Home / Advanced Search

  • Title/Keywords

  • Author/Affliations

  • Journal

  • Article Type

  • Start Year

  • End Year

Update SearchingClear
  • Articles
  • Online
Search Results (3)
  • Open Access

    ARTICLE

    Study on Real-Time Heart Rate Detection Based on Multi-People

    Qiuyu Hu1, Wu Zeng1,*, Yi Sheng1, Jian Xu1, Weihua Ou2, Ruochen Tan3

    Computer Systems Science and Engineering, Vol.44, No.2, pp. 1397-1408, 2023, DOI:10.32604/csse.2023.027980 - 15 June 2022

    Abstract Heart rate is an important vital characteristic which indicates physical and mental health status. Typically heart rate measurement instruments require direct contact with the skin which is time-consuming and costly. Therefore, the study of non-contact heart rate measurement methods is of great importance. Based on the principles of photoelectric volumetric tracing, we use a computer device and camera to capture facial images, accurately detect face regions, and to detect multiple facial images using a multi-target tracking algorithm. Then after the regional segmentation of the facial image, the signal acquisition of the region of interest is More >

  • Open Access

    ARTICLE

    Heart Rate Detection Based on Facial Video

    Yudan Zhao*, Chaoyu Wang

    Journal of Information Hiding and Privacy Protection, Vol.3, No.3, pp. 121-130, 2021, DOI:10.32604/jihpp.2021.026380 - 07 February 2022

    Abstract Heart rate is an important data reflecting human vital characteristics and an important reference index to describe human physical and mental state. Currently, widely used heart rate measurement devices require direct contact with a person’s skin, which is not suitable for people with burns, delicate skin, newborns and the elderly. Therefore, the research of non-contact heart rate measurement method is of great significance. Based on the basic principle of Photoplethysmography, we use the camera of computer equipment to capture the face image, detect the face region accurately, and detect multiple faces in the image based More >

  • Open Access

    ARTICLE

    Analysis of OSA Syndrome from PPG Signal Using CART-PSO Classifier with Time Domain and Frequency Domain Features

    N. Kins Burk Sunil1, *, R. Ganesan2, B. Sankaragomathi3

    CMES-Computer Modeling in Engineering & Sciences, Vol.118, No.2, pp. 351-375, 2019, DOI:10.31614/cmes.2018.04484

    Abstract Obstructive Sleep Apnea (OSA) is a respiratory syndrome that occurs due to insufficient airflow through the respiratory or respiratory arrest while sleeping and sometimes due to the reduced oxygen saturation. The aim of this paper is to analyze the respiratory signal of a person to detect the Normal Breathing Activity and the Sleep Apnea (SA) activity. In the proposed method, the time domain and frequency domain features of respiration signal obtained from the PPG device are extracted. These features are applied to the Classification and Regression Tree (CART)-Particle Swarm Optimization (PSO) classifier which classifies the More >

Displaying 1-10 on page 1 of 3. Per Page