• Title/Summary/Keyword: 센서 기반 바이오피드백 시스템

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Development of the Total Exercise Management System Based on Intelligent Bio-feedback (지능형 바이오피드백 기반의 종합 운동관리 시스템 개발)

  • Yoo, Sung-Jae;Noh, Yeon-Sik;Nam, Young-Kwang;Yoon, Hyung-Ro
    • Proceedings of the Korean Information Science Society Conference
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    • 2011.06b
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    • pp.98-101
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    • 2011
  • 건강에 대한 관심이 높아지면서 헬스케어와 IT와의 결합으로 많은 IT관련 헬스 케어 시스템이 개발되고 있으며, 이러한 시스템의 수요 또한 증가하는 추세에 있다. 본 논문에서는 이와 같은 건강에 대한 관심을 반영하여 자신에 맞는 운동을 선택 및 수행하고 그에 따른 피드백을 받을 수 있는 시스템을 소개한다. 본 시스템은 헬스케어의 건강 관리 시스템을 피트니스 관점에 비중을 두어 이용자의 초기 운동 정보를 기반으로 몸에 맞는 운동을 처방하여 운동을 수행 시키고 그 결과를 저장한다. 운동 정보는 생체 신호 계측을 위한 물리량 센서 및 모듈에 의하여 측정된다. 저장된 운동 결과는 다음 운동 처방에 반영되어 피드백 방식으로 이용자의 운동에 적용된다. 운동 처방은 주단위로 수행되면서 지속적인 관리를 받을 수 있도록 설계되었다. 본 시스템은 운동 중 발생하는 무구속, 무자각적 생체 신호 계측을 위한 물리량 센서 및 모듈을 이용하여 다차원 생체 정보를 수집하고 생체 신호 표준화 및 생체 역학적 해석을 통해 데이터베이스를 구축하였다. 이렇게 구축한 데이터들을 통하여 지능형 바이오피드백 기반의 사용자 맞춤형 운동 관리 시스템을 개발하여 사용자의 건강 및 운동능력을 향상시키는데 그 목적이 있다.

Tube phonation in water for patients with hyperfunctional voice disorders: The effect of tube diameter and water immersion depth on bubble height and maximum phonation time (과기능적 음성장애 환자의 물저항발성: 튜브 직경과 물 깊이가 물거품 높이 및 최대발성지속시간에 미치는 영향)

  • Min Gyeong Kim;Seong Hee Choi;Jong-In Youn
    • Phonetics and Speech Sciences
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    • v.15 no.2
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    • pp.31-40
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    • 2023
  • Tube phonation in water has been widely used for voice training among semi-occluded vocal tract (SOVT) exercises in which the patient bubbles with phonation keeping the tube submerged in water. This study aims to investigate the effect of tube diameter and water depth on bubble height and maximum phonation time (MPT) for patients with hyperfunctional voice disorders. Seventeen patients with hyperfunctional voice disorders were asked to bubble with sustained /u/ at the different inner diameters of tube (5, 7, and 10 mm), water depth (4, 7, and 10 cm). A water resistance phonation biofeedback system using a water height sensor was used for recording bubble height and MPT. The bubble height was significantly changed by the tube diameter while MPT was significantly changed with the tube diameter and water depth. Although the wider tube presented significantly lower bubble height for a given depth, relatively consistent bubble height was maintained. Depending on the water depth, the bubble height did not significantly differ for a given tube diameter. In addtion, MPT significantly decreased with water depth and a wider tube led significantly shorter MPT. A water level-driven water resistance biofeedback system provided useful information on bubble characteristics and vocal fold vibration depending on tube diameter and water depth. It can be useful to monitor the breath support during water resistance phonation for patients with hyperfunctional voice disorders.

m-Health System for Processing of Clinical Biosignals based Android Platform (안드로이드 플랫폼 기반의 임상 바이오신호 처리를 위한 모바일 헬스 시스템)

  • Seo, Jung-Hee;Park, Hung-Bog
    • Journal of the Korea Society of Computer and Information
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    • v.17 no.7
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    • pp.97-106
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    • 2012
  • Management of biosignal data in mobile devices causes many problems in real-time transmission of large volume of multimedia data or storage devices. Therefore, this research paper intends to suggest an m-Health system, a clinical data processing system using mobile in order to provide quick medical service. This system deployed health system on IP network, compounded outputs from many bio sensing in remote sites and performed integrated data processing electronically on various bio sensors. The m-health system measures and monitors various biosignals and sends them to data servers of remote hospitals. It is an Android-based mobile application which patients and their family and medical staff can use anywhere anytime. Medical staff access patient data from hospital data servers and provide feedback on medical diagnosis and prescription to patients or users. Video stream for patient monitoring uses a scalable transcoding technique to decides data size appropriate for network traffic and sends video stream, remarkably reducing loads of mobile systems and networks.

Development of Personalized Exercise Prescription System based on Kinect Sensor (Kinect Sensor 기반의 개인 맞춤형 운동 처방 시스템 개발)

  • Woo, Hyun-Ji;Yu, Mi;Hong, Chul-Un;Kwon, Tae-Kyu
    • The Journal of the Korea Contents Association
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    • v.22 no.3
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    • pp.593-605
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    • 2022
  • The purpose of this study is to investigate the personalized treacmill exercise analysis using a smart mirror based on Kinect sensor. To evaluate the performance of the development system, 10 health males were used to measure the range of the hip joint, knee joint, and ankle joint using a smart mirror when walking on a treadmill. For the validity and reliability of the development system, the validity and reliability were analyzed by comparing the human movement data measured by the Kinect sensor with the human movement data measured by the infrared motion capture device. As a result of validity verification, the correlation coefficient r=0.871~0.919 showed a high positive correlation, and through linear regression analysis, the validity of the smart mirror system was 88%. Reliability verification was conducted by ICC analysis. As a result of reliability verification, the correlation coefficient r=0.743~0.916 showed high correlation between subjects, and the consistency for repeated measurement was also very high at ICC=0.937. In conclusion, despite the disadvantage that Kinect sensor is less accurate than the motion capture system, Kinect is it has the advantage of low price and real-time information feedback. This means that the Kinect sensor is likely to be used as a tool for evaluating exercise prescription through human motion measurement and analysis.

EEG Based Brain-Computer Interface System Using Time-multiplexing and Bio-Feedback (Time-multiplexing과 바이오 피드백을 이용한 EEG기반 뇌-컴퓨터 인터페이스 시스템)

  • Bae, Il-Han;Ban, Sang-Woo;Lee, Min-Ho
    • Journal of Sensor Science and Technology
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    • v.13 no.3
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    • pp.236-243
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    • 2004
  • In this paper, we proposed a brain-computer interface system using EEG signals. It can generate 4 direction command signal from EEG signals captured during imagination of subjects. Bandpass filter used for preprocessing to detect the brain signal, and the power spectrum at a specific frequency domain of the EEG signals for concentration status and non-concentration one is used for feature. In order to generate an adequate signal for controlling the 4 direction movement, we propose a new interface system implemented by using a support vector machine and a time-multiplexing method. Moreover, bio-feed back process and on-line adaptive pattern recognition mechanism are also considered in the proposed system. Computer experimental results show that the proposed method is effective to recognize the non-stational brain wave signal.