• Journal of the Ergonomics Society of Korea
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• v.35 no.5
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• pp.371-381
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• 2016

Objective:This study aims to evaluate the features of heart rate variability (HRV) and respiratory signals as indices for a driver's drowsiness and waking status in order to develop the classification model for a driver's drowsiness and waking status using those features. Background: Driver's drowsiness is one of the major causal factors for traffic accidents. This study hypothesized that the application of combined bio-signals to monitor the alertness level of drivers would improve the effectiveness of the classification techniques of driver's drowsiness. Method: The features of three heart rate variability (HRV) measurements including low frequency (LF), high frequency (HF), and LF/HF ratio and two respiratory measurements including peak and rate were acquired by the monotonous car driving simulation experiments using the photoplethysmogram (PPG) and respiration sensors. The experiments were repeated a total of 50 times on five healthy male participants in their 20s to 50s. The classification model was developed by selecting the optimal measurements, applying a binary logistic regression method and performing 3-fold cross validation. Results: The power of LF, HF, and LF/HF ratio, and the respiration peak of drowsiness status were reduced by 38%, 22%, 31%, and 7%, compared to those of waking status, while respiration rate was increased by 3%. The classification sensitivity of the model using both HRV and respiratory features (91.4%) was improved, compared to that of the model using only HRV feature (89.8%) and that using only respiratory feature (83.6%). Conclusion: This study suggests that the classification of driver's drowsiness and waking status may be improved by utilizing a combination of HRV and respiratory features. Application: The results of this study can be applied to the development of driver's drowsiness prevention systems.

• Journal of Sensor Science and Technology
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• v.15 no.2
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• pp.106-111
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• 2006

Pulse sensors generally have characteristics that cause a analytical error by the interference of signals according to tiny motion of body and pressure applied to skin. To resolve this problem, we implemented the sensor that is capable of simultaneously measuring pressure and PPG(photoplethymogram) in a state attached to skin. Pressure and PPG was recorded at the finger and wrist respectively to evaluate the usefulness of the implemented sensor. Then, it was observed that the shape of PPG from sensor changed by pressure pushing down skin. Results of this study suggested that it is possible to monitor a degree of skin pressurization and to guarantee a reliable measurement by simultaneously measuring pressure and PPG using implemented integrated sensor when measuring PPG on the wrist or the finger.

• Journal of Sensor Science and Technology
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• v.22 no.1
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• pp.76-83
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• 2013

A real-time wireless monitoring and analysis methods using the wearable PPG sensor to estimate cardiovascular condition is studied for ubiquitous healthcare service. A small size and low-power consuming wearable photoplethysmogram (PPG) sensor is designed as a wrist type device and connected with the IP node assigned its own IPv6 address. The measured PPG waveform in the IP node is collected and transferred to a central server PC through the IP-enabled wireless network for storage and analysis purposes. A monitoring and analysis program is designed to process the accelerated plethysmogram (APG) waveform by applying the second order derivatives to analyze systolic waves as well as heart rate variability analysis from the measured PPG waveform. From our results, the features of cardiovascular condition from individual's PPG waveform and estimation of vascular compliance by the comparison of APG-aging index (AI) and ratio of LF/HF are demonstrated.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.62 no.7
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• pp.1020-1026
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• 2013

Multirate filtering process on the biological signals like Electrocardiogram (ECG) and Photoplethysmogram (PPG) can be defined as the digital signal processing algorithm in which the sampling rate varies to omit or interpolate the intermediate values between the sampled data. With this aim, we suggest a new multirate filtering algorithm by deleting the extraneous data to eliminate the unwanted degradations such as granular noise due to the usage of high sampling frequency and simultaneously to detect the fiducial features of ECG and PPG with reducing the complexity of resolving fiducial points such as R-peak, Pulse peak and Pulse Transit Time (PTT). After the experimental simulations performed, we can conclude the fact that we can detect the fiducial features of ECG and PPG signal in terms of R-peak, Pulse peak and PTT without the loss of accuracy even if we do not maintain the original sampling frequency.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.67 no.7
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• pp.962-968
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• 2018

In this study, we developed novel indicators to assess postoperative pain based on PPG derivative waveform. As the candidate indicator of postoperative pain assessment, the time from the start of beating to the n-th peak($T_n$) and the n-th peak amplitude($A_n$) of the PPG derivative were selected. In order to verify derived indicators, each candidate indicator was derived from the PPG of 78 subjects before and after surgery, and it was confirmed whether significant changes were observed after surgery. Logistic classification was performed with each proposed indicator to calculate the pain classification accuracy, then the classification performance was compared with SPI(Surgical Pleth Index, GE Healthcare, Chicago, US). The results showed that there were significant differences(p < 0.01) in all indicators except for $T_3$ and $A_3$. The coefficient of variation(CV) of every time-related indicators were lower than the CV of SPI(30.43%), however, the CV in amplitude-related parameters were higher than that of SPI. Among the candidate indicators, amplitude of the first peak, $A_1$, showed that highest accuracy in post-operative pain classification, 68.72%, and it is 15.53% higher than SPI.

