phat 16(7): e3

Research Article

Mauka-Mauka : Measuring and Predicting Opportunities for Webcam-based Heart Rate Sensing in Workplace Environment

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  • @ARTICLE{10.4108/eai.28-9-2015.2261492,
        author={Mridula Singh and Abhishek Kumar and Kuldeep Yadav and Himanshu Madhu and Tridib Mukherjee},
        title={Mauka-Mauka : Measuring and Predicting Opportunities for Webcam-based Heart Rate Sensing in Workplace Environment},
        journal={EAI Endorsed Transactions on Pervasive Health and Technology},
        volume={2},
        number={7},
        publisher={ACM},
        journal_a={PHAT},
        year={2015},
        month={12},
        keywords={webcam based heart rate sensing, pervasive and unobtrusive sensing, wellness programs, workplace environment},
        doi={10.4108/eai.28-9-2015.2261492}
    }
    
  • Mridula Singh
    Abhishek Kumar
    Kuldeep Yadav
    Himanshu Madhu
    Tridib Mukherjee
    Year: 2015
    Mauka-Mauka : Measuring and Predicting Opportunities for Webcam-based Heart Rate Sensing in Workplace Environment
    PHAT
    EAI
    DOI: 10.4108/eai.28-9-2015.2261492
Mridula Singh1,*, Abhishek Kumar1, Kuldeep Yadav1, Himanshu Madhu1, Tridib Mukherjee1
  • 1: Xerox Research Centre, India
*Contact email: mridula.singh@xerox.com

Abstract

Prolonged sitting and physical inactivity at workplace often lead to various health risks such as diabetes, heart attack, cancer etc. Many organizations are investing in wellness programs to ensure the well-being of their employees. Generally wearable devices are used in such wellness programs to detect health problems of employees, but studies have shown that wearables do not result in sustained adoption. Heart rate measurement has emerged as an effective tool to detect various ailments such as anxiety, stress, cardiovascular diseases etc. There are pre-existing techniques that use webcam feed to sense heart rate subject to some experimental constraints like stillness of face, light illumination etc. In this paper, we show that in-situ opportunities can be found and predicted for webcam based heart rate sensing in the workplace environment by analyzing data from unobtrusive sensors in a pervasive manner.