• The Journal of Korean Physical Therapy
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• v.25 no.6
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• pp.374-378
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• 2013

Purpose: Human body have biological rhythmic pattern in a day, which is affected by internal and external environmental factors. We investigated whether respiratory function was fluctuated according to the influence of time-of-day (around at 9 am, 1 pm, and 6 pm) in health subjects, using pulmonary function test (PFT). Methods: Eighteen healthy volunteers (8 men, mean ages; $22.4{\pm}1.6$, mean heights; $166.61{\pm}9.60$, mean weight; $59.3{\pm}10.3$) were recruited. Pulmonary function test (PFT) was measured at three time points in day, around 9 am, 1 pm, and 6 pm in calm research room with condition of under 55dB noise level, using a spirometer (Vmax 229, SensorMecis, USA). Forced vital capacity (FVC), forced expiratory volume at one second (FEV1), FVC/FEV1, and peak expiratory flow (PEF) were acquired. Results: In comparison of raw value of PFT among three time points, subjects showed generally better respiratory function at 9 am, than at other points, although no significance was found. In comparison of distribution of ranking for respiratory function in each individual, only PEF showed significant difference. In general, distributional ratio of subjects who showed best performance of respiratory function in a day was high. Conclusion: These findings showed that circadian rhythm by diurnal pattern was not detected on respiratory function throughout all day. But, best performance on respiratory function was observed mostly in the morning, although statistical significance did not exist.

• International journal of advanced smart convergence
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• v.9 no.4
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• pp.132-138
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• 2020

Worldwide, the number of corona virus disease 2019 (COVID-19) confirmed cases is rapidly increasing. Although vaccines and treatments for COVID-19 are being developed, the disease is unlikely to disappear completely. By attaching a smart sensor to the respirator worn by medical staff, Internet of Things (IoT) technology and artificial intelligence (AI) technology can be used to automatically detect the medical staff's infection symptoms. In the case of medical staff showing symptoms of the disease, appropriate medical treatment can be provided to protect the staff from the greater risk. In this study, we design and develop a system that detects cough, a typical symptom of respiratory infectious diseases, by applying IoT technology and artificial technology to respiratory protection. Because the cough sound is distorted within the respirator, it is difficult to guarantee accuracy in the AI model learned from the general cough sound. Therefore, coughing and non-coughing sounds were recorded using a sensor attached to a respirator, and AI models were trained and performance evaluated with this data. Mel-spectrogram conversion method was used to efficiently classify sound data, and the developed cough recognition system had a sensitivity of 95.12% and a specificity of 100%, and an overall accuracy of 97.94%.

• Tuberculosis and Respiratory Diseases
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• v.46 no.3
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• pp.386-393
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• 1999

Objective : Cardiopulmonary exercise testing in patients with heart and lung problems is used to assess functional capacity, evaluate responses to medical treatment, plan for exercise therapy, assess progression of disease process, and determine prognosis. Particularly in the patients with lung cancer, the exercise pulmonary function test gives significant physiologic assessment of the lung resection candidate. Common exercise modalities are running and cycling. Until now, the comparison of two tests mainly has been done in normal person and patients with cardiac diseases. This study is designed to compare the treadmill and bicycle exercise pulmonary function test in patients with respiratory diseases. Methods : Twenty one patients underwent a progressively incremental exercise test to the symptom-limited stage with the treadmill (Vmax29 Sensor Medics, USA) and the bicycle(model No. 2,900 Sensor Medics, USA) with 7 days apart between the two tests. Measurements were made of the metabolic, cardiorespiratory parameters, blood gases, and symptoms. Results : The results of the treadmill exercise showed significant elevation in the $VO_2$max, VEmax, and anaerobic threshold compared to those of bicycle exercise. In contrast, the results of the breathing and heart rate reserve showed the reverse. Conclusion : These results suggest that the type of exercise should be taken into consideration when interpreting exercise test in patients with respiratory diseases.

• Science of Emotion and Sensibility
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• v.21 no.1
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• pp.83-90
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• 2018

The purpose of this study is for fundamental research of meditation smart wear for physical and mental healing, and researching method for monitoring phase of meditation through textile by measuring the number of abdominal respiration when meditating. For this purpose, the research implemented Single Wall Carbon Nano-Tube (SWCNT) based strain gauges type textile sensor, considered reliability and validity of respiratory sensing, and analyzed efficiency of respiratory sensing based on body parts comparatively. The first preliminary experiment was to evaluate the performance of textile sensor through abdominal model dummy which open and shut of 5 cm repeatedly for 2 minutes at the rate of 0.1Hz in order to simulate abdominal respiration. It concluded signal efficiency between reference sensor(BIOPAC) and textile respiratory sensor appears statistically significant (p<0.001). The second experiment were conducted with 4 subjects doing abdominal respiration under same conditions, and after comparing the signal values between two sensors from 4 attached locations(around center and sides of omphali and phren), center of omphali and sides of phren were selected as suitable location for measuring meditational breathing as they showed large and stable signals. In result, this research aimed for implementing of the textile sensor for sensing meditational breathing of long respiration cycle, review of reliability and validity for sensing number of meditational respiration with the sensor and consideration of sensing efficiency by sensing location on body parts.