• Journal of Sensor Science and Technology
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• v.15 no.5
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• pp.334-340
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• 2006

A compact biosignal monitoring device was developed. Electrodes for electrocardiogram (ECG) and a LED and silicon detector for photoplethysmogram (PPG) were used. A lead II type was arranged for ECG measurement and reflected light was measured at the finger tip for PPG. A single chip microprocessor (model ADuC812, Analog Device) controlled a measurement protocol and processed measured signals. PPG and ECG had a sampling rate of 300 Hz with 8-bit resolution. The maximum power consumption was 100 mW. The microprocessor computed pulse transit time (PTT) between the R-wave of ECG and the peak of PPG. To increase the resolution of PTT, analog peak detectors obtained the peaks of ECG and PPG whose interval was calculated using an internal clock cycle of 921.6 kHz. The device was designed to be operated by 3-volt battery. Biosignals can be measured for $2{\sim}3$ days continuously without the external interruptions and data is stored to an on-board memory. Our system was successfully tested with human subjects.

• Journal of Sensor Science and Technology
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• v.21 no.5
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• pp.352-358
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• 2012

A sensor network system can be an efficient tool for healthcare telemetry for multiple users due to its power efficiency. One drawback is its limited data size. This paper proposed a real-time application of data compression/decompression method in u-Health monitoring system in order to improve the network efficiency. Our high priority was given to maintain a high quality of signal reconstruction since it is important to receive undistorted waveform. Our method consisted of down sampling coding and differential Huffman coding. Down sampling was applied based on the Nyquist-Shannon sampling theorem and signal amplitude was taken into account to increase compression rate in the differential Huffman coding. Our method was successfully tested in a ZigBee and WLAN dual network. Electrocardiogram (ECG) had an average compression ratio of 3.99 : 1 with 0.24% percentage root mean square difference (PRD). Photoplethysmogram (PPG) showed an average CR of 37.99 : 1 with 0.16% PRD. Our method produced an outstanding PRD compared to other previous reports.

• Journal of the Korea Society of Computer and Information
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• v.17 no.3
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• pp.105-111
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• 2012

Photoplethysmogram is widely used to measure heart rate and arterial blood oxygen saturation in human. This paper describes implementation a photoplethysmography monitoring system that uses 780nm and 940nm length infrared light in radial artery. That system used combinations of 8 LEDs and 2 photoelectricities. When recorded on the skin over radial artery, the radial pulse wave was inverted. The mechanism of inverted pulse wave skin, which was reduced during systolic period and increase during diastolic period of the cardiac cycle. Through this system, we discovered optimal environments and combinations of sensors in both penetration type and reflection type. These results suggest that radial arterial wall way reflect infrared ray.

• Journal of Biomedical Engineering Research
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• v.27 no.3
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• pp.89-93
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• 2006

A simple algorithm that can be used to estimate a healthy person's blood pressure using pulse transit time is proposed in this paper. Fifty healthy students participated in the experiment that was conducted in line with the study. The subjects were asked to exercise on several exercise levels using a bicycle ergometer. Their blood pressures during the succeeding rest period were measured. A simple method was proposed to illustrate the relationship between blood pressure and pulse transit time. The systolic blood pressures as well as the heights and weights of the subjects were regarded as the proper parameters, and a second-order regression curve was produced to estimate the subjects' blood pressures. The mean error of estimation was less than 10 mmHg, which was the mean error of manual measurement. Although our estimation model is so simple, it can be used to estimate continuous blood pressure measurement for bicycle ergometer exercise. The electrocardiograms, photoplethysmograms, and blood pressures, however, could not be measured simultaneously As such, their estimation may be slightly different from the results taken from simultaneous measurements.

• Journal of the Korean Society for Precision Engineering
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• v.27 no.6
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• pp.75-81
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• 2010

The purpose of this study was to investigate the short-term effects of electrical massager on stress-related parameters including heart rate variability (HRV), heart rate (HR) using the photoplethysmogram (PPG) signal with motion artifact correction. Twenty healthy subjects were randomly allocated to receive a 15-min section of three types ((1) resting mode (control group), (2) light massage mode, (3) strong massage mode). Results indicated that self-report, VAS (Visual Analog Scale) significantly decreased for two massage modes after massage except control group. In strong massage mode, it was associated with significant increases in HF, but significant decreases in LF and LH/HF ratio compared with the light massage mode. For all outcomes, similar changes were not observed in the control group. Also, the result founded that mean HR of all groups decrease. We conclude that electrical massager reduces perceived stress and improves adaptive autonomic response to stress in healthy adults.