procedia Computer Science. 161:630-637 |
| ISSN: | 1877-0509 |
| DOI: | 10.1016/j.procs.2019.11.166 |
| Popis: | Information technology in the medical field has a role in improving patient treatment quality by tracking patient condition in real time using heart rate variability (HRV). There is a correlation between HRV and autonomic nervous system (ANS), where HRV analysis can be used in an invasive way for monitoring ANS activity. There are many analytical methods related to cardiac autonomic modulation, for instance, time domain, frequency domain, and nonlinear analyses. The previous study has been using PUCK as a new index to evaluate the ANS activity and MSE for analysis of cardiovascular disease. However, the indication of PUCK showed another possibility of the cardiac modulation. Therefore, the objective of this research is to know the relation between MSE with ANS activity from several physical activities using treadmill exercise. An accurate control of heartbeat interval during exercise is measured using wearable electrocardiograph to get high precision. MSE analysis may provide to detect several cardiovascular diseases. The information related to the entanglement of the ANS of the heart rate using MSE is lacking, even though the MSE method in the clinical analysis is widely accepted. As a result, MSE in the large scales tend to decrease following the change of posture and the increasing of speed during treadmill exercise. The present study shows that MSE could indicate the activity of ANS in the large scales for the parasympathetic system activity. Further research is needed to know the specific parameters in the MSE method to get the results that can quantify ANS activity correctly. |
| Databáze: | OpenAIRE |
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