{"id":481389,"date":"2018-04-20T12:37:21","date_gmt":"2018-04-20T19:37:21","guid":{"rendered":"https:\/\/www.microsoft.com\/en-us\/research\/?post_type=msr-research-item&p=481389"},"modified":"2018-10-16T22:23:17","modified_gmt":"2018-10-17T05:23:17","slug":"cardiolens-remote-physiological-monitoring-mixed-reality-environment","status":"publish","type":"msr-research-item","link":"https:\/\/www.microsoft.com\/en-us\/research\/publication\/cardiolens-remote-physiological-monitoring-mixed-reality-environment\/","title":{"rendered":"Cardiolens: Remote Physiological Monitoring in a Mixed Reality Environment"},"content":{"rendered":"

Numerous vital signs can be captured through the measurement of blood flow; however, these signals are not visible to the unaided eye and measurement traditionally requires customized contact sensors. We present Cardiolens – a mixed reality application that enables real-time hands-free measurement and visualization of blood flow and vital signs. The system combines a front-facing camera, remote imaging photoplethysmography software and a heads-up display allowing users to view the physiological state of a person simply by looking at them. Cardiolens provides the wearer with a new way to understand physiology and has applications in healthcare and effective computing.<\/p>\n","protected":false},"excerpt":{"rendered":"

Numerous vital signs can be captured through the measurement of blood flow; however, these signals are not visible to the unaided eye and measurement traditionally requires customized contact sensors. We present Cardiolens – a mixed reality application that enables real-time hands-free measurement and visualization of blood flow and vital signs. The system combines a front-facing […]<\/p>\n","protected":false},"featured_media":0,"template":"","meta":{"msr-url-field":"","msr-podcast-episode":"","msrModifiedDate":"","msrModifiedDateEnabled":false,"ep_exclude_from_search":false,"footnotes":""},"msr-content-type":[3],"msr-research-highlight":[],"research-area":[13554,13553],"msr-publication-type":[193716],"msr-product-type":[],"msr-focus-area":[],"msr-platform":[],"msr-download-source":[],"msr-locale":[268875],"msr-field-of-study":[],"msr-conference":[],"msr-journal":[],"msr-impact-theme":[],"msr-pillar":[],"class_list":["post-481389","msr-research-item","type-msr-research-item","status-publish","hentry","msr-research-area-human-computer-interaction","msr-research-area-medical-health-genomics","msr-locale-en_us"],"msr_publishername":"ACM","msr_edition":"ACM SIGGRAPH 2017 Emerging 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