Accuracy Comparison: Optoelectronic Motion Capture and Markerless System (OPR)
Accuracy of Markerless Motion Analysis in Comparison With Optoelectronic Motion Capture System
Study Overview
Status
Status
Conditions
Conditions
Intervention / Treatment
Intervention / Treatment
Detailed Description
Study Type
Study Type
Enrollment (Actual)
Enrollment
Contacts and Locations
Study Locations
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-
Italy
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Bosisio Parini, Italy, Italy, 22037
- IRCCS E. Medea
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-
Participation Criteria
Eligibility Criteria
Eligibility Criteria
Ages Eligible for Study
- Child
- Adult
- Older Adult
Accepts Healthy Volunteers
Sampling Method
Study Population
Description
Inclusion Criteria:
- Age over 4 years;
- Ability to walk independently without walking aids and/or orthoses.
Exclusion Criteria:
- Inability to walk independently and safely for short distances without walking aids and/or orthoses.
Study Plan
How is the study designed?
Design Details
Number of groups / cohorts
Cohorts and Interventions
Group / CohortGroup / Cohort |
Intervention / TreatmentIntervention / Treatment |
|---|---|
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Healthy subjects
This group includes healthy subjects over 4 years of age; with the ability to walk independently without walking aids and/or orthoses.
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The two videos were elaborated using OpenPose that returns a set of 25 2D keypoints coordinates for body pose estimation for each video.
Key-points were located in relevant body landmarks and it were used to determine the 2D Cartesian coordinates on the sagittal plane and on the frontal plane.
The data calculated with routines were filtered and interpolated in case of missing data.
With respect to kinematic parameters, the segment and joint angles were measured from the estimated feature points of each joint.
Spatiotemporal gait parameters were calculated using successive heel strike and toe-off events.
The raw data acquired from motion capture system were processed with Smart Analyzer software (BTS Bioengineering, Milano, Italy).
First, the 3D data were filtered and interpolated in case of missing data for short time.
Then spatial-temporal parameters (cycle duration, cadence, gait speed, stance phase, swing phase, double-support phase, stride length and step width) and conventional kinematic parameters of traditional Davis marker-set protocols were computed.
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Subjects with a diagnosis of cerebral palsy and right hemiplegia
This group includes subjects with a diagnosis of cerebral palsy and right hemiplegia over 4 years of age; with the ability to walk independently without walking aids and/or orthoses.
|
The two videos were elaborated using OpenPose that returns a set of 25 2D keypoints coordinates for body pose estimation for each video.
Key-points were located in relevant body landmarks and it were used to determine the 2D Cartesian coordinates on the sagittal plane and on the frontal plane.
The data calculated with routines were filtered and interpolated in case of missing data.
With respect to kinematic parameters, the segment and joint angles were measured from the estimated feature points of each joint.
Spatiotemporal gait parameters were calculated using successive heel strike and toe-off events.
The raw data acquired from motion capture system were processed with Smart Analyzer software (BTS Bioengineering, Milano, Italy).
First, the 3D data were filtered and interpolated in case of missing data for short time.
Then spatial-temporal parameters (cycle duration, cadence, gait speed, stance phase, swing phase, double-support phase, stride length and step width) and conventional kinematic parameters of traditional Davis marker-set protocols were computed.
|
|
Subjects with a diagnosis of cerebral palsy and left hemiplegia
This group includes subjects with a diagnosis of cerebral palsy and left hemiplegia over 4 years of age; with the ability to walk independently without walking aids and/or orthoses.
|
The two videos were elaborated using OpenPose that returns a set of 25 2D keypoints coordinates for body pose estimation for each video.
Key-points were located in relevant body landmarks and it were used to determine the 2D Cartesian coordinates on the sagittal plane and on the frontal plane.
The data calculated with routines were filtered and interpolated in case of missing data.
With respect to kinematic parameters, the segment and joint angles were measured from the estimated feature points of each joint.
Spatiotemporal gait parameters were calculated using successive heel strike and toe-off events.
The raw data acquired from motion capture system were processed with Smart Analyzer software (BTS Bioengineering, Milano, Italy).
First, the 3D data were filtered and interpolated in case of missing data for short time.
