KMITL

Permanent URI for this communityhttps://dspace.kmitl.ac.th/handle/123456789/1

Browse

Settings

Author: search.filters.author.Jongprasithporn, ManutchanokSubject: search.filters.subject.Smartphone

Search Results

Now showing 1 - 2 of 2
  • Loading...
    Thumbnail Image
    Some of the metrics are blocked by your 
    consent settings
    Item type:Item,
    The use of smartphone for gait analysis
    (2017-06-07)
    Yodpijit, Nantakrit
    ;
    Tavichaiyuth, Nicha
    ;
    Jongprasithporn, Manutchanok
    ;
    Songwongamarit, Chalida
    ;
    Sittiwanchai, Teppakorn
    In today's information-rich environment, one of the most popular devices is a smartphone. Research has shown significant growth in the use of smartphones and apps all over the world. Accelerometer within smartphone is a motion sensor that can be used to detect human movements. Compared to other major vital signs, gait characteristics represent general health status, and can be determined using smartphones. The objective of the current study is to design and develop the alternative technology that can potentially predict health status and reduce healthcare cost. This study uses a smartphone as a wireless accelerometer for quantifying human motion characteristics from four steps of the system design and development (data acquisition operation, feature extraction algorithm, classifier design, and decision making strategy). Findings indicate that it is possible to extract features from a smartphone's accelerometer using a peak detection algorithm. Gait characteristics obtain from the peak detection algorithm include stride time, stance time, swing time and cadence. Applications and limitations of this study are also discussed.
  • Loading...
    Thumbnail Image
    Some of the metrics are blocked by your 
    consent settings
    Item type:Item,
    A smartphone-based real-time simple activity recognition
    (2017-06-07)
    Jongprasithporn, Manutchanok
    ;
    Yodpijit, Nantakrit
    ;
    Srivilai, Rawiphorn
    ;
    Pongsophane, Paweena
    This paper explores a physical activity monitoring application in smartphones. The combination of smartphone application and sensors could perform as a biomedical sensor to monitor physical activities. Thai 3 Axis (TH3AX) was developed as a real-time physical activities monitoring application such as standing, walking, and running. The smartphone was attached to right hip of 10 young, healthy adult subjects to collect accelerometer data to determine threshold range for each activity. After finding thresholds, the results were used as range for a predictive model of activity recognition. The second experiment was scheduled with 6 young healthy subjects performed three physical activities (standing, walking, and running) to evaluate TH3AX application. Then, a diagnostic test was computed to test TH3AX's sensitivity, specificity, and accuracy. Results showed that TH3AX sensitivity, specificity, and accuracy are 0.981, 0.988, and 0.986, respectively.