• Journal of the Institute of Convergence Signal Processing
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• v.20 no.1
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• pp.45-50
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• 2019

When PPG signal is used in mobile healthcare devices, the accuracy of the measured heartbeat decreases from the influence by the movement of the user. The reason is that the frequency band of the noise overlaps the frequency band of the PPG signal. In order to remove these same noises, the methods using frequency analysis method or application of acceleration sensor have been investigated and showed excellent performance. However, in applying these methods to low-cost healthcare devices, it is difficult to apply these methods because of much processing time and sensor's cost. In order to solve these problems, this study proposed the filter design method using an adaptive notch filter and the fuzzy inference system to extract more accurate heart rate in real time and evaluated its performance. As results, it showed better results than the other methods. Based on the results, when applying the proposed method to design the mobile healthcare device, it is possible to measure the heartbeat more accurately in real time.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.10 no.2
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• pp.161-167
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• 2017

This paper presents an effective PPG measurement device in a wrist watch for smart healthcare. PPG can be acquired by measuring absorption of light and PPG measurement device is classified as transmission and reflection type. Reflection type is easy to implement but vulnerable to motion artifact. Moreover, reflection type must use 2 hands at once if the device is implemeted in a wrist watch. This paper describes the implementation of robust transmission type PPG measurement device by using previous developed reflection type device. PPG sensor is clip type and can be separated from the device so that the influence of motion artifact can be reduced. The proposed device can transmit the measured signal in real-time and is useful for smart healthcare. For evaluation of the proposed device, PPG signals are compared with reflection type in the same condition. The results show that the proposed device has 20% improvement in performance.

• The Journal of the Korea institute of electronic communication sciences
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• v.9 no.4
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• pp.499-508
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• 2014

In this paper, we implemented a LED sensitivity illumination system, being driven in response to changes in the biological signals of GSR and PPG signal. After measuring biological signals of a human body from GSR and PPG sensor modules, MCU decided the state of relaxation or arousal of the subject, being based on the wake relaxation identifying map proposed in this paper. A developed LED sensitivity illumination system makes the subject to reach a normal state by giving a change of the LED illumination color, corresponding to a state of the subject.

• Journal of the Ergonomics Society of Korea
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• v.27 no.4
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• pp.95-101
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• 2008

This research is to develop PPG filtering method for respiration measurement in U-Health Care system. Respiration rate was determined by filtering PPG and analyzing its spectrum. Optimal filter of PPG has been selected to get respiration by testing 120 sets of experiment data using 700 filtering cases. As a result, 2nd order Bessel-filter that used band-pass cutoff frequency at 0.175~0.4Hz with second order was good at developing respiration signal. Respiration signal in time domain could be continuously analyzed by converting frequency domain using spectrum analysis. 24 seconds has been found to be optimal time duration of collecting PPG data for determining respiration. Therefore, this study was successful of getting not only heart activity but also respiration by only PPG. Minimal invasive measurement obtaining multi-bio information by one sensor can be expected to apply to U-Health Care and human computer interaction.

• Journal of the Korean Institute of Intelligent Systems
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• v.17 no.5
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• pp.619-625
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• 2007

As low power, low cost wireless communication technology like Bluetooth, Zigbee, RFID has been put to practical use together with the wellbeing trend, the concern about ubiquitous health care has been greatly increased and u-Health is becoming one of the most important application in the sensor network field. Especially, development of the medical services to be able to cope with a state of emergency for solitary senior citizens and the aged in silver town is very meaningful itself and their needs are also expected to continuously increase with a rapid increase in an aging population. In this paper we demonstrate the feasibility of extracting accurate heart rate variability (HRV) measurements from photoelectric plethysmography(PPG) signals gathered by a ring type pulse oximeter sensor attached to the finger. For this, we made 2 types of ring sensor, that is reflective and pervious type, and developed the remote monitoring system which is able to collect HR data from ring sensor, analyze and cope with a state of emergency.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.26 no.10
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• pp.1469-1476
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• 2022

Recently, many researches have been conducted to estimate blood pressure using ECG(Electrocardiogram) and PPG(Photoplentysmography) signals. In this paper, we designed and implemented a mobile system to monitor blood pressure in real time by using 1-D convolutional neural networks. The proposed model consists of deep 11 layers which can learn to extract various features of ECG and PPG signals. The simulation results show that the more the number of convolutional kernels the learned neural network has, the more detailed characteristics of ECG and PPG signals resulted in better performance with reduced mean square error compared to linear regression model. With receiving measurement signals from wearable ECG and PPG sensor devices attached to the body, the developed system receives measurement data transmitted through Bluetooth communication from the devices, estimates systolic and diastolic blood pressure values using a learned model and displays its graph in real time.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.10 no.5
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• pp.992-999
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• 2009

The pulse transit time(PTT), which is determined by measuring the electrocardiogram(ECG) and pulse wave, gives comprehensive information about the cardiovascular system. However, a little movement of body and/or inaccurate pressure applied to skin during the measurement of pulse wave leads to acquire incorrect results. To overcome such problem, we developed an integrated sensor system which makes it possible to measure ECG, pressure pulse wave(PPW) and photoplethysmograph(PPG) at the same time. Futhermore, we implemented a new metal electrode which enables to continuously measure ECG. We verified that both integrated sensor system and new electrode provide useful effect.

• Advances in nano research
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• v.15 no.2
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• pp.155-163
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• 2023

Exercise is beneficial to the body in some ways. It is vital for people who have heart problems to perform exercise according to their condition. This paper describes how an Android platform can provide early warnings of fatigue during wushu exercise using Photoplethysmography (PPG) signals. Using the data from a micro-electro-mechanical system (MEMS) gyroscope to detect heart rate, this study contributes an algorithm to determine a user's fatigue during wushu exercise. It sends vibration messages to the user's smartphone device when the heart rate exceeds the limit or is too fast during exercise. The heart rate monitoring system in the app records heart rate data in real-time while exercising. A simple pulse sensor and Android app can be used to monitor heart rate. This plug-in sensor measures heart rate based on photoplethysmography (PPG) signals during exercise. Pulse sensors can be easily inserted into the fingertip of the user. An embedded microcontroller detects the heart rate by connecting a pulse sensor transmitted via Bluetooth to the smartphone. In order to measure the impact of physical activity on heart rate, Wushu System tests are conducted using various factors, such as age, exercise speed, and duration. During testing, the Android app was found to detect heart rate with an accuracy of 95.3% and to warn the user when their heart rate rises to an abnormal level.

• 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 information and communication convergence engineering
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• v.8 no.1
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• pp.112-115
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• 2010

The heart rate is the most important vital sign in diagnosing heart status. The simple method to measure the heart rate in the mobile healthcare device is using the PPG signal. In developing the mobile healthcare device using the PPG signal, the most important issue is the inaccuracy of the measured heart rate because the PPG signal is distorted from the user's motions. To improve the problem, this study proposed the new method that is to estimate the heart rate without an additional sensor in real life. The proposed method in this study is using the histogram filter. In order to evaluate the performance of the proposed method, the study compares its results with the moving average method in motion environment. According to the experimental results, the performance of the proposed method was more than 40% better than the performances of the MAF.