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Measuring the Kinematics of Daily Living Movements with Motion Capture Systems in Virtual Reality

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Published on: April 5, 2018

Three-Dimensional human motion analysis using LiDAR technology: A systematic review.

Jiaqi Lai¹, Mohammad Yavari¹, Peter Vee Sin Lee¹

¹Department of Biomedical Engineering, University of Melbourne, Parkville, Victoria 3010, Australia.

Journal of Biomechanics

|April 19, 2026

Summary

This summary is machine-generated.

This review explores 3D Light Detection and Ranging (LiDAR) for human motion analysis. Deep learning methods, particularly Convolutional Neural Networks (CNNs), show promise in extracting motion data from point clouds.

Keywords:

Joint kinematics Machine learning Motion detection Point cloud

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Area of Science:

Robotics and Computer Vision
Biomedical Engineering
Human-Computer Interaction

Background:

3D Light Detection and Ranging (LiDAR) offers non-invasive dynamic 3D pose data capture.
Extracting motion from sparse, unordered LiDAR point clouds presents significant challenges.

Purpose of the Study:

To systematically review 3D LiDAR data processing methods for human motion analysis.
To identify state-of-the-art algorithms and their performance in human detection and motion estimation.

Main Methods:

Systematic literature search across five major databases (Web of Science, Scopus, Medline, PubMed, Embase).
Screening of 752 articles, with 38 studies included for analysis.
Focus on Convolutional Neural Networks (CNNs), PointNet, and deep learning integration.

Main Results:

Convolutional Neural Networks (CNNs) are prevalent for human detection; PointNet excels in feature extraction.
YOLOv3 achieved 97.7% human detection precision; a LiDAR-IMU fusion method yielded a 30.0 mm Mean Joint Position Error.
A CNN-based Federated Learning framework reached 98% activity recognition accuracy.

Conclusions:

Deep learning effectively extracts spatiotemporal motion patterns from LiDAR data.
Challenges persist in multi-person scenarios and handling LiDAR occlusion for robust analysis.