{"id":168376,"date":"2014-12-01T00:00:00","date_gmt":"2014-12-01T00:00:00","guid":{"rendered":"https:\/\/www.microsoft.com\/en-us\/research\/msr-research-item\/vision-based-body-tracking-turning-kinect-into-a-clinical-tool\/"},"modified":"2018-10-16T21:18:39","modified_gmt":"2018-10-17T04:18:39","slug":"vision-based-body-tracking-turning-kinect-into-a-clinical-tool","status":"publish","type":"msr-research-item","link":"https:\/\/www.microsoft.com\/en-us\/research\/publication\/vision-based-body-tracking-turning-kinect-into-a-clinical-tool\/","title":{"rendered":"Vision-based body tracking: turning Kinect into a clinical tool"},"content":{"rendered":"<div class=\"asset-content\">\n<p><b>Purpose:<\/b> Vision-based body tracking technologies, originally developed for the consumer gaming market, are being repurposed to form the core of a range of innovative healthcare applications in the clinical assessment and rehabilitation of movement ability. Vision-based body tracking has substantial potential, but there are technical limitations. <\/p>\n<p><b>Method:<\/b> We use our \u201cstories from the field\u201d to articulate the challenges and offer examples of how these can be overcome. <\/p>\n<p><b>Results:<\/b> We illustrate that: (1)<b> <\/b>substantial effort is needed to determine the measures and feedback vision-based body tracking should provide, accounting for the practicalities of the technology (e.g. range) as well as new environments (e.g. home). (2) Practical considerations are important when planning data capture so that data is analysable, whether finding ways to support a patient or ensuring everyone does the exercise in the same manner. (3) Home is a place of opportunity for vision-based body tracking, but what we do now in the clinic (e.g. balance tests) or in the home (e.g. play games) will require modifications to achieve capturable, clinically relevant measures. <\/p>\n<p><b>Conclusions:<\/b> This article articulates how vision-based body tracking works and when it does not to continue to inspire our clinical colleagues to imagine new applications. <\/p>\n<p><\/div>\n<p><!-- .asset-content --><\/p>\n","protected":false},"excerpt":{"rendered":"<p>Purpose: Vision-based body tracking technologies, originally developed for the consumer gaming market, are being repurposed to form the core of a range of innovative healthcare applications in the clinical assessment and rehabilitation of movement ability. Vision-based body tracking has substantial potential, but there are technical limitations. Method: We use our \u201cstories from the field\u201d to [&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":""},"msr-content-type":[3],"msr-research-highlight":[],"research-area":[13554],"msr-publication-type":[193715],"msr-product-type":[],"msr-focus-area":[],"msr-platform":[],"msr-download-source":[],"msr-locale":[268875],"msr-post-option":[],"msr-field-of-study":[],"msr-conference":[],"msr-journal":[],"msr-impact-theme":[],"msr-pillar":[],"class_list":["post-168376","msr-research-item","type-msr-research-item","status-publish","hentry","msr-research-area-human-computer-interaction","msr-locale-en_us"],"msr_publishername":"","msr_edition":"Disability and Rehabilitation: Assistive Technology","msr_affiliation":"","msr_published_date":"2014-12-01","msr_host":"","msr_duration":"","msr_version":"","msr_speaker":"","msr_other_contributors":"","msr_booktitle":"","msr_pages_string":"","msr_chapter":"","msr_isbn":"","msr_journal":"Disability and Rehabilitation: Assistive Technology","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":"204556","msr_publicationurl":"http:\/\/informahealthcare.com\/doi\/abs\/10.3109\/17483107.2014.989419","msr_doi":"10.3109\/17483107.2014.989419","msr_publication_uploader":[{"type":"file","title":"DRAT_BodyTracking_authorfinalversion.pdf","viewUrl":"https:\/\/www.microsoft.com\/en-us\/research\/wp-content\/uploads\/2016\/02\/DRAT_BodyTracking_authorfinalversion.pdf","id":204556,"label_id":0},{"type":"url","title":"http:\/\/informahealthcare.com\/doi\/abs\/10.3109\/17483107.2014.989419","viewUrl":false,"id":false,"label_id":0},{"type":"doi","title":"10.3109\/17483107.2014.989419","viewUrl":false,"id":false,"label_id":0}],"msr_related_uploader":"","msr_attachments":[{"id":0,"url":"http:\/\/informahealthcare.com\/doi\/abs\/10.3109\/17483107.2014.989419"},{"id":204556,"url":"https:\/\/www.microsoft.com\/en-us\/research\/wp-content\/uploads\/2016\/02\/DRAT_BodyTracking_authorfinalversion.pdf"}],"msr-author-ordering":[{"type":"user_nicename","value":"cecilym","user_id":31356,"rest_url":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/microsoft-research\/v1\/researchers?person=cecilym"},{"type":"text","value":"Peter