{"id":325889,"date":"2016-11-22T13:02:56","date_gmt":"2016-11-22T21:02:56","guid":{"rendered":"https:\/\/www.microsoft.com\/en-us\/research\/?post_type=msr-project&#038;p=325889"},"modified":"2023-06-16T13:06:53","modified_gmt":"2023-06-16T20:06:53","slug":"workout","status":"publish","type":"msr-project","link":"https:\/\/www.microsoft.com\/en-us\/research\/project\/workout\/","title":{"rendered":"Workout: Using a Wearable Sensor to Find, Recognize, and Count Repetitive Exercises"},"content":{"rendered":"<p class=\"overviewheadertext\">Although numerous devices exist to track and share exercise routines based on running and walking, these devices offer limited functionality for strength-training exercises. We introduce a system for automatically tracking repetitive exercises \u2013 such as weight training and calisthenics \u2013 via an arm-worn inertial sensor. Our goal is to provide real-time and post-workout feedback, with no user-specific training and no intervention during a workout. Toward this end, we address three challenges:<\/p>\n<p class=\"overviewtext\">(1) Segmenting exercise from intermittent non-exercise periods<br \/>\n(2) Recognizing which exercise is being performed<br \/>\n(3) Counting repetitions<\/p>\n<p class=\"overviewtext\">We present cross-validation results on our training data and results from a study assessing the final system, totaling 114 participants over 146 sessions. We achieve precision and recall greater than 95% in identifying exercise periods, recognition of 99%, 98%, and 96% on circuits of 4, 7, and 13 exercises respectively, and counting that is accurate to \u00b11 repetition 93% of the time. These results suggest that our approach enables a new category of fitness tracking devices.<\/p>\n<p class=\"overviewtext\">The automatic counting portion of this work shipped as part of the <a href=\"https:\/\/www.microsoft.com\/microsoft-band\">Microsoft Band<span class=\"sr-only\"> (opens in new tab)<\/span><\/a>.<\/p>\n<p class=\"overviewtext\">Data from this project is available <a class=\"msr-external-link glyph-append glyph-append-open-in-new-tab glyph-append-xsmall\" href=\"https:\/\/github.com\/microsoft\/Exercise-Recognition-from-Wearable-Sensors\" target=\"_blank\" rel=\"noopener\">on GitHub<span class=\"sr-only\"> (opens in new tab)<\/span><\/a>.<\/p>\n<h3 class=\"overviewtext\">Video:<\/h3>\n<p><iframe loading=\"lazy\" title=\"Workout: Automatic Exercise Analysis\" width=\"500\" height=\"281\" src=\"https:\/\/www.youtube-nocookie.com\/embed\/zs1Xwaaf350?feature=oembed&rel=0\" frameborder=\"0\" allow=\"accelerometer; autoplay; clipboard-write; encrypted-media; gyroscope; picture-in-picture; web-share\" referrerpolicy=\"strict-origin-when-cross-origin\" allowfullscreen><\/iframe><\/p>\n<h3 class=\"overviewtext\" style=\"margin-top: 25px;\">Random images with cool wavy lines:<\/h3>\n<table style=\"border: 0px;\">\n<tbody>\n<tr>\n<td style=\"text-align: center; padding: 10px;\"><img loading=\"lazy\" decoding=\"async\" class=\"alignnone size-full wp-image-325919 aligncenter\" src=\"https:\/\/www.microsoft.com\/en-us\/research\/uploads\/prod\/2016\/11\/workout_ss_250.jpg\" alt=\"workout_ss_250\" width=\"250\" height=\"124\" \/><\/td>\n<td style=\"text-align: center; padding: 10px;\"><img loading=\"lazy\" decoding=\"async\" class=\"size-medium wp-image-325910 aligncenter\" src=\"https:\/\/www.microsoft.com\/en-us\/research\/uploads\/prod\/2016\/11\/reco300-300x148.png\" alt=\"reco300\" width=\"300\" height=\"148\" \/><\/td>\n<\/tr>\n<tr>\n<td style=\"text-align: center; padding: 10px;\"><img loading=\"lazy\" decoding=\"async\" class=\"alignnone size-medium wp-image-325913\" src=\"https:\/\/www.microsoft.com\/en-us\/research\/uploads\/prod\/2016\/11\/signal_300-300x103.png\" alt=\"signal_300\" width=\"300\" height=\"103\" \/><\/td>\n<td style=\"text-align: center; padding: 10px;\"><img loading=\"lazy\" decoding=\"async\" class=\"alignnone size-medium wp-image-325904\" src=\"https:\/\/www.microsoft.com\/en-us\/research\/uploads\/prod\/2016\/11\/peaks300-300x83.png\" alt=\"peaks300\" width=\"300\" height=\"83\" \/><\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n<p>&nbsp;<\/p>\n","protected":false},"excerpt":{"rendered":"<p>Although numerous devices exist to track and share exercise routines based on running and walking, these devices offer limited functionality for strength-training exercises. We introduce a system for automatically tracking repetitive exercises \u2013 such as weight training and calisthenics \u2013 via an arm-worn inertial sensor. Our goal is to provide real-time and post-workout feedback, with [&hellip;]<\/p>\n","protected":false},"featured_media":0,"template":"","meta":{"msr-url-field":"","msr-podcast-episode":"","msrModifiedDate":"","msrModifiedDateEnabled":false,"ep_exclude_from_search":false,"_classifai_error":"","footnotes":""},"research-area":[13556,13554,13553],"msr-locale":[268875],"msr-impact-theme":[],"msr-pillar":[],"class_list":["post-325889","msr-project","type-msr-project","status-publish","hentry","msr-research-area-artificial-intelligence","msr-research-area-human-computer-interaction","msr-research-area-medical-health-genomics","msr-locale-en_us","msr-archive-status-active"],"msr_project_start":"","related-publications":[317630],"related-downloads":[914145],"related-videos":[],"related-groups":[],"related-events":[],"related-opportunities":[],"related-posts":[],"related-articles":[],"tab-content":[],"slides":[],"related-researchers":[{"type":"user_nicename","display_name":"Scott Saponas","user_id":33715,"people_section":"Group 1","alias":"ssaponas"},{"type":"guest","display_name":"Ilya Kelner","user_id":434244,"people_section":"Group 1","alias":""},{"type":"guest","display_name":"Andrew Guillory","user_id":434208,"people_section":"Group 1","alias":""}],"msr_research_lab":[],"msr_impact_theme":[],"_links":{"self":[{"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/msr-project\/325889"}],"collection":[{"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/msr-project"}],"about":[{"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/types\/msr-project"}],"version-history":[{"count":6,"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/msr-project\/325889\/revisions"}],"predecessor-version":[{"id":949929,"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/msr-project\/325889\/revisions\/949929"}],"wp:attachment":[{"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/media?parent=325889"}],"wp:term":[{"taxonomy":"msr-research-area","embeddable":true,"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/research-area?post=325889"},{"taxonomy":"msr-locale","embeddable":true,"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/msr-locale?post=325889"},{"taxonomy":"msr-impact-theme","embeddable":true,"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/msr-impact-theme?post=325889"},{"taxonomy":"msr-pillar","embeddable":true,"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/msr-pillar?post=325889"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}