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All Journal International Journal of Electrical and Computer Engineering Proceeding of the Electrical Engineering Computer Science and Informatics
Bagus Haryadi
Universitas Ahmad Dahlan
Computer Science & IT Electrical & Electronics Engineering

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Poincaré plots to analyze photoplethysmography signal between non-smokers and smokers Bagus Haryadi; Po-Hao Chang; Akrom Akrom; Arifan Q. Raharjo; Galih Prakoso
International Journal of Electrical and Computer Engineering (IJECE) Vol 12, No 2: April 2022
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v12i2.pp1565-1570

Abstract

An analysis of blood circulation was used to identify variations of heart rate and to create an early warning system of autonomic dysfunction. The Poincaré plot analyzed blood circulation using photoplethysmography (PPG) signals between non-smokers and smokers in three different indices: SD1, SD2, and SD1 SD2 ratio (SSR). There were twenty subjects separated into non-smoker and smoker groups with sample sizes of 10, respectively. An independent sample t-test to compare the continuous variables. Whereas, the comparison between two groups employed Fisher’s exact test for categorical variables. The result showed that SD1 was found to be considerably lower in the group of smokers (0.03±0.01) than that of the non-smokers (0.06±0.03). Similarly, SSR was recorded at 0.0012±0.0005 and 0.0023±0.0012 for smoking and non-smoking subjects, respectively. As a comparison, SD2 for non-smokers (25.7±0.5) was lower than smokers (27.3±0.4). In conclusion, we revealed that the parameters of Poincaré plots (SD1, SD2, and SSR) exert good performances to significantly differentiate the PPG signals of the group of non-smokers from those of smokers. We also supposed that the method promises to be a suitable method to distinguish the cardiovascular disease group. Therefore, this method can be applied as a part of early detection system of cardiovascular diseases.
Poincaré Plot of Fingertip Photoplethysmogram Pulse Amplitude Suitable to Assess Diabetes Status Bagus Haryadi; Gen-Min Lin; Chieh-Ming Yang; Shiao-Chiang Chu; Hsien-Tsai Wu
Proceeding of the Electrical Engineering Computer Science and Informatics Vol 4: EECSI 2017
Publisher : IAES Indonesia Section

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (327.951 KB) | DOI: 10.11591/eecsi.v4.1004

Abstract

Multiscale entropy (MSE), an estimate of the complexity of physiological signals has been used for assessing diabetes status. This method requires much computation effort. Our study aimed to examine the Poincaré plot, an easier method for computation to differentiate the diabetes status. We selected subjects and divided them into three groups including the non- diabetes (HbA1c ≤ 6.5%, n=22), diabetes with good control (6.5% < HbA1c < 8%, n=23), and diabetes with poor control (HbA1c ≥ 8%, n=17). Poincaré method used consecutive 250 data points of PPG pulse amplitudes from each subject’s right index fingertip. This method resulted in SSR, the standard deviation of the original photoplethysmogram (PPG) pulse amplitude (SD1) and the standard deviation of the interval 1 PPG pulse amplitude (SD2) ratio. The SSR in the three groups of non-diabetes, diabetes with good control and diabetes with poor control were 0.50, 0.28, and 0.23, respectively and differed between groups (P < 0.05).  Our findings suggested that the Poincaré plot of right-hand PPG pulse amplitude may be convenient to evaluate diabetes status.
Co-Authors Akrom, Akrom Arifan Q. Raharjo Chieh-Ming Yang Chu, Shiao-Chiang Galih Prakoso Gen-Min Lin Hsien-Tsai Wu Lin, Gen-Min Po-Hao Chang Shiao-Chiang Chu Wu, Hsien-Tsai Yang, Chieh-Ming