• Journal of People, Plants, and Environment
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• v.22 no.2
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• pp.219-229
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• 2019

This study was carried out to verify the accuracy of fitness tracking devices in monitoring heart rate and energy consumption and to contribute to the development of a forest exercise program that can recommend the intensity and amount of forest exercises based on personal health-related data and provide monitoring and feedback on forest exercises. Among several commercially available wearable devices, Fitbit was selected for the research, as it provides Open API and data collected by Fitbit can be utilized by third parties to develop programs. Fitbit provides users with various information collected during forest exercises including exercise time and distance, heart rate, energy consumption, as well as the altitude and slope of forests collected by GPS. However, in order to verify the usability of the heart rate and energy consumption data collected by Fitbit in forest, the accuracy of heart rate and energy consumption were verified by comparing the data collected by Fitbit and reference. In this study, 13 middle-aged women were participated, and it was found that the heart rate measured by Fitbit showed a very low error rate and high correlation with that measured by the reference. The energy consumption measured by Fitbit was not significantly different from that measured in the reference, but the error rate was slightly higher. However, there was high correlation between the results measured by Fibit and the reference, therefore, it can be concluded that Fitbit can be utilized in developing actual forest exercise programs.

• The Journal of the Korea Contents Association
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• v.9 no.12
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• pp.339-347
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• 2009

Purpose : This study was to investigate the influence of heart rate and coronary calcification on diagnostic accuracy of 64-slice multidetector CT(MDCT) in coronary artery disease. Methods : 178 patients(84 men, 94 women) undergoing cardiac CT were included in this study. 3 coronary arteries(LAD, LCX, RCA) were assessed the presence of significant stenosis($\geq50%$) and the results compared with those of coronary angiography. Results : On a patient-based analysis, the diagnostic accuracy of 64-slice MDCT was 96.6%. The diagnostic accuracy on left anterior descending, left circumflex, right coronary artery were 86.5%, 84.3%, 92.1% respectively. Body mass index and blood pressure were not influenced on diagnostic accuracy of 64-slice MDCT. In less than 60/min of heart rate, accuracy was 90.1% and $\kappa$ value was 0.78. While in more than 70/min of heart rate, accuracy was 75.8% and $\kappa$ value was 0.52. In less than 100 of coronary calcification, accuracy was 91.3% and $\kappa$ value was 0.81. While in more than 400, accuracy was 68.6% and $\kappa$ value was 0.33. Conclusion : 64-slice MDCT shows similar diagnostic accuracy as coronary angiography. But in the context of more than 70/min of heart rate and 400 of coronary calcification, diagnostic accuracy was decreased. So there needs to identify heart rate and coronary calcification in cardiac CT, and if heart rate shows more than 70/min, use beta-blocker to regulate it.

• Journal of Multimedia Information System
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• v.8 no.1
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• pp.1-10
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• 2021

Heart Rate is a crucial physiological parameter that provides basic information about the state of the human body in the cardiovascular system, as well as in medical diagnostics and fitness assessments. At present day, it has been demonstrated that facial video-based photoplethysmographic signal captured using a low-cost RGB camera is possible to retrieve remote heart rate. Traditional heart rate measurement is mostly obtained by direct contact with the human body, therefore, it can result inconvenient for long-term measurement due to the discomfort that it causes to the subject. In this paper, we propose a non-contact-based remote heart rate measuring approach of the subject which depends on the color intensity variation of the subject's facial skin. The proposed method is applied in two regions of the subject's face, forehead and cheeks. For this, three different algorithms are used to measure the heart rate. i.e., Fast Fourier Transform (FFT), Independent Component Analysis (ICA) and Principal Component Analysis (PCA). The average accuracy for the three algorithms utilizing the proposed method was 89.25% in both regions. It is also noteworthy that the FastICA algorithm showed a higher average accuracy of more than 92% in both regions. The proposed method obtained 1.94% higher average accuracy than the traditional method based on average color value.

• 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.

