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Journal : Journal of Biomedical Science and Bioengineering

Heart Rate Variability Analysis and The Influence of Exercise Intensity Over Time in Young-healthy Women Aisha Widi Rahayu; Izza Alifa Hassya; Eki Dipo Laksono; Alvin Sahroni
Journal of Biomedical Science and Bioengineering Vol 1, No 1 (2021)
Publisher : Center for Biomechanics, Biomaterials, Biomechantronics and Biosignal Processing (CBOIM3S)

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (487.755 KB) | DOI: 10.14710/jbiomes.2021.v1i1.1-6

Abstract

Our heart is a vital organ that pumps blood and through the vessels of the circulatory system. In medical applications, we can observe the heart rate using Electrocardiograph (ECG). Currently, people tend to have high working activity without a proper exercise intensity. This study was conducted to observe the heart rate variability (HRV) on the healthy young woman who was not doing any exercise. We evaluated the HRV characteristics while exercising with a regular period and different intensity (light to hard) and how the difference before and after of evaluation period. Seven young-healthy women (19 - 21 years old) women were observed during three observation stages: pre-exercise, main exercise-period, and post-exercise for 2 months. We analyzed MeanRR, SDRR, CVRR, rMSSD, VLF, LF, HF, and the Poincaré plot parameters (SD1 and SD2) as the HRV properties. We found that SDRR was decreased from the first week (0.08 s) to the last week of the evaluation period (0.03 s) followed by the HF component (0.15 – 0.2 Hz). The Poincaré plot properties also reduced from the first week to the last week of the exercise period (0.07 s to 0.03 s). We indicated the characteristics of a woman's HRV during regular exercise periods with different intensity have made the heart more effective in pumping blood. We concluded that the heart condition would be improved during regular exercise with the increment of intensity even in a short of a period. Finally, the heart rate performance may be decreased during absent from regular exercise for a month.
Multiparameter Biosignal Analysis in Elderly Ischemic Stroke Patients Muhammad Zakariyah; Alvin Sahroni; Erlina Marfianti
Journal of Biomedical Science and Bioengineering Vol 1, No 1 (2021)
Publisher : Center for Biomechanics, Biomaterials, Biomechantronics and Biosignal Processing (CBOIM3S)

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (414.068 KB) | DOI: 10.14710/jbiomes.2021.v1i1.7-16

Abstract

Biosignal can provide information about body conditions, including physiological conditions of ischemic stroke. The regulation of blood in the brain is regulated through the mechanism of Cerebral Autoregulation (CA). Some parameters that can be used to determine this mechanism are Blood Flow Velocity (BFV) and Blood Pressure (BP). Stroke is also related to nervous system activity, which is represented through the Heart Rate Variability (HRV). This study aims to determine the relationship between those biosignals and their effects on the physiology of ischemic stroke sufferers. The subjects were divided into two groups (20 strokes and 20 controls). BFV data is obtained in the Middle Cerebral Artery (MCA), BP is obtained through the arteries of the upper arms, and 3 leads electrocardiogram is placed in the chest. The results showed that there was a relationship between BP and BFV in the control group (p-value < 0.05; r = -0.574). This correlation was not found in the stroke group. The relationship between BP and HRV was only found in the stroke group, which was associated with high sympathetic activity and lower parasympathetic activity (p-values < 0.05 and r > 0.4). It was based on SDRR, RMSSD, CVRR, LF, and SD1 parameters. In the control group, there was no relationship between HRV and BP. The relationship between BFV and HRV in the control group was not found statistically. Still, in the stroke group, this relationship was found in the LF and LF/HF Ratio parameters (p-value < 0.05; r > 0.4). Based on this research, parameters on HRV that can be used to determine the characteristics of stroke patients in all positions are MeanRR, VLF, and LF