• ETRI Journal
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• v.43 no.5
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• pp.881-890
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• 2021

Photoplethysmography (PPG) is a noninvasive technique that can be used to conveniently measure heart rate (HR) and thus obtain relevant health-related information. However, developing an automated PPG system is difficult, because its waveforms are susceptible to motion artifacts and between-patient variation, making its interpretation difficult. We use deep neural network (DNN) filters to mimic the cognitive ability of a human expert who can distinguish the features of PPG altered by noise from various sources. Systolic (S), onset (O), and first derivative peaks (W) are recognized by three different DNN filters. In addition, the boundaries of uninformative regions caused by artifacts are identified by two different filters. The algorithm reliably derives the HR and presents recognition scores for the S, O, and W peaks and artifacts with only a 0.7-s delay. In the evaluation using data from 11 patients obtained from PhysioNet, the algorithm yields 8643 (86.12%) reliable HR measurements from a total of 10 036 heartbeats, including some with uninformative data resulting from arrhythmias and artifacts.

• Journal of Biomedical Engineering Research
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• v.31 no.4
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• pp.328-334
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• 2010

Over the past few years, a considerable number of methods have been proposed and applied for the classification of photoplethysmography (PPG). Most of the previous studies, however, focused on the qualitative description of the pulse type according to specific disease and thus provided ambiguous criteria to interpreters. In order to screen out this problem, we present a quantitative method for the pulse type classification including the second derivative of photoplethysmography (SDPTG). In the PPG signal, we have classified the signal as 4 types using the position and the presence of the dicrotic wave. In addition, we have categorized the SDPTG signal as 7 types using the position and the presence of "c" and "d" wave and the sign of "c" wave. In order to check the efficacy of the proposed pulse type classification rule, we collected pulse signals from 155 subjects with different ages and sex. From the correlation analysis, Class 1(p<0.01) and Class 2(p<0.01) in the PPG signal are significantly correlated with ages. In a similar manner Class A(p<0.01), Class C(p<0.05), Class D(p<0.01), and Class F(p<0.01) in the SDPTG signal are considerably correlated with the ages. From these observations, and some earlier ones [4], [5], we can conclude that since the newly proposed method has objectivity and clarity in pulse type classification, this method can be used as an alternative of previous classification rules including similar age-related characteristics.

• Journal of Biomedical Engineering Research
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• v.32 no.2
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• pp.109-117
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• 2011

Assuming that photons absorbed by a vessel do not have acute variations, DC component reflect the basal blood volume (or diameter) before blood pulsation. Vascular stiffness and reflection is influenced by changes in basal blood volume (or diameter). This paper describes analysis of the characteristic variations of vascular stiffness, according to relative variations in DC components of the PPG signal (25-75%). For quantitative analysis, we have used parameters that were proposed previously, reflection and stiffness index, and the second derivative of PPG waveform, b/a and d/a. Significantly, the vascular stiffness and reflections were increased according to increase in DC component of the PPG signal for more than about 3% of baseline values. The systolic blood pressure were increased from $113.1{\times}13.18$ to $116.2{\times}13.319$ mmHg, about 2.76% (r = 0.991, P < 0.001) and the AC component of the PPG signal were decreased from $2.073{\times}2.287$ to $1.973{\times}2.2038$ arbitrary unit, about 5.09% (r = -0.993, P < 0.001). It is separated by DC median and correlation analysis was performed for analyzing vascular characteristics according to instantaneous DC variations. There are significant differences between two correlation coefficients in separated data.

• Journal of Magnetics
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• v.15 no.4
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• pp.209-212
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• 2010

Photoplethysmogram (PPG) and pressure pulse waveform (PPW) were compared and evaluated for the efficacy of stimulating knuckles by using the pulsed magnetic field. Both signals were observed simultaneously while the knuckles were exposed for 10 min to the pulsed magnetic field, with maximum field intensity of 0.8 T and transition time of 0.126 msec. After 5 min stimulation of the knuckles, the results showed that the aging indexes calculated from the second derivative of the PPG were increased from -1.913 to 0.072, and that of the PPW from -0.063 to 0.387. However, for the relatively long-term stimulation for 10 min, we found that the values of both the aging indexes of the second derivatives and augmentation index of the PPW returned to the starting level. The changes observed in characteristic factors such as the aging indexes of the second derivatives and augmentation index of the PPW indicate the potential of pulsed magnetic field stimulation as a therapeutic method for the treatment of patients with peripheral vascular disease.

• Proceedings of the KIEE Conference
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• 2008.04a
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• pp.125-126
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• 2008

현재, 우리나라 당뇨병의 유병률은 빠른 속도로 증가하고 있으며 당뇨병의 유병기간이 길수록 각종 합병증이 발생하며 더욱 심각한 증세를 나타내기도 한다. 그 중, 비만 및 고혈당, 당대사장애로 인한 당뇨병성 혈관 합병증과 말초 혈관 경화증이 많이 발병하고 있는 실정이다. 본 연구에서는 광혈류량 측정법(Photoplethysmograaphy)으로 손가락에서 얻어진 맥파의 2차 미분 분석을 통해 당뇨병으로 확진된 36명의 당뇨병 환자에 대해 말초혈관 경화도를 연령별로 비교하고자 하였다. 이때 사용한 PPG 파형의 2차 미분 분석 평가 인자는 a와 d이고, d/a는 혈관의 경화도를 의미하며 경화도가 클수록 d/a의 값은 감소하게 되고, 연령이 증가할수록 경화도는 증가하게 된다. 50대 미만의 당뇨병 환자의 d/a값은 $-0.32{\pm}0.12$, 50대는 $-0.48{\pm}0.13$, 60대는 $-0.55{\pm}0.16$, 70대 이상에서는 $-0.59{\pm}0.19$로 연령이 높아질수록 d/a값이 감소하는 것을 확인하였다. 또한, SPSS 13.0 for Windows(SPSS Inc, USA)의 Oneway ANOVA 분석 결과, 연령과 경화도는 통계적으로 유의한 차이를 보였다(p<0.05). 하지만 70대 이상의 당뇨병 환자 그룹에서는 유의한 차이를 확인할 수 없었다. 본 연구에서는 PPG 파형의 2차 미분 분석을 통하여 연령별 당뇨병 환자의 말초혈판 경화도를 비교하였으며, 향후 보완 연구를 통해 비침습적이고 간단한 방법으로 당뇨병 환자의 말초혈관 경화도를 객관적으로 평가하고 진단할 수 있는 시스템 개발로 당뇨병 환자들의 심혈관계질환 사전예방과 치료효과 판정에 도움을 줄 것으로 기대한다.