• 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 Communications and Networks
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• v.13 no.2
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• pp.86-94
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• 2011

In recent years, there has been a rise in epidemiological evidence suggesting the health benefits of a physically active lifestyle. However, it is not always easy for individuals to personally recognize the optimal conditions for exercise and physical activity. Wearable acceleration-based pedometers have become widely used in estimating the amount of physical activity, and to a limited extent, providing information regarding exercise intensity, but they have never been used to assess adaptation to exercise. In order to realize simultaneous activity monitoring for multiple users exercising outdoors, we developed a prototype wireless local area network (WLAN) based system. In our system, a WLAN is deployed outside, and a user wearing a smart phone and monitoring device exercises freely within the coverage area of the wireless network. By doing so, the developed system is able to monitor the activity of each user andmeasures various parameters including those related to exercise adaptation. In a demonstration experiment, the developed system was evaluated and used to monitor users enjoying a Nordic walk, after which users were immediately able to receive their exercise report. In this paper, we discuss the requirements and issues in developing an activity monitoring system and report the findings we obtained through the demonstration experiment.

• Journal of Biomedical Engineering Research
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• v.35 no.5
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• pp.111-118
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• 2014

As assessment of quantitative energy expenditure for effective exercise is becoming more important, many researches about the monitoring system for exercise status or result have been actively carried out. In this case, however, bicycle riders feel restrained and uncomfortable because the riders should wear a belt-type electrocardiograph or a watch-type accelerometer or GPS system during the assessment of bicycle exercise. In this study, therefore, an electrocardiograph based on textile electrode was developed for measuring ECG and calculating heart rate from the bicycle rider without feeling restraint, and smartphone application was also developed for monitoring the heart rate.

• Convergence Security Journal
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• v.15 no.5
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• pp.23-28
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• 2015

This study was carried out the exercise monitoring utilizing mobile device which is easily accessible and personalized exercise prescription based on it. For this, a variety of exercise monitoring and status of those were investigated and suggested the potential of personalized exercise prescription. If individual users send their body and vital informations using a mobile device, all informations are collected in u-Fitness center. After then exercise expert provide a customized prescription based on the collected information and feed data into database of u-Fitness center. System of U-Fitness center will provide the best personalized exercise prescription by automatically connecting to the content providers. In the future, a variety of mobile devices and services will work together and it can be evolved as an open platform that can be used for multiple services according to the needs of individual users on a single platform.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.67 no.7
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• pp.910-916
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• 2018

In this paper, we developed a shoulder rehabilitation exercise device and monitoring system to remotely provide rehabilitation system for the ones who need shoulder exercises including the patients with rotator cuff rupture. In order to evaluate the severity of shoulder muscle injury, a total of 4 shoulder rehabilitation exercises ((3) shoulder abduction, (2) shoulder flexion, (3) shoulder abduction with elbow flexion, (4) shoulder extension with elbow flexion) were selected and instructed to be performed with a 3 kg dumbbell for 5 times. For EMG (electromyogram) signal analysis, each subject's maximum voluntary contraction (MVC) was measured. EMG signals reflect the activation level of contracting muscles during dynamic exercises. Six participants' muscle activation levels in posterior deltoid, middle deltoid, upper trapezius, and infraspinatus were measured and compared. The mean power spectrum values in the time and frequency domains were compared between two age-matched groups (20s and 50s). The results showed lower muscle activation in the elderly subjects (n=3) compared to that of the ones in their twenties (n=3).

• Journal of Digital Contents Society
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• v.19 no.7
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• pp.1225-1235
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• 2018

In this study, as a part of practical and customized smart contents development planning research related to smart fitness contents associated with smart wear that can monitor physical activity, we investigated the potential needs for smart fitness contents through research. As a result, the potential needs for smart fitness contents is 'accessibility to use', 'inducement of interest', 'diverse story line' were derived at the stage of 'before exercise', 'Real - time voice coaching', 'accurate exercise posture monitoring', and 'personalized exercise prescription' were derived at the stage of 'during exercise'. At the stage of 'after exercise', 'substantial reward system', 'grading system', 'body figure change monitoring' and 'everyday life monitoring' were derived. At the stage of 'connection to the next exercise', 'triggering exercise motivation', 'high sustainability' wear derived.

• Journal of the Institute of Convergence Signal Processing
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• v.21 no.1
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• pp.49-54
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• 2020

Cardiovascular disease is the leading cause of death worldwide and is caused by a variety of causes. The highest risk factor for cardiovascular disease is high blood pressure, which has no obvious symptoms, but if left untreated, it causes several complications. In order to treat hypertension, medication and regular exercise are required. In people with high blood pressure, excessive physical activity can put a great strain on the heart and lead to cardiovascular disease. Therefore, there is a need for an exercise intensity monitoring system through PTT measurement that can perform exercise at an appropriate intensity. In this study, we implemented a PTT change monitoring system according to exercise intensity by calculating PTT through ECG and PPG measurement. The implemented system differentiates the R-peak of the ECG and P-peak of the PPG, and calculates the PTT using the time difference between R-peak and P-peak. A running experiment was conducted to monitoring PTT change according to exercise intensity. As a result of the experiment, low intensity PTT is 0.313s, moderate is 0.220s, high is 0.188s, it was confirmed that the PTT decreased as the exercise increase increased.

• Journal of Electrical Engineering and Technology
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• v.10 no.6
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• pp.2434-2441
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• 2015

This paper proposes an exercise recommendation system for treating obesity that provides systematic recommendations for exercise and diet. Five body indices are considered as indicators for recommend exercise and diet. The system also informs users of prohibited foods using health data including blood pressure, blood sugar, and total cholesterol. To maximize the utility of the system, it displays recommendations for both indoor and outdoor activities. The system is equipped with multimode sensors, including a three-axis accelerometer, a laser, a pressure sensor, and a wrist-mounted sensor. To demonstrate the effectiveness of the system, field tests are carried out with three participants over 20 days, which show that the proposed system is effective in treating obesity.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.16 no.7
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• pp.1533-1540
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• 2012

u-Life care device collect body bio formation, and classify and store them in exercise patterns. Afterwards, the devices send the data through bluetooth wireless communication to the smart phones which set Google Android operation system at regular intervals. The information is checked out through application. u-Life care device calculates calories spent a day after monitoring activity quantity with 3-axis acceleration sensor. The device judges the status of health through body data mining and consults tailored exercise treatment. When sending body data, the device sends them in smart phone through Blue Tooth wireless communication at once. So, as a strong point, the device doesn't need mobile gateway or home gateway used for sending to web server information sensed from exercise life care products.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.56 no.9
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• pp.1688-1693
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• 2007

The aim of this paper is to develop and verify the system which can detect heart rate during exercise by using conductive fabric electrode and transportable measurement module. The experiment was performed under 4 conditions(resting, walking, jogging, running) and 18 subjects data are used. By using the ECG measurement system used in cardiac stress testing as reference value in order to verify the accuracy of the developed system, the relative error and correlation coefficient was calculated for each subject at every 3 seconds. The results have shown that the high correlation between the developed system and the reference system for detecting heart rate during exercise. Relative error and correlation coefficient are 2.27% and 0.9877, respectively. 7 subjects data are omitted in these calculations because of severe noises. Therefore, it is expected that this system could be used as a health monitoring system in ubiquitous environment in the future.