{"id":661485,"date":"2020-05-21T14:17:00","date_gmt":"2020-05-21T21:17:00","guid":{"rendered":"https:\/\/www.microsoft.com\/en-us\/research\/?post_type=msr-research-item&p=661485"},"modified":"2020-05-21T14:28:27","modified_gmt":"2020-05-21T21:28:27","slug":"stress-monitoring-using-multimodal-bio-sensing-headset","status":"publish","type":"msr-research-item","link":"https:\/\/www.microsoft.com\/en-us\/research\/publication\/stress-monitoring-using-multimodal-bio-sensing-headset\/","title":{"rendered":"Stress Monitoring using Multimodal Bio-sensing Headset"},"content":{"rendered":"

Exposure to continuous stress can have a negative impact on a person’s mental and physical well-being. Stress monitoring and management, with the aim to analyze or mitigate the effects of stress, are an active area of research. A promising approach for detecting stress is by measuring bio-signals such as an electroencephalogram (EEG) or an electrocardiogram (ECG). In this study, we introduce a wearable in- and over-ear device that measures EEG and ECG signals simultaneously. The device is composed of dry and soft sensing electrodes which are conformally integrated on the surface of earbuds. We carried out a pilot study exposing test subjects to three standard stressors (stroop, memory search, and mental arithmetic) while measuring their EEG and ECG signals. Preliminary results indicate the feasibility of classifying various stress conditions using a convolutional neural network.<\/p>\n

\"Wearable<\/p>\n","protected":false},"excerpt":{"rendered":"

Exposure to continuous stress can have a negative impact on a person’s mental and physical well-being. Stress monitoring and management, with the aim to analyze or mitigate the effects of stress, are an active area of research. A promising approach for detecting stress is by measuring bio-signals such as an electroencephalogram (EEG) or an electrocardiogram […]<\/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":[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-661485","msr-research-item","type-msr-research-item","status-publish","hentry","msr-research-area-medical-health-genomics","msr-locale-en_us"],"msr_publishername":"","msr_edition":"","msr_affiliation":"","msr_published_date":"2020-4-1","msr_host":"","msr_duration":"","msr_version":"","msr_speaker":"","msr_other_contributors":"","msr_booktitle":"","msr_pages_string":"","msr_chapter":"","msr_isbn":"","msr_journal":"","msr_volume":"","msr_number":"","msr_editors":"","msr_series":"","msr_issue":"","msr_organization":"","msr_how_published":"","msr_notes":"","msr_highlight_text":"","msr_release_tracker_id":"","msr_original_fields_of_study":"","msr_download_urls":"","msr_external_url":"","msr_secondary_video_url":"","msr_longbiography":"","msr_microsoftintellectualproperty":1,"msr_main_download":"","msr_publicationurl":"","msr_doi":"","msr_publication_uploader":[{"type":"file","viewUrl":"https:\/\/www.microsoft.com\/en-us\/research\/uploads\/prod\/2020\/05\/2020_CHI_LBW_In_ear_Stress_Monitoring.pdf","id":"661488","title":"2020_chi_lbw_in_ear_stress_monitoring","label_id":"243132","label":0},{"type":"url","viewUrl":"false","id":"false","title":"https:\/\/dl.acm.org\/doi\/abs\/10.1145\/3334480.3382891","label_id":"243109","label":0}],"msr_related_uploader":"","msr_attachments":[{"id":661488,"url":"https:\/\/www.microsoft.com\/en-us\/research\/uploads\/prod\/2020\/05\/2020_CHI_LBW_In_ear_Stress_Monitoring.pdf"}],"msr-author-ordering":[{"type":"text","value":"Joong Hoon Lee","user_id":0,"rest_url":false},{"type":"user_nicename","value":"Hannes Gamper","user_id":31943,"rest_url":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/microsoft-research\/v1\/researchers?person=Hannes Gamper"},{"type":"user_nicename","value":"Ivan Tashev","user_id":32127,"rest_url":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/microsoft-research\/v1\/researchers?person=Ivan Tashev"},{"type":"text","value":"Steven Dong","user_id":0,"rest_url":false},{"type":"user_nicename","value":"Siyuan Ma","user_id":35419,"rest_url":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/microsoft-research\/v1\/researchers?person=Siyuan Ma"},{"type":"text","value":"Jacquelin Remaley","user_id":0,"rest_url":false},{"type":"text","value":"James D. Holbery","user_id":0,"rest_url":false},{"type":"user_nicename","value":"Sang Ho Yoon","user_id":37248,"rest_url":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/microsoft-research\/v1\/researchers?person=Sang Ho Yoon"}],"msr_impact_theme":[],"msr_research_lab":[199565,212740],"msr_event":[],"msr_group":[144923],"msr_project":[661380],"publication":[],"video":[],"download":[],"msr_publication_type":"inproceedings","_links":{"self":[{"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/msr-research-item\/661485"}],"collection":[{"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/msr-research-item"}],"about":[{"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/types\/msr-research-item"}],"version-history":[{"count":1,"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/msr-research-item\/661485\/revisions"}],"predecessor-version":[{"id":661494,"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/msr-research-item\/661485\/revisions\/661494"}],"wp:attachment":[{"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/media?parent=661485"}],"wp:term":[{"taxonomy":"msr-content-type","embeddable":true,"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/msr-content-type?post=661485"},{"taxonomy":"msr-research-highlight","embeddable":true,"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/msr-research-highlight?post=661485"},{"taxonomy":"msr-research-area","embeddable":true,"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/research-area?post=661485"},{"taxonomy":"msr-publication-type","embeddable":true,"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/msr-publication-type?post=661485"},{"taxonomy":"msr-product-type","embeddable":true,"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/msr-product-type?post=661485"},{"taxonomy":"msr-focus-area","embeddable":true,"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/msr-focus-area?post=661485"},{"taxonomy":"msr-platform","embeddable":true,"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/msr-platform?post=661485"},{"taxonomy":"msr-download-source","embeddable":true,"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/msr-download-source?post=661485"},{"taxonomy":"msr-locale","embeddable":true,"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/msr-locale?post=661485"},{"taxonomy":"msr-field-of-study","embeddable":true,"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/msr-field-of-study?post=661485"},{"taxonomy":"msr-conference","embeddable":true,"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/msr-conference?post=661485"},{"taxonomy":"msr-journal","embeddable":true,"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/msr-journal?post=661485"},{"taxonomy":"msr-impact-theme","embeddable":true,"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/msr-impact-theme?post=661485"},{"taxonomy":"msr-pillar","embeddable":true,"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/msr-pillar?post=661485"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}