• IEMEK Journal of Embedded Systems and Applications
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• v.18 no.2
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• pp.51-58
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• 2023

This paper proposes a deep learning method for estimating the heart rate from facial videos. Our proposed method estimates remote photoplethysmography (rPPG) signals to predict the heart rate. Although there have been proposed several methods for estimating rPPG signals, most previous methods can not be utilized in low-power single board computers due to their computational complexity. To address this problem, we construct a lightweight student model and employ a knowledge distillation technique to reduce the performance degradation of a deeper network model. The teacher model consists of 795k parameters, whereas the student model only contains 24k parameters, and therefore, the inference time was reduced with the factor of 10. By distilling the knowledge of the intermediate feature maps of the teacher model, we improved the accuracy of the student model for estimating the heart rate. Experiments were conducted on the UBFC-rPPG dataset to demonstrate the effectiveness of the proposed method. Moreover, we collected our own dataset to verify the accuracy and processing time of the proposed method on a real-world dataset. Experimental results on a NVIDIA Jetson Nano board demonstrate that our proposed method can infer the heart rate in real time with the mean absolute error of 2.5183 bpm.

• Journal of Biomedical Engineering Research
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• v.43 no.1
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• pp.45-51
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• 2022

The purpose of this study is to improve the classification accuracy compared to the existing InceptionV3 model by proposing a new model modified with the fully connected hierarchical structure of InceptionV3, which showed excellent performance in medical image classification. The data used for model training were trained after data augmentation on a total of 1026 chest X-ray images of patients diagnosed with normal heart and Cardiomegaly at Kyungpook National University Hospital. As a result of the experiment, the learning classification accuracy and loss of the InceptionV3 model were 99.57% and 1.42, and the accuracy and loss of the proposed model were 99.81% and 0.92. As a result of the classification performance evaluation for precision, recall, and F1 score of Inception V3, the precision of the normal heart was 78%, the recall rate was 100%, and the F1 score was 88. The classification accuracy for Cardiomegaly was 100%, the recall rate was 78%, and the F1 score was 88. On the other hand, in the case of the proposed model, the accuracy for a normal heart was 100%, the recall rate was 92%, and the F1 score was 96. The classification accuracy for Cardiomegaly was 95%, the recall rate was 100%, and the F1 score was 97. If the chest X-ray image for normal heart and Cardiomegaly can be classified using the model proposed based on the study results, better classification will be possible and the reliability of classification performance will gradually increase.

• Korean Journal of Radiology
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• v.20 no.1
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• pp.94-101
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• 2019

Objective: To investigate the efficacy of motion-correction algorithm (MCA) in improving coronary artery image quality and measurement accuracy using an anthropomorphic dynamic heart phantom and 256-detector row computed tomography (CT) scanner. Materials and Methods: An anthropomorphic dynamic heart phantom was scanned under a static condition and under heart rate (HR) simulation of 50-120 beats per minute (bpm), and the obtained images were reconstructed using conventional algorithm (CA) and MCA. We compared the subjective image quality of coronary arteries using a four-point scale (1, excellent; 2, good; 3, fair; 4, poor) and measurement accuracy using measurement errors of the minimal luminal diameter (MLD) and minimal luminal area (MLA). Results: Compared with CA, MCA significantly improved the subjective image quality at HRs of 110 bpm (1.3 ± 0.3 vs. 1.9 ± 0.8, p = 0.003) and 120 bpm (1.7 ± 0.7 vs. 2.3 ± 0.6, p = 0.006). The measurement error of MLD significantly decreased on using MCA at 110 bpm (11.7 ± 5.9% vs. 18.4 ± 9.4%, p = 0.013) and 120 bpm (10.0 ± 7.3% vs. 25.0 ± 16.5%, p = 0.013). The measurement error of the MLA was also reduced using MCA at 110 bpm (19.2 ± 28.1% vs. 26.4 ± 21.6%, p = 0.028) and 120 bpm (17.9 ± 17.7% vs. 34.8 ± 19.6%, p = 0.018). Conclusion: Motion-correction algorithm can improve the coronary artery image quality and measurement accuracy at a high HR using an anthropomorphic dynamic heart phantom and 256-detector row CT scanner.

