• Journal of Electrical Engineering and Technology
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• v.13 no.5
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• pp.2080-2085
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• 2018

There have been numerous studies that extract the R-peak from electrocardiogram (ECG) signals. All of these studies can extract R-peak from ECG. However, these methods are complicated and difficult to implement in a real-time portable ECG device. After filtration choosing a threshold value for R-peak detection is a big challenge. Fixed threshold scheme is sometimes unable to detect low R-peak value and adaptive threshold sometime detect wrong R-peak for more adaptation. In this paper, a simple and robustness algorithm is proposed to detect R-peak with less complexity. This method also solves the problem of threshold value selection. Using the adaptive filter, the baseline drift can be removed from ECG signal. After filtration, an appropriate threshold value is automatically chosen by using the minimum and maximum value of an ECG signals. Then the neighborhood searching scheme is applied under threshold value to detect R-peak from ECG signals. Proposed method improves the detection and accuracy rate of R-peak detection. After R-peak detection, we calculate heart rate to know the heart condition.

• Journal of Industrial Convergence
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• v.20 no.10
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• pp.209-218
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• 2022

Individuals often report significant relief from pain and stress even after a single session of massage therapy; however, no previous studies have provided objective evidence supporting the effectiveness of a solitary massage therapy session. In the present study, we aimed to investigate the effectiveness of one-time treatment with a spinal thermal massage device reported to exert the same therapeutic effects as massage therapy in terms of pain reduction and stress relief. A man with chronic low back pain (LBP) underwent two rounds of experiments involving spinal massage treatment and bed rest, respectively. Pain was assessed using a visual analog scale, and heart rate variability (HRV) was measured in real-time to examine autonomic nervous system (ANS) activity. Blood samples were obtained at five points during each round of the experiment to examine changes in cortisol, epinephrine, and norepinephrine. Spinal massage significantly reduced pain and enhanced parasympathetic activity when compared with the bed rest condition. In addition, both epinephrine and norepinephrine levels were lower following spinal massage than following bed rest. These results are consistent with the reported effects of conventional massage therapy and support the effectiveness of one-time treatment using a spinal thermal massage device.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.18 no.12
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• pp.126-134
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• 2017

There have been numerous studies on extracting the R-peak from electrocardiogram (ECG) signals. However, most of the detection methods are complicated to implement in a real-time portable electrocardiograph device and have the disadvantage of requiring a large amount of calculations. R-peak detection requires pre-processing and post-processing related to baseline drift and the removal of noise from the commercial power supply for ECG data. An adaptive filter technique is widely used for R-peak detection, but the R-peak value cannot be detected when the input is lower than a threshold value. Moreover, there is a problem in detecting the P-peak and T-peak values due to the derivation of an erroneous threshold value as a result of noise. We propose a robust R-peak detection algorithm with low complexity and simple computation to solve these problems. The proposed scheme removes the baseline drift in ECG signals using an adaptive filter to solve the problems involved in threshold extraction. We also propose a technique to extract the appropriate threshold value automatically using the minimum and maximum values of the filtered ECG signal. To detect the R-peak from the ECG signal, we propose a threshold neighborhood search technique. Through experiments, we confirmed the improvement of the R-peak detection accuracy of the proposed method and achieved a detection speed that is suitable for a mobile system by reducing the amount of calculation. The experimental results show that the heart rate detection accuracy and sensitivity were very high (about 100%).