Automatic Physiotherapy and Rehabilitation System for Lower Body Total Joint Replacement
NCT ID: NCT02324829
Last Updated: 2016-06-20
Study Results
The study team has not published outcome measurements, participant flow, or safety data for this trial yet. Check back later for updates.
Basic Information
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COMPLETED
18 participants
OBSERVATIONAL
2012-11-30
2015-12-31
Brief Summary
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Detailed Description
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A previous version of this experiment on healthy participants has been successfully performed. This study would like to examine the feasibility of this system on rehabilitation subjects, as the movement patterns of a subject in physical rehabilitation may be dramatically different then a healthy subject. No intervention is suggested by the system, as this study is observational.
Conditions
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Study Design
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COHORT
CROSS_SECTIONAL
Study Groups
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Total joint replacement
Patients who has undergone lower body total joint replacement surgery.
No interventions assigned to this group
Eligibility Criteria
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Inclusion Criteria
* Patients with medical complications or other injuries will be not be excluded, as we are interested in seeing the movement profiles of a wide range of people.
* In-patients
Exclusion Criteria
* Out-patients.
* Patients who cannot give explicit consent or understand the physiotherapist's instructions
* Patients who do not speak fluent English
ALL
No
Sponsors
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Toronto Rehabilitation Institute
OTHER
Natural Sciences and Engineering Research Council, Canada
OTHER
University of Waterloo
OTHER
Responsible Party
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Principal Investigators
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Dana Kulic, PhD
Role: PRINCIPAL_INVESTIGATOR
University of Waterloo
Locations
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Toronto Rehabilitation Instititue
Toronto, Ontario, Canada
Countries
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References
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Lin JF, Kulic D. Human pose recovery using wireless inertial measurement units. Physiol Meas. 2012 Dec;33(12):2099-115. doi: 10.1088/0967-3334/33/12/2099. Epub 2012 Nov 23.
Feng-Shun Lin J, Kulic D. Segmenting human motion for automated rehabilitation exercise analysis. Annu Int Conf IEEE Eng Med Biol Soc. 2012;2012:2881-4. doi: 10.1109/EMBC.2012.6346565.
Lin JF, Kulic D. Online Segmentation of Human Motion for Automated Rehabilitation Exercise Analysis. IEEE Trans Neural Syst Rehabil Eng. 2014 Jan;22(1):168-80. doi: 10.1109/TNSRE.2013.2259640. Epub 2013 May 2.
Other Identifiers
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REB 12-025
Identifier Type: OTHER
Identifier Source: secondary_id
ORE 18193
Identifier Type: -
Identifier Source: org_study_id
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