Wireless Mobile Communication and Healthcare. Second International ICST Conference, MobiHealth 2011, Kos Island, Greece, October 5-7, 2011. Revised Selected Papers

Research Article

Hybrid Vital Sensor of Health Monitoring System for the Elderly

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  • @INPROCEEDINGS{10.1007/978-3-642-29734-2_45,
        author={Dong Shin and Ji Song and Se Joo and Soo Huh},
        title={Hybrid Vital Sensor of Health Monitoring System for the Elderly},
        proceedings={Wireless Mobile Communication and Healthcare. Second International ICST Conference, MobiHealth 2011, Kos Island, Greece, October 5-7, 2011. Revised Selected Papers},
        proceedings_a={MOBIHEALTH},
        year={2012},
        month={10},
        keywords={Hybrid Vital Sensor Health Monitoring},
        doi={10.1007/978-3-642-29734-2_45}
    }
    
  • Dong Shin
    Ji Song
    Se Joo
    Soo Huh
    Year: 2012
    Hybrid Vital Sensor of Health Monitoring System for the Elderly
    MOBIHEALTH
    Springer
    DOI: 10.1007/978-3-642-29734-2_45
Dong Shin1,*, Ji Song2,*, Se Joo3,*, Soo Huh3,*
  • 1: Asan Medical Center
  • 2: SooEe Electronics Co. SeongNam
  • 3: University of Ulsan College of Medicine
*Contact email: kbread@amc.seoul.kr, jhsong@sooee.co.kr, skjoo@amc.seoul.kr, sjhuh@amc.seoul.kr

Abstract

There are many sensors to monitor vital signs in u-Healthcare system. These vital sensors including ECG, PPG, blood pressure sensor spend heavy processing resource and costs. We propose and developing a new type of hybrid vital sensor. We combine accelerometer and PPG module and control two basic sensors with classified situations. So, we can monitor vital signs more compactly, inexpensively and conveniently using our hybrid sensor. We measured the activity using 3-axis accelerometer and measured the heart rate and oxygen saturation using pulse oxymeter. The major problem of pulse oxymeter is motion artifact. But we suggested a new method using the combination of these two sensors. In case of active motion, we used and analyzed the accelerometer signal and withdraw the pulse oxymeter signal. In case of no activity, we adopt pulse oxymeter signal which has no motion artifacts. The important thing is to categorize activity patterns such as normal or abnormal activity. We categorized activities to 4 patterns which are normal activity, no activity(resting), sleeping and abnormal state. When the device detects abnormal condition, it sends a short message to server and then connected to the u-Healthcare center or emergency center.