• 제목/요약/키워드: Heart rate sensor

Search Result 126, Processing Time 0.031 seconds

Heart Response Effect by 1/f Fluctuation Sounds for Emotional Labor on Employee (1/f 수준 별 음악 자극이 감정 노동 종사자의 심장 반응에 미치는 효과)

  • Jeon, Byung-Mu;Whang, Min-Cheol
    • Science of Emotion and Sensibility
    • /
    • v.18 no.3
    • /
    • pp.63-70
    • /
    • 2015
  • This study identified heart response of participants while listening to sounds which have 1/f fluctuations with exponent ${\alpha}$ gradient. The participants were engaged in emotional stress work. Prior studies related to 1/f fluctuation sound have reported that sound source can alleviate psychological and physiological state of users. Subjects of this study were exposed to sound with three levels of ${\alpha}$ gradient. Heart response of subjects were measured with Photoplethysmography(PPG) sensor simultaneously. The dependent variables of this study were beat per minute(BPM), very low frequency percent of pulse rate variability (VLF percent), the standard deviation of all normal RR intervals (SDNN), and high frequency power(HF power). Subject showed arousal response when exposed to sound with exponent ${\alpha}$ gradient of 3 whereas the sound with exponent ${\alpha}$ gradient of 1 and 2 resulted in relax effect. The characteristic of 1/f fluctuation sounds can be applied to alleviate stress for employers under emotional labor.

BioPebble: Stone-type physiological sensing device Supporting personalized physiological signal analysis (BioPebble: 개인화된 해석을 지원하는 돌 타입 휴대용 생체신호 측정센서)

  • Choi, Ah-Young;Park, Go-Eun;Woo, Woon-Tack
    • 한국HCI학회:학술대회논문집
    • /
    • 2008.02a
    • /
    • pp.13-18
    • /
    • 2008
  • In these days, wearable and mobile physiological sensing devices have been studied according to the increasing interest on the healthy and wellbeing life. However, these sensing devices display just the sensing results, such as heart rate, skin temperature, and its daily records. In this work, we propose the novel type of mobile physiological sensing device which deliver the user comfortable grabbing feeling. In addition, we indicate the personalized physiological signal analysis result which be concluded by the different analysis results according to the person to person. In order to verify this sensing device, we collect the data set from 4 different users during a week and measure the physiological signal such as heart rate, hand temperature, and skin conductance. And we observe the result how the analysis results shows the difference between the users. We expect that this work can be applied in the various health care applications in the near future.

  • PDF

Software Architecture of a Wearable Device to Measure User's Vital Signal Depending on the Behavior Recognition (행동 인지에 따라 사용자 생체 신호를 측정하는 웨어러블 디바이스 소프트웨어 구조)

  • Choi, Dong-jin;Kang, Soon-Ju
    • The Journal of Korean Institute of Communications and Information Sciences
    • /
    • v.41 no.3
    • /
    • pp.347-358
    • /
    • 2016
  • The paper presents a software architecture for a wearable device to measure vital signs with the real-time user's behavior recognition. Taking vital signs with a wearable device help user measuring health state related to their behavior because a wearable device is worn in daily life. Especially, when the user is running or sleeping, oxygen saturation and heart rate are used to diagnose a respiratory problems. However, in measuring vital signs, continuosly measuring like the conventional method is not reasonable because motion artifact could decrease the accuracy of vital signs. And in order to fix the distortion, a complex algorithm is not appropriate because of the limited resources of the wearable device. In this paper, we proposed the software architecture for wearable device using a simple filter and the acceleration sensor to recognize the user's behavior and measure accurate vital signs with the behavior state.

The study of blood glucose level prediction using photoplethysmography and machine learning (PPG와 기계학습을 활용한 혈당수치 예측 연구)

  • Cheol-Gu, Park;Sang-Ki, Choi
    • Journal of Digital Policy
    • /
    • v.1 no.2
    • /
    • pp.61-69
    • /
    • 2022
  • The paper is a study to develop and verify a blood glucose level prediction model based on biosignals obtained from photoplethysmography (PPG) sensors, ICT technology and data. Blood glucose prediction used the MLP architecture of machine learning. The input layer of the machine learning model consists of 10 input nodes and 5 hidden layers: heart rate, heart rate variability, age, gender, VLF, LF, HF, SDNN, RMSSD, and PNN50. The results of the predictive model are MSE=0.0724, MAE=1.1022 and RMSE=1.0285, and the coefficient of determination (R2) is 0.9985. A blood glucose prediction model using bio-signal data collected from digital devices and machine learning was established and verified. If research to standardize and increase accuracy of machine learning datasets for various digital devices continues, it could be an alternative method for individual blood glucose management.

Unconstrained detection of Heart Rate and Respiration using PPG sensor (PPG 센서를 이용한 심박 및 호흡 신호의 무구속적 검출에 대한 연구)

  • Cha, Ji-Young;Choi, Hyun-Seok;Shin, Jae-Yeon;Lee, Kyoung-Joung
    • Proceedings of the KIEE Conference
    • /
    • 2008.10b
    • /
    • pp.482-483
    • /
    • 2008
  • 본 연구는 수면 중 무구속적 방식으로 에어 베개에 부착한 PPG 센서에서 호흡 및 심박을 검출하는 방법을 제안하였다. 본 연구에서 사용된 반사형 PPG 센서는 광원이 피부로 투과되어 혈관의 이완 및 수축 정도를 측정할 수 있다. 반사형 PPG 센서로부터 하드웨어 모듈을 통과한 생체 신호는 AD 변환되어 PC로 전송된다 PPG에서 검출된 분당 심박 수는 전송된 신호의 밸리점간의 시간 간격을 이용하여 추출하며 호흡 신호는 밸리점의 크기를 연결하여 추출하였다. 검출된 호흡 신호와 기준 호흡 신호간의 상관성을 확인하기 위해 기준신호로 호흡과 심박을 동시에 측정하여 그 결과를 분석하였다. PPG 센서로부터 획득한 심박 및 호흡 신호는 기준신호들과 높은 상관성을 가지며 호흡시 발생하는 움직임과 호흡 속도에 영향을 받는다는 것을 알 수 있었다.

