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Cost-Effective Solution of Remote Photoplethysmography Capable of Real-Time, Multi-Subject Monitoring with Social Distancing.
Huang, Hen-Wei; Rupp, Philip; Chen, Jack; Kemkar, Abhijay; Khandelwal, Naitik; Ballinger, Ian; Chai, Peter; Traverso, Giovanni.
  • Huang HW; Division of Gastroenterology, Brigham & Women's Hospital, Harvard Medical School, Boston, MA 02115 USA.
  • Rupp P; The Koch Institute for Integrative Cancer Research, Massachusetts Institute of Technology, Cambridge, MA 02142 USA.
  • Chen J; Department of Mechanical Engineering, Massachusetts Institute of Technology, Cambridge, MA 02139 USA.
  • Kemkar A; Division of Gastroenterology, Brigham & Women's Hospital, Harvard Medical School, Boston, MA 02115 USA.
  • Khandelwal N; Division of Gastroenterology, Brigham & Women's Hospital, Harvard Medical School, Boston, MA 02115 USA.
  • Ballinger I; Division of Gastroenterology, Brigham & Women's Hospital, Harvard Medical School, Boston, MA 02115 USA.
  • Chai P; Division of Gastroenterology, Brigham & Women's Hospital, Harvard Medical School, Boston, MA 02115 USA.
  • Traverso G; Division of Gastroenterology, Brigham & Women's Hospital, Harvard Medical School, Boston, MA 02115 USA.
Proc IEEE Sens ; 20222022.
Article in English | MEDLINE | ID: covidwho-2171071
ABSTRACT
Recent advances in remote-photoplethysmography (rPPG) have enabled the measurement of heart rate (HR), oxygen saturation (SpO2), and blood pressure (BP) in a fully contactless manner. These techniques are increasingly applied clinically given a desire to minimize exposure to individuals with infectious symptoms. However, accurate rPPG estimation often leads to heavy loading in computation that either limits its real-time capacity or results in a costly setup. Additionally, acquiring rPPG while maintaining protective distance would require high resolution cameras to ensure adequate pixels coverage for the region of interest, increasing computational burden. Here, we propose a cost-effective platform capable of the real-time, continuous, multi-subject monitoring while maintaining social distancing. The platform is composed of a centralized computing unit and multiple low-cost wireless cameras. We demonstrate that the central computing unit is able to simultaneously handle continuous rPPG monitoring of five subjects with social distancing without compromising the frame rate and rPPG accuracy.
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Full text: Available Collection: International databases Database: MEDLINE Type of study: Experimental Studies / Prognostic study Language: English Year: 2022 Document Type: Article

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Full text: Available Collection: International databases Database: MEDLINE Type of study: Experimental Studies / Prognostic study Language: English Year: 2022 Document Type: Article