Accuracy Comparison: Optoelectronic Motion Capture and Markerless System (OPR)

Accuracy of Markerless Motion Analysis in Comparison With Optoelectronic Motion Capture System

The purpose of this study was to assess the Openpose reliability to measure kinematics and spatiotemporal gait parameters and to evaluate the minimum technical requirements. This analysis used video and optoelectronic motion capture simultaneously recorded. We assessed more of 20 subject with different motor gait impairments

Study Overview

• Status: Active, not recruiting
• Conditions: Motor Disorders; Children, Adult
• Intervention / Treatment: Other: Measure gait spatiotemporal parameters and kinematics from markerless system; Other: Measure gait spatiotemporal parameters and kinematics from optoelectronic system; Other: Quantify tip toe step during gait from kinematic

Detailed Description

Marker-based Optical motion tracking is the gold standard in gait analysis, but today, markerless solutions are growing rapidly. Treatment of physical impairments could improve if supported with reliable motion capture. Moreover, the use of markerless technology offers numerous advantages for working with pediatric populations under various conditions. In this paper, we assess the Openpose reliability to measure kinematics and spatiotemporal gait parameters and to evaluate the minimum technical requirements., in a population of children with and without gait impairments. Validating markerless methods can open the way for new motion capture techniques and enhance the accessibility of kinematic measurements and improve the treatment of physical impairments.

• Study Type: Observational
• Enrollment (Actual): 25

Contacts and Locations

Study Locations

• Italy
  • Italy
    • Bosisio Parini, Italy, Italy, 22037
      • IRCCS E. Medea

Participation Criteria

Eligibility Criteria

• Ages Eligible for Study: Child; Adult; Older Adult
• Accepts Healthy Volunteers: Yes

• Sampling Method: Probability Sample

Study Population

This study includes subjects who previously underwent a functional motor assessment using the SMART DX 100 system at the IRCCS Eugenio Medea Institute. The sample comprises both healthy individuals and those with walking difficulties, all aged over 4 years.

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?

Number of groups / cohorts

5

Cohorts and Interventions

Group / Cohort	Intervention / Treatment
Healthy subjects; This group includes healthy subjects over 4 years of age; with the ability to walk independently without walking aids and/or orthoses.	Other: Measure gait spatiotemporal parameters and kinematics from markerless system; 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.; Other: Measure gait spatiotemporal parameters and kinematics from optoelectronic system; 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 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.	Other: Measure gait spatiotemporal parameters and kinematics from markerless system; 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.; Other: Measure gait spatiotemporal parameters and kinematics from optoelectronic system; 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.	Other: Measure gait spatiotemporal parameters and kinematics from markerless system; 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.; Other: Measure gait spatiotemporal parameters and kinematics from optoelectronic system; 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.	Other: Measure gait spatiotemporal parameters and kinematics from markerless system; 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.; Other: Measure gait spatiotemporal parameters and kinematics from optoelectronic system; 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.
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.	Other: Measure gait spatiotemporal parameters and kinematics from markerless system; 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.; Other: Quantify tip toe step during gait from kinematic; The kinematic features calculated are used to identify and count the number of tip toe steps during gait or standing

What is the study measuring?

Primary Outcome Measures

Outcome Measure	Measure Description	Time Frame
Absolute Error	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	Through study completion, an average of 1 year
intraclass correlation coefficients	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.	Through study completion, an average of 1 year
cross-correlation coefficients	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.	Through study completion, an average of 1 year

Collaborators and Investigators

• Sponsor: IRCCS Eugenio Medea
• Investigators: Principal Investigator: Giuseppe Andreoni, IRCCS E.Medea

Study record dates

Study Major Dates

• Study Start (Actual): May 15, 2024
• Primary Completion (Estimated): September 24, 2026
• Study Completion (Estimated): September 24, 2026

Study Registration Dates

• First Submitted: August 5, 2024
• First Submitted That Met QC Criteria: August 5, 2024
• First Posted (Actual): August 9, 2024

Study Record Updates

• Last Update Posted (Actual): February 27, 2026
• Last Update Submitted That Met QC Criteria: February 25, 2026
• Last Verified: February 1, 2026

More Information

Terms related to this study

• Keywords: Kinematic; Markerless; OpenPose
• Additional Relevant MeSH Terms: Mental Disorders; Motor Disorders
• Other Study ID Numbers: GIP1121

Drug and device information, study documents

• Studies a U.S. FDA-regulated drug product: No
• Studies a U.S. FDA-regulated device product: No
• product manufactured in and exported from the U.S.: No