  • PDF

A Study on Measurement of Heartrate and Respiration during Sleep using Doppler Radar: Preliminary Study (도플러 레이더를 이용한 수면 중의 심박 및 호흡 측정: 예비연구)

  • Lim, Yong Gyu
    • Journal of Biomedical Engineering Research
    • /
    • v.38 no.5
    • /
    • pp.264-270
    • /
    • 2017
  • A Doppler radar sensor was applied to detect respirations and heartbeats of persons who were lying on a bed. This study is preliminary study aiming at non-contact and non-intrusive respiration and heart rate monitoring during sleep in daily life. For the experiments, 10GHz Doppler radar with patch-type antenna was used and installed on the upper right and the distance between the body and the antenna was 1 m. The results show that each signal of respiration and heartbeat is observed in each frequency band however the frequency band and the waveform vary according to the subjects and the posture. The results show that the heartbeats can be detected with the peak detection in some frequency band. This study shows the feasibility of applying the Doppler radar to detection of heartbeat and respiration during sleep and further studies about heartbeat detection algorithm are required.

The development of the WEB-Based Virtual Reality for the Treatment of the Alcoholism (알코올중독자 치료를 위한 WEB 기반 가상현실 제작)

  • Paek, Seung-Eun;Beack, Seung-Hwa;Ryu, Jong-Hyun;Kim, Dong-Wan
    • Proceedings of the KIEE Conference
    • /
    • 2004.07d
    • /
    • pp.2690-2692
    • /
    • 2004
  • Medications or cognitive-behavior methods have been mainly used as a treatment of alcoholism. lately the virtualy technology has been applied to the kink of alcoholic disorders. A virtual environment makes him having ability to over come the drink. In this study, we were implemented by making panorama images and 3D object modules using 3D Studio MAX. VRML, JAVA Applet. And the BAR stimulator that composed with a position sensor head mount display, and audio system, is suggested. To illustrate the physiological difference between a person who has a alcoholism and and without a liquor bottle, heart rate was measured during experiment, and also measured a Person's HR after the virtual reality training. we demonstrated the subjective effectiveness of virtual reality psychotherapy through the clinical experiment.

  • PDF

Development of PPG Pillow System for Unconstrained Respiration and Heart Rate Monitoring during Sleep (수면 중 무구속적인 호흡 및 심박 수 측정을 위한 PPG 베개 시스템의 개발)

  • Cha, Ji-Young;Choi, Hyun-Seok;Shin, Jae-Yeon;Lee, Kyoung-Joung
    • Proceedings of the IEEK Conference
    • /
    • 2008.06a
    • /
    • pp.1101-1102
    • /
    • 2008
  • In this paper, we have developed PPG pillow system for unconstrained respiration monitoring during sleep. The system employs a pillow containing a PPG sensor and a simple respiration extraction algorithm. The results showed that the extracted respiratory rhythm was found to have close relations with the reference signal. The system has an advantage of processing simplicity. A follow-up study should be performed to evaluate the system in terms of breath intake.

  • PDF

Development of 3-channel Pulse Wave Measurement System (3채널 맥파 측정 시스템 개발)

  • Kim, Eun-Geun;Heo, Hyun;Nam, Ki-Chang;Kang, Hee-Jung;Huh, Young
    • Proceedings of the IEEK Conference
    • /
    • 2008.06a
    • /
    • pp.1049-1050
    • /
    • 2008
  • It is difficult to measure the pulse wave in a short time because radial artery position and located depth are different depending on the person. In this paper, the pulse wave measurement system was developed using 3 channel piezoresistive sensor array to detect the most significant pulse wave. Augmentation Index(AI) and Heart Rate(HR) analysis are also available for predicting cardiovascular risks. The developed system is small and easy to use. And it is promising to be used as home healthcare device.

  • PDF

Development of Dementia Screening Application Using Urine Test and Bionic Sensors (소변검사와 생체센서를 이용한 치매 스크리닝 애플리케이션 개발)

  • Kim, Jun-Young;Cho, Myeon-Gyun
    • IEMEK Journal of Embedded Systems and Applications
    • /
    • v.10 no.2
    • /
    • pp.109-117
    • /
    • 2015
  • In this paper, we have developed smart-phone App(application) for screening Dementia using bionic sensors, urine test and questionnaire. Since small amounts of urinary protein strongly predict faster cognitive decline in the elderly, smart-phone based urinalysis is adopted to screen dementia more accurately as well as bionic sensors such as $SpO_2$ and HRV(Heart Rate Variability). Firstly, DI(Dementia Index) is calculated from urinalysis, two bionic sensors and electric questionnaire, and then compared to the threshold from clinical test. Finally the results of Dementia screening is shown in your smart-phone and useful information to prevent or relieve Dementia is also given. We performed simple testing on persons aged over 60 and found out the proposed application can be useful devices for screening Dementia easily and quickly.