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Sensors 2017, 17(8), 1776; https://doi.org/10.3390/s17081776

Heart Rate Detection Using Microsoft Kinect: Validation and Comparison to Wearable Devices

Dipartimento di Ingegneria dell’Informazione, Università Politecnica delle Marche via Brecce Bianche 12, Ancona 60131, Italy
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Received: 23 June 2017 / Revised: 28 July 2017 / Accepted: 1 August 2017 / Published: 2 August 2017
(This article belongs to the Special Issue Wearable and Ambient Sensors for Healthcare and Wellness Applications)
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Abstract

Contactless detection is one of the new frontiers of technological innovation in the field of healthcare, enabling unobtrusive measurements of biomedical parameters. Compared to conventional methods for Heart Rate (HR) detection that employ expensive and/or uncomfortable devices, such as the Electrocardiograph (ECG) or pulse oximeter, contactless HR detection offers fast and continuous monitoring of heart activities and provides support for clinical analysis without the need for the user to wear a device. This paper presents a validation study for a contactless HR estimation method exploiting RGB (Red, Green, Blue) data from a Microsoft Kinect v2 device. This method, based on Eulerian Video Magnification (EVM), Photoplethysmography (PPG) and Videoplethysmography (VPG), can achieve performance comparable to classical approaches exploiting wearable systems, under specific test conditions. The output given by a Holter, which represents the gold-standard device used in the test for ECG extraction, is considered as the ground-truth, while a comparison with a commercial smartwatch is also included. The validation process is conducted with two modalities that differ for the availability of a priori knowledge about the subjects’ normal HR. The two test modalities provide different results. In particular, the HR estimation differs from the ground-truth by 2% when the knowledge about the subject’s lifestyle and his/her HR is considered and by 3.4% if no information about the person is taken into account. View Full-Text
Keywords: heart rate; contactless sensing; EVM; Kinect; RGB-D sensors; photoplethysmography; videoplethysmography heart rate; contactless sensing; EVM; Kinect; RGB-D sensors; photoplethysmography; videoplethysmography
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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited (CC BY 4.0).
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Gambi, E.; Agostinelli, A.; Belli, A.; Burattini, L.; Cippitelli, E.; Fioretti, S.; Pierleoni, P.; Ricciuti, M.; Sbrollini, A.; Spinsante, S. Heart Rate Detection Using Microsoft Kinect: Validation and Comparison to Wearable Devices. Sensors 2017, 17, 1776.

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