Culmer","user_id":0,"rest_url":false},{"type":"user_nicename","value":"hementis","user_id":31995,"rest_url":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/microsoft-research\/v1\/researchers?person=hementis"},{"type":"text","value":"Tamar Pincus","user_id":0,"rest_url":false}],"msr_impact_theme":[],"msr_research_lab":[],"msr_event":[],"msr_group":[],"msr_project":[576045],"publication":[],"video":[],"download":[],"msr_publication_type":"article","related_content":{"projects":[{"ID":576045,"post_title":"Assessing Multiple Sclerosis with Kinect","post_name":"assessing-multiple-sclerosis-with-kinect","post_type":"msr-project","post_date":"2019-03-28 03:44:56","post_modified":"2022-09-06 09:59:49","post_status":"publish","permalink":"https:\/\/www.microsoft.com\/en-us\/research\/project\/assessing-multiple-sclerosis-with-kinect\/","post_excerpt":"ASSESS MS enables a consistent, quantified measure of motor ability using Kinect that is both inexpensive and non-invasive. Using Kinect, the system captures depth videos of neuro-assessment movements performed by patients in a clinical setting with the support of the health professional.","_links":{"self":[{"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/msr-project\/576045"}]}}]},"_links":{"self":[{"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/msr-research-item\/168376"}],"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":2,"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/msr-research-item\/168376\/revisions"}],"predecessor-version":[{"id":534771,"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/msr-research-item\/168376\/revisions\/534771"}],"wp:attachment":[{"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/media?parent=168376"}],"wp:term":[{"taxonomy":"msr-content-type","embeddable":true,"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/msr-content-type?post=168376"},{"taxonomy":"msr-research-highlight","embeddable":true,"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/msr-research-highlight?post=168376"},{"taxonomy":"msr-research-area","embeddable":true,"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/research-area?post=168376"},{"taxonomy":"msr-publication-type","embeddable":true,"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/msr-publication-type?post=168376"},{"taxonomy":"msr-product-type","embeddable":true,"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/msr-product-type?post=168376"},{"taxonomy":"msr-focus-area","embeddable":true,"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/msr-focus-area?post=168376"},{"taxonomy":"msr-platform","embeddable":true,"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/msr-platform?post=168376"},{"taxonomy":"msr-download-source","embeddable":true,"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/msr-download-source?post=168376"},{"taxonomy":"msr-locale","embeddable":true,"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/msr-locale?post=168376"},{"taxonomy":"msr-post-option","embeddable":true,"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/msr-post-option?post=168376"},{"taxonomy":"msr-field-of-study","embeddable":true,"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/msr-field-of-study?post=168376"},{"taxonomy":"msr-conference","embeddable":true,"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/msr-conference?post=168376"},{"taxonomy":"msr-journal","embeddable":true,"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/msr-journal?post=168376"},{"taxonomy":"msr-impact-theme","embeddable":true,"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/msr-impact-theme?post=168376"},{"taxonomy":"msr-pillar","embeddable":true,"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/msr-pillar?post=168376"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}