Multimodal Motion Capture Toolbox for Enhanced Analysis of Intersegmental Coordination in Children with Cerebral Palsy and Typically Developing

Summary

This study introduces a toolbox combining motion capture technologies to analyze kinematic signals and quantify full-body coordinative patterns with angle-angle plots. Designed to overcome challenges of traditional marker-based systems, the toolbox supports flexibility across research, clinical, and field settings, advancing individualized care and functional assessments for children with motor disabilities.

Abstract

Three-dimensional marker-based motion capture systems are the gold standard for evaluating kinematic patterns in human movement, offering precise quantification of segment and joint positions. However, traditional marker-based systems pose several challenges, particularly for children with neurological disabilities and sensory processing abnormalities, such as those observed with children with cerebral palsy. These challenges hinder the use of kinematic markers and limit detailed analyses of movement patterns. Recent advancements in markerless motion capture systems utilizing deep learning-based human pose estimation allowed us to explore cost-effective alternatives to traditional optical systems and the subsequent data processing approaches. An integrated toolbox was developed, combining multiple motion capture technologies: research-grade kinematic equipment, kinematic clusters, inertial measurement units, three-dimensional (3D) markerless systems, and two-dimensional (2D) markerless systems with commercially available cameras (via MediaPipe). For this current study, we present the outcomes of 3D marker-based versus 2D markerless motion capture, the major ongoing issue in human subjects' biomechanical studies, to describe coordinative patterns via hip-knee angle-angle plots. The cyclogram approach was selected because it offers a robust metric and readily interpretable framework for analyzing coordination via coupled motion between body segments. Two typically developing children and two children with cerebral palsy performed a functional movement pattern, the sit-to-stand task. The findings here demonstrated the feasibility of integrating multimodal systems for kinematic analyses, providing flexibility for research and clinical settings. Moreover, the novel open-source approach presented in this work addresses the challenges posed by many patient populations experiencing sensory processing issues, allowing for an advanced and individualized plan of care.

Introduction

Three-dimensional kinematic motion capture evaluations have offered reliable information in the quantification of expected and abnormal movement patterns. Such information is crucial when designing rehabilitation plans¹ and establishing safety approaches for patient engagement with clinical equipment (e.g.,^2,3). When considering children with neurologic-induced disabilities, these kinematic evaluations can provide enhanced care by addressing changes in coordination patterns in distinct functional tasks such as gait⁴, sit-to-stand task⁵, an....

Protocol

This study was conducted as a case series using representative results from four children to demonstrate protocol feasibility rather than statistical inference. Two children typically developing (male 4 years old, 100 cm, 14.5 kg; male 10 years old, 144 cm, 40.8 kg) and two children with cerebral palsy, Gross Motor Function Classification System III (female 4 years old, 93 cm, 13.8 kg; male 4 years old, 102 cm, 16.7 kg) participated in this study. Parents/legal guardians and children provided informed consent/assent prior to participation in accordance with our Institutional Review Board-approved study protocol (IRB-FY2024-33).

NOTE: While ....

Results

The open-source Python-based toolbox successfully quantified hip-knee coordination patterns from both marker-based and markerless systems in pediatric participants during the sit-to-stand task. To provide a quantitative comparison alongside the visual cyclograms, key summary metrics (Hip and Knee Range of Motion) for the representative trials are presented in Table 1. Representative angle-angle plots from typically developing children (Figure 4A,B) exhibit c.......

Discussion

The goal of this work was to demonstrate the feasibility and application of an open-source, multimodal toolbox capable of integrating marker-based and markerless motion capture systems to analyze whole-body coordination in pediatric populations. In representative applications, the protocol successfully produced hip-knee cyclograms that were comparable between marker-based and markerless systems in typically developing children, while also highlighting similarities and discrepancies in children with cerebral palsy when mo.......

Materials

List of materials used in this article

Name	Company	Catalog Number	Comments
FLIR Blackfly camera	FLIR Systems	Model: BFS-U3-200S6C-C	Used for 2D markerless motion capture (50 Hz, 1980×1200 px)
Hikvision PoE camera	Hikvision	N/A	Alternative video recording for 2D markerless capture
LockLab hardware trigger	Vicon	LockLab	Used for temporal synchronization
Logitech C920 camera	Logitech	HD Pro Webcam C920	Alternative consumer camera for markerless capture
MediaPipe	Google Research	v0.10.21	Used for real-time 2D pose estimation. Available online at https://ai.google.dev/edge/mediapipe/solutions/guide
OpenPose software	Carnegie Mellon University / OpenPose community	Version 1.7.0	Used for real-time 2D pose estimation
Plug-in Gait full body model	Vicon	Standard model	Used as the biomechanical model for anatomical marker placement
Vero infrared cameras	Vicon	Vero series	Used for 3D marker-based motion capture (100 Hz)