دانلود مقاله انگلیسی رایگان:حرکت به سمت پزشکی از راه دور هوشمند: اندازه گیری بینایی کامپیوتری حرکت انسان - 2022
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  • Moving towards intelligent telemedicine: Computer vision measurement of human movement Moving towards intelligent telemedicine: Computer vision measurement of human movement
    Moving towards intelligent telemedicine: Computer vision measurement of human movement

    دسته بندی:

    بینایی ماشین - Machine vision


    سال انتشار:

    2022


    عنوان انگلیسی مقاله:

    Moving towards intelligent telemedicine: Computer vision measurement of human movement


    ترجمه فارسی عنوان مقاله:

    حرکت به سمت پزشکی از راه دور هوشمند: اندازه گیری بینایی کامپیوتری حرکت انسان


    منبع:

    ScienceDirect- Elsevier- Computers in Biology and Medicine, 147 (2022) 105776: doi:10:1016/j:compbiomed:2022:105776


    نویسنده:

    Renjie Li


    چکیده انگلیسی:

    Background: Telemedicine video consultations are rapidly increasing globally, accelerated by the COVID- 19 pandemic. This presents opportunities to use computer vision technologies to augment clinician visual judgement because video cameras are so ubiquitous in personal devices and new techniques, such as DeepLabCut (DLC) can precisely measure human movement from smartphone videos. However, the accuracy of DLC to track human movements in videos obtained from laptop cameras, which have a much lower FPS, has never been investigated; this is a critical gap because patients use laptops for most telemedicine consultations. Objectives: To determine the validity and reliability of DLC applied to laptop videos to measure finger tapping, a validated test of human movement. Method: Sixteen adults completed finger-tapping tests at 0.5 Hz, 1 Hz, 2 Hz, 3 Hz and at maximal speed. Hand movements were recorded simultaneously by a laptop camera at 30 frames per second (FPS) and by Optotrak, a 3D motion analysis system at 250 FPS. Eight DLC neural network architectures (ResNet50, ResNet101, ResNet152, MobileNetV1, MobileNetV2, EfficientNetB0, EfficientNetB3, EfficientNetB6) were applied to the laptop video and extracted movement features were compared to the ground truth Optotrak motion tracking. Results: Over 96% (529/552) of DLC measures were within +∕−0.5 Hz of the Optotrak measures. At tapping frequencies >4 Hz, there was progressive decline in accuracy, attributed to motion blur associated with the laptop camera’s low FPS. Computer vision methods hold potential for moving us towards intelligent telemedicine by providing human movement analysis during consultations. However, further developments are required to accurately measure the fastest movements.
    keywords: پزشکی از راه دور | ضربه زدن با انگشت | موتور کنترل | کامپیوتری | Telemedicine | DeepLabCut | Finger tapping | Motor control | Computer vision


    سطح: متوسط
    تعداد صفحات فایل pdf انگلیسی: 9
    حجم فایل: 2301 کیلوبایت

    قیمت: رایگان


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