• Journal of the Korean Institute of Electrical and Electronic Material Engineers
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• v.35 no.4
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• pp.412-417
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• 2022

Capacitive-type humidity sensors with a high sensitivity and fast response/recovery times have attracted a great attention in non-contact respiration biological signal monitoring applications. However, complicated fabrication processes involving high-temperature heat treatment for the hygroscopic film is essential in the conventional ceramic-based humidity sensors. In this study, a non-toxic ceramic/metal halide (BaTiO₃(BT)/NaCl) humidity sensor was prepared at room temperature using a solvent-free aerosol deposition process (AD) without any additional process. Currently prepared BT/NaCl humidity sensor shows an excellent sensitivity (245 pF/RH%) and superior response/recovery times (3s/4s) due to the NaCl ionization effect resulting in an immense interfacial polarization. Furthermore, the non-contact respiration signal variation using the BT/NaCl sensor was determined to be over 700% by maintaining the distance of 20 cm between the individual and the sensor. Through the AD-fabricated sensor in this study, we expect to develop a non-contact biological signal monitoring system that can be applied to various fields such as respiratory disease detection and management, infant respiratory signal observation, and touchless skin moisture sensing button.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.25 no.8
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• pp.1130-1133
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• 2021

In this paper, a miniaturized sensor interface circuit for the respiration detection system is proposed. Respiratory diagnosis is one of the main ways to predict various diseases. The proposed system consists of respiration detection sensor, temperature sensor, and interface circuits. Electrochemical type gas sensor using solid electrolytes is adopted for respiration detection. Proposed system performs sensing, amplification, analog-to-digital conversion, digital signal processing, and i2c communication. And also proposed system has a small form factor and low-cost characteristics through optimization and miniaturization of the circuit structure. Moreover, technique for sensor degradation compensation is introduced to obtain high accuracy. The size of proposed system is about 1.36 cm².

• Journal of the Korea Academia-Industrial cooperation Society
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• v.20 no.7
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• pp.151-157
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• 2019

Recently, monitoring respiration of people has been of interest using non-invasive method. Among the vital signals usually used for indicating health status, non-invasive and portable device based monitoring respiratory status is practically useful and enable one to promptly deal with abnormal physical status. This paper proposes the approach to real-time detection of apnea signal based on Short-Time-Fourier-Transform(STFT). Contrary to the analysis of a signal in frequency domain using Fast-Fourier Transform, this paper employs Short-time-Fourier-Transform so that frequency response can be analyzed in short time interval. The respiratory signal is acquired using UWB radar sensor that enables one to obtain respiration signal in contactless way. Detection of respiratory status is carried out by analyzing frequency response, and classification of respiratory status can be provided. In particular, STFT is employed to analyze respiratory signal in real-time, leading to effective analysis of the respiratory status in practice. In the case of existence of noise in the signal, appropriate filtering process is employed as well. The proposed method is straightforward and is workable in practice to analyze the respiratory status of people. To evaluate the proposed method, experimental results are provided.

• International journal of advanced smart convergence
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• v.12 no.4
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• pp.378-385
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• 2023

The importance of wearing respiratory protective equipment has been highlighted even more during the COVID-19 pandemic. Even if the suitability of respiratory protection has been confirmed through testing in a laboratory environment, there remains the potential for leakage points in the respirators due to improper application by the wearer, damage to the equipment, or sudden movements in real working conditions. In this paper, we propose a method to detect the occurrence of leak holes by measuring the pressure changes inside the mask according to the wearer's breathing activity by attaching an IoT sensor to a full-face respirator. We designed 9 experimental scenarios by adjusting the degree of leak holes of the respirator and the breathing cycle time, and acquired respiratory data for the wearer of the respirator accordingly. Additionally, we analyzed the respiratory data to identify the duration and pressure change range for each breath, utilizing this data to train a neural network model for detecting leak holes in the respirator. The experimental results applying the developed neural network model showed a sensitivity of 100%, specificity of 94.29%, and accuracy of 97.53%. We conclude that the effective detection of leak holes can be achieved by incorporating affordable, small-sized IoT sensors into respiratory protective equipment.

• Proceedings of the IEEK Conference
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• 2000.06e
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• pp.121-123
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• 2000

Changes in breathing pattern and apnea both can be !he result of sleep disorders. The focus of this paper is to develop methodologies to monitor the breathing pattern and to detect apnea. An accurate recording of the respiratory phase can be carried out with different methods. One of these methods is the use of a thermocouple, which reacts to the variation in air temperature, placed in the nose and mouth of the patient. The K-type thermocouple was used because it has high reliability, thermo-stability, and good corrosion resistance. And also, it has a considerable long time constant that gives a low cut-off frequency, well below the respiratory frequency and thereby causing a large phase difference. The result showed that timing of respiration was accurately obtained with the AD595, amplifier for K-type thermocouple.

• Progress in Medical Physics
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• v.23 no.1
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• pp.1-7
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• 2012

The purpose of this study was to develop the respiratory training system using individual characteristic guiding waveform to reduce the impact of respiratory motion that causes artifact in radiotherapy. In order to evaluate the improvement of respiratory regularity, 5 volunteers were included and their respiratory signals were acquired using the in-house developed belt-type sensor. Respiratory training system needs 10 free breathing cycles of each volunteer to make individual characteristic guiding waveform based on Fourier series and it guides patient's next breathing. For each volunteer, free breathing and guided breathing which uses individual characteristic guiding waveform were performed to acquire the respiratory cycles for 3 min. The root mean square error (RMSE) was computed to analyze improvement of respiratory regularity in period and displacement. It was found that respiratory regularity was improved by using respiratory training system. RMSE of guided breathing decreased up to 40% in displacement and 76% in period compared with free breathing. In conclusion, since the guiding waveform was easy to follow for the volunteers, the respiratory regularity was significantly improved by using in-house developed respiratory training system. So it would be helpful to improve accuracy and efficiency during 4D-RT, 4D-CT.