Automatic Physiotherapy and Rehabilitation System for Lower Body Total Joint Replacement

Lower-body Total Joint Replacement Clinical Trial

Official title:

Automatic Physiotherapy and Rehabilitation System for Lower Body Total Joint Replacement

Clinical Trial Details — Status: Completed

Administrative data

• NCT number: NCT02324829
• Other study ID #: ORE 18193
• Secondary ID: REB 12-025
• Status: Completed
• Phase: N/A
• First received: December 3, 2014
• Last updated: June 16, 2016
• Start date: November 2012
• Est. completion date: December 2015

Study information

• Verified date: June 2016
• Source: University of Waterloo
• Contact: n/a
• Is FDA regulated: No
• Health authority: Canada: Health Canada
• Study type: Observational

Clinical Trial Summary

Physiotherapists spend a large amount of their time with patients observing their rehabilitation techniques. A patient going through rehabilitation exercises are routine and does not necessarily require the attention of the physiotherapist. This research will develop a sensor system that will be strapped onto the patients and will provide feedback on how accurately the exercise is being executed. This will free up the physiotherapist to focus on diagnosis and other tasks that will better utilize the physiotherapist's training. A previous study has shown that this system is feasible for healthy subjects. This study would test to see if this system is extendable to rehabilitation subjects.

Description:

Many of the tasks performed regularly by physiotherapists during any given rehabilitation session are repetitive and do not rely on the physiotherapist's expertise, and could be performed and observed by automated means. The developed system will detect patient body postures and movements with data collected through sensors such as accelerometers. This data will be pattern matched to a predetermined movement pattern and feedback will be provided for patients regarding accuracy of their exercises. This data can be logged for the physiotherapist to examine at a later time. By automating this component of a rehabilitation session, the system will allow the physiotherapist to focus diagnosis and other tasks that will better utilize their training. The specific application for this prototype will be post-operative knee/hip replacement patients, so all devices must be non-invasive and must not interfere with normal recovery processes.

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.

Recruitment information / eligibility

• Status: Completed
• Enrollment: 18
• Est. completion date: December 2015
• Est. primary completion date: July 2013
• Accepts healthy volunteers: No
• Gender: Both
• Age group: N/A and older

Eligibility

Inclusion Criteria:

• Any patient who has had hip and/or knee total joint replacement and requires rehabilitation, and are assessed by physiotherapists as likely able to finish their rehabilitation cycle and be discharged to home.

• 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:

• Patients at risk of developing serious postoperative complications, such as an infection, myocardial infarction or anything that requires subsequent surgery, they may be excluded.

• Out-patients.

• Patients who cannot give explicit consent or understand the physiotherapist's instructions

• Patients who do not speak fluent English

Study Design

Observational Model: Cohort, Time Perspective: Cross-Sectional

Related Conditions & MeSH terms

• Lower-body Total Joint Replacement

Locations

Country	Name	City	State
Canada	Toronto Rehabilitation Instititue	Toronto	Ontario

Sponsors (3)

Lead Sponsor	Collaborator
University of Waterloo	Natural Sciences and Engineering Research Council, Canada, Toronto Rehabilitation Institute

Country where clinical trial is conducted

Canada, 

References & Publications (3)

Feng-Shun Lin J, Kulic D. Segmenting human motion for automated rehabilitation exercise analysis. Conf Proc IEEE Eng Med Biol Soc. 2012;2012:2881-4. doi: 10.1109/EMBC.2012.6346565. — View Citation

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. — View Citation

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. — View Citation

Outcome

Type	Measure	Description	Time frame	Safety issue
Primary	Joint angle assessment	Inertial measurement unit (IMU) data will be translated to joint angles via extended Kalman filter and kinematic modeling.	2 weeks	No
Secondary	Motion segmentation and identification	The joint angle data will be processed to automatically segment and identify rehabilitation motion.	2 weeks	No