{"id":{"repo_id":"gmu","oai_identifier":"oai:MARS:1920/10474"},"canonical_url":"https://search.dev.ndltd.org/etd/gmu/oai:MARS:1920/10474","repository":{"repo_id":"gmu","name":"George Mason University","base_url":"https://mars.gmu.edu/server/oai/request"},"display":{"title":"Visible Spectrum Based Non-Contact Detection and Characterization of Blood Wave Signal Dynamics and Applications in Stress Detection","abstract":"Stress is a major health concern that not only compromises our quality of life, but also affects our health and well-being. Despite its importance, our ability to objectively detect and quantify stress in a real-time, non-invasive manner is limited. This capability would have a wide variety of medical, military, and security applications. Under the dissertation research, we have developed a pipeline of image and signal processing algorithms for such a capability, which includes remote blood wave (BW) signal detection based on minor color intensity fluctuations in visible spectrum videos of the human skin during the cardiac cycle, and physiological stress measurements based on the temporal variability in these remotely detected cardiac signals.","abstract_html":"Stress is a major health concern that not only compromises our quality of life, but also affects our health and well-being. Despite its importance, our ability to objectively detect and quantify stress in a real-time, non-invasive manner is limited. This capability would have a wide variety of medical, military, and security applications. Under the dissertation research, we have developed a pipeline of image and signal processing algorithms for such a capability, which includes remote blood wave (BW) signal detection based on minor color intensity fluctuations in visible spectrum videos of the human skin during the cardiac cycle, and physiological stress measurements based on the temporal variability in these remotely detected cardiac signals.","abstract_has_math":false,"creators":["Kaur, Balvinder"],"institution":null,"degree_name":null,"degree_level":null,"degree_discipline":null,"degree_department":null,"school":null,"contributors":[],"advisors":[],"committee_chairs":[],"committee_members":[],"year":2016,"date_issued":"2016","date_published":"2016","updated_at":"2026-07-27T19:51:56Z","subjects":["Electrical engineering","Biomedical engineering","Philosophy","Non-contact Blood Wave Detection","Non-contact Differential Pulse Transit Time","Non-contact Heart Rate Variability","Non-contact Stress Detection","Visible Spectrum based Camera"],"languages":[],"rights":[],"rights_urls":[],"identifier_entries":[{"key":"dc:identifier","label":"Identifier","values":["hdl:1920/10474"],"render_values":[{"text":"hdl:1920/10474","href":null,"code":true}]}]},"links":{"outbound_url":null,"outbound_label":null,"outbound_source":null},"metadata_groups":[{"id":"academic_context","label":"Academic Context","entries":[{"key":"dc:date.issued","label":"Date","values":["2016"]},{"key":"dc:type","label":"Dc Type","values":["Dissertation"]}]},{"id":"subjects_keywords","label":"Subjects and Keywords","entries":[{"key":"dc:subject","label":"Dc Subject","values":["Electrical engineering","Biomedical engineering","Philosophy","Non-contact Blood Wave Detection","Non-contact Differential Pulse Transit Time","Non-contact Heart Rate Variability","Non-contact Stress Detection","Visible Spectrum based Camera"]}]},{"id":"identifiers","label":"Identifiers","entries":[{"key":"dc:identifier","label":"Identifier","values":["hdl:1920/10474"]}]},{"id":"additional","label":"Additional Metadata","entries":[{"key":"dc:description.other","label":"Dc Description Other","values":["Stress is a major health concern that not only compromises our quality of life, but also affects our health and well-being. Despite its importance, our ability to objectively detect and quantify stress in a real-time, non-invasive manner is limited. This capability would have a wide variety of medical, military, and security applications. Under the dissertation research, we have developed a pipeline of image and signal processing algorithms for such a capability, which includes remote blood wave (BW) signal detection based on minor color intensity fluctuations in visible spectrum videos of the human skin during the cardiac cycle, and physiological stress measurements based on the temporal variability in these remotely detected cardiac signals."]},{"key":"dc:title","label":"Title","values":["Visible Spectrum Based Non-Contact Detection and Characterization of Blood Wave Signal Dynamics and Applications in Stress Detection"]}]}],"canonical_facts":{"dc:date.issued":["2016"],"dc:description.other":["Stress is a major health concern that not only compromises our quality of life, but also affects our health and well-being. Despite its importance, our ability to objectively detect and quantify stress in a real-time, non-invasive manner is limited. This capability would have a wide variety of medical, military, and security applications. Under the dissertation research, we have developed a pipeline of image and signal processing algorithms for such a capability, which includes remote blood wave (BW) signal detection based on minor color intensity fluctuations in visible spectrum videos of the human skin during the cardiac cycle, and physiological stress measurements based on the temporal variability in these remotely detected cardiac signals."],"dc:identifier":["hdl:1920/10474"],"dc:subject":["Electrical engineering","Biomedical engineering","Philosophy","Non-contact Blood Wave Detection","Non-contact Differential Pulse Transit Time","Non-contact Heart Rate Variability","Non-contact Stress Detection","Visible Spectrum based Camera"],"dc:title":["Visible Spectrum Based Non-Contact Detection and Characterization of Blood Wave Signal Dynamics and Applications in Stress Detection"],"dc:type":["Dissertation"]},"updated_at":"2026-07-27T19:51:56Z"}