Then spatial-temporal parameters (cycle duration, cadence, gait speed, stance phase, swing phase, double-support phase, stride length and step width) and conventional kinematic parameters of traditional Davis marker-set protocols were computed.
|
|
Subjects with a diagnosis of spastic paraparesis
TThis group includes subjects with a diagnosis of spastic paraparesis over 4 years of age; with the ability to walk independently without walking aids and/or orthoses.
|
The two videos were elaborated using OpenPose that returns a set of 25 2D keypoints coordinates for body pose estimation for each video.
Key-points were located in relevant body landmarks and it were used to determine the 2D Cartesian coordinates on the sagittal plane and on the frontal plane.
The data calculated with routines were filtered and interpolated in case of missing data.
With respect to kinematic parameters, the segment and joint angles were measured from the estimated feature points of each joint.
Spatiotemporal gait parameters were calculated using successive heel strike and toe-off events.
The raw data acquired from motion capture system were processed with Smart Analyzer software (BTS Bioengineering, Milano, Italy).
First, the 3D data were filtered and interpolated in case of missing data for short time.
Then spatial-temporal parameters (cycle duration, cadence, gait speed, stance phase, swing phase, double-support phase, stride length and step width) and conventional kinematic parameters of traditional Davis marker-set protocols were computed.
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|
healthy children mimic gesture
This group includes a sample of healthy subjects who mimic the chimney tip typical of some diseases such as cerebral palsy and autism.
|
The two videos were elaborated using OpenPose that returns a set of 25 2D keypoints coordinates for body pose estimation for each video.
Key-points were located in relevant body landmarks and it were used to determine the 2D Cartesian coordinates on the sagittal plane and on the frontal plane.
The data calculated with routines were filtered and interpolated in case of missing data.
With respect to kinematic parameters, the segment and joint angles were measured from the estimated feature points of each joint.
Spatiotemporal gait parameters were calculated using successive heel strike and toe-off events.
The kinematic features calculated are used to identify and count the number of tip toe steps during gait or standing
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What is the study measuring?
Primary Outcome Measures
Primary Outcome Measures
Outcome Measure |
Measure Description |
Time Frame |
|---|---|---|
|
Absolute Error
Time Frame: Through study completion, an average of 1 year
|
Absolute errors were calculated for the kinematics parameters and for each spatiotemporal variable by taking the absolute value after subtracting the values obtained using pose estimation methods from the value measured using markerbased motion capture
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Through study completion, an average of 1 year
|
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intraclass correlation coefficients
Time Frame: Through study completion, an average of 1 year
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To confirm whether the data obtained by OpenPose agreed with the data from the optoelectronic system, investigators calculated the ICCs (two-way mixed effects model, absolute agreement, average measurements) between the spatiotemporal and kinematic data from both systems.
The ICC values were interpreted as follows: poor agreement for ICC < 0.5, moderate agreement for values between 0.5 and 0.75, good agreement for values between 0.75 and 0.9, and excellent agreement for values greater than 0.90.
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Through study completion, an average of 1 year
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cross-correlation coefficients
Time Frame: Through study completion, an average of 1 year
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The cross-correlation coefficients (CCC) between both systems were used to evaluate the similarity of angles during the gait cycle.
The CCC values were interpreted as follows: weak or no coupling for values between -0.3 and 0.3, moderate coupling for values between 0.3 and 0.7 or -0.7 and -0.3, and strong coupling for values greater than 0.7 or less than -0.7.
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Through study completion, an average of 1 year
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Collaborators and Investigators
Sponsor
Sponsor
Investigators
Investigators
- Principal Investigator: Giuseppe Andreoni, IRCCS E.Medea
Study record dates
Study Major Dates
Study Start (Actual)
Study Start
Primary Completion (Estimated)
Primary Completion
Study Completion (Estimated)
Study Completion
Study Registration Dates
First Submitted
First Submitted
First Submitted That Met QC Criteria
First Submitted That Met QC Criteria
First Posted (Actual)
First Posted
Study Record Updates
Last Update Posted (Actual)
Last Update Posted
Last Update Submitted That Met QC Criteria
Last Update Submitted That Met QC Criteria
Last Verified
Last Verified
More Information
Terms related to this study
Keywords
Additional Relevant MeSH Terms
Other Study ID Numbers
Other Study ID Numbers
- GIP1121
Drug and device information, study documents
Studies a U.S. FDA-regulated drug product
Studies a U.S. FDA-regulated device product
product manufactured in and exported from the U.S.
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