Human Gait Anomaly Detection Using LiDAR for Healthcare Monitoring

DOI

10.2991/978-94-6463-784-7_10How to use a DOI?

Keywords

LiDAR; Internet of Things