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All Journal Jurnal ELTIKOM : Jurnal Teknik Elektro, Teknologi Informasi dan Komputer Journal of Electronics, Electromedical Engineering, and Medical Informatics
Sofyan, Pramudya Rakhmadyansyah
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Aerospace Engineering Computer Science & IT Control & Systems Engineering Electrical & Electronics Engineering Engineering

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Time Segment Analysis of Heart Rate Variability to Evaluate Daily Stress using Wearable Device Technology Sahroni, Alvin; Sofyan, Pramudya Rakhmadyansyah
Jurnal ELTIKOM : Jurnal Teknik Elektro, Teknologi Informasi dan Komputer Vol. 7 No. 2 (2023)
Publisher : P3M Politeknik Negeri Banjarmasin

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31961/eltikom.v7i2.747

Abstract

Present studies have successfully evaluated psychological properties such as mental health and stress by using physiological data from the cardiovascular system. Most studies established specific interventions and ambiguous heart rate properties according to homeostatic conditions. We proposed a study evaluating mental stress based on daily activities dataset. Twenty-two healthy men were observed in this study. We employed two approaches based on the time segments, while extracting the HRV parameters. We discovered that there was no significant difference between the parameters corresponding to the daily stress score groups (low- and high-stress) when we used whole-day recording in one segment HRV parameter measurement (p > 0.05). However, by extracting the HRV parameters based on multi time segments (phases 1, 2, and 3), we found parameters that were able to properly distinguish the two groups (low- and high-stress). The frequency domain parameters are the most sensitive features, especially the LF and HF (p < 0.01), followed by the total power (p < 0.05). In the time domain measurement, the RMSSD, StdHR, SD1, and SD2 are able to differentiate the participants based on the daily stress scores (p < 0.05). As a result, this study proposed that by continually monitoring biological signals based on time segment and employing the given parameters, it is possible to appropriately and meaningfully measure the daily stress condition for future classification studies.
Single Channel Electrogastrogram Frequency Domain Analysis and Correspondence to Brain Activity in a Resting State Condition Sahroni, Alvin; Miladiyah, Isnatin; Adinandra, Sisdarmanto; Sofyan, Pramudya Rakhmadyansyah; Anora, Levina; Hanafi, Mhd.
Journal of Electronics, Electromedical Engineering, and Medical Informatics Vol 7 No 1 (2025): January
Publisher : Department of Electromedical Engineering, POLTEKKES KEMENKES SURABAYA

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35882/jeeemi.v7i1.590

Abstract

An electrogastrogram (EGG) is a well-known method to record gastric myoelectrical activity. However, some researchers believe that EGG measures the gastric slow wave and can be used as a surrogate for gastric motility, whereas others claim that EGG is flawed. Our proposed study broadens the scope of EGG research, particularly by offering the opportunity to observe gut-brain signaling pathways, which can enhance our understanding of brain properties and behavior in response to psychological changes. This study focuses on how to confirm single-channel EGG's setup with public datasets and previous studies and how to observe the relationship of gut-brain axis pathways. We gathered four subjects utilizing a 250 Hz bioamp to monitor brain wave activity on the head and scalp including gastric activity, and used Zenodo's EGG dataset for the confirmation phase. We placed single-channel electrodes around the stomach to investigate gastric myoelectrical activity and extracted the EGG's power spectrum using a specific band-pass filter (0.03 - 0.07 Hz). We extracted the EGG's power spectrum and dominant frequency as our main features. Regarding brain electricity activities, we applied the FIR filter to obtain each brain wave's properties. We found that each subject had different responses during pre- and postprandial, both from primary and secondary resources. We found that the increase in EGG activity caused a change in EEG properties, particularly in the alpha band (8-12 Hz). Additionally, the EEG P3 site in the parietal lobe followed the power change rates of the EGG between 0 to 0.015 of relative power. We conclude that P3 and slow-wave gastric movement from EGG correspond to each other and reflect gut-brain axis pathways. However, future studies with larger samples must strengthen our findings according to the gut-brain axis pathways in the P3 site and EGG
Co-Authors Alvin Sahroni Anora, Levina Hanafi, Mhd. Isnatin Miladiyah Sisdarmanto Adinandra, Sisdarmanto