• Journal of Korean Physical Therapy Science
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• v.10 no.1
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• pp.38-46
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• 2003

Since the current tendencies show us the increasing number of cerebral palsy children and the standard longevity, we need to find out more research about the following various problems. Therefore I have tried to figure out the difference of oxygen saturation and heart rate between before ambulation and after. Objects chosen are 17 C.P children on the process of treatment those who were able to walk and 8 normal children in Ah-San hospital, Gang-Nung. They haven't had either any operation or suffered heart disease and I measured their oxygen saturation and heart rate by using pulse-oximeter and are analyzed by SPSS (10.07 version). Results are the followings; 1. There was no difference of oxygen saturation and heart rate between pre-ambulation and post-ambulation of normal and spastic hemiplegia children. 2. There showed the significant statistic difference of oxygen saturation, heart rate between pre-ambulates and post-ambulation of normal and spastic diplegia(p<.05). 3. There was no difference of oxygen saturation, heart rate in C.P between(p>.05), but shows the significant statistic difference in heart rate(p<.05). As I compared the oxygen saturation and heart rate of spastic and normal children on between pre-ambulation and post-ambulation, theres is significant statistic difference on both items (p<.05). However there was no difference of oxygen saturation among hemiplegia, normal and diplegia children while the pulse rate showed the significant difference(p<.05). According to this clinical research, CP children's oxygen saturation and heart rate had no change between pre and post compared to normal children. But there was difference in diplegia. This is why we need to invest time to study these kinds of research about various analysis and comparison of oxygen saturation and heart rate, and furthermore making use of pulse-oxymetry in physical therapy room for the children involved would be beneficial to calculate in accuracy without any discomfort for the patient as well.

• Science of Emotion and Sensibility
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• v.23 no.2
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• pp.51-60
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• 2020

This study aimed to develop a modular smart clothing system for heart rate monitoring that reduces the inconvenience caused by battery charging and the large size of measurement devices. The heart rate monitoring system was modularized into a temporary device and a continuous device to enable heart rate monitoring depending on the requirement. The temporary device with near-field communication (NFC) and heart rate sensors was developed as a clothing attachment type that enables heart rate monitoring via smart phone tagging when required. The continuous device is based on Bluetooth Low Energy (BLE) communication and batteries and was developed to enable continuous heart rate measurement via a direct connection to the temporary device. Furthermore, the temporary device was configured to connect with a textile electrode made of a silver-based knitted fabric designed to be located below the pectoralis major muscle for heart rate measurement. Considering the user-experience factors, key functions, and the ease of use, we developed an application to automatically log through smart phone tagging to improve usability. To evaluate the accuracy of the heart rate measurement, we recorded the heart rate of 10 healthy male subjects with a modular smart clothing system and compared the results with the heart rate values measured by the Polar RS800. Consequently, the average heart rate value measured by the temporary system was 85.37, while that measured by the reference device was 87.03, corresponding to an accuracy of 96.73%. No significant difference was found in comparison with the reference device (T value = -1.892, p = .091). Similarly, the average heart rate measured by the continuous system was 86.00, while that measured by the reference device was 86.97, corresponding to an accuracy of 97.16%. No significant difference was found in terms of the heart rate value between the two signals (T value = 1.089, p = .304). The significance of this study is to develop and validate a modular clothing system that can measure heart rates according to the purpose of the user. The developed modular smart clothing system for heart rate monitoring enables dual product planning by reducing the price increase due to unnecessary functions.

• Journal of the Korean Society for Precision Engineering
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• v.22 no.1
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• pp.193-198
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• 2005

Changes in visuospatial cognitive performance, blood oxygen saturation and heart rate due to the highly concentrated oxygen administration were observed in this study. Six male ($25.8 \pm$1.0) and six female (($23.8 \pm$ 1.9) adults were asked to perform 20 visuospatial tasks with the same level of difficulties by supplying two different oxygen levels (21%, 30%). Experiment consisted of Rest1 (1 min.), Control (1 min.), Task (4 min.), and Rest2 (4 min.) and physiological signals such as blood oxygen saturation and heart rate were measured through each stage. The result showed the accuracy of task performance increased significantly at 30% oxygen concentration compared with 21%, which means oxygen supply has positive effects on visuospatial cognitive performance. When 30% oxygen was supplied, blood oxygen saturation during control and task phases was increased and heart rate was decreased compared with 21%. It means that 30% oxygen can stimulate brain activities by directly increasing the actual level of blood oxygen concentration during cognitive performance, and enough oxygen supply during cognitive performance make heart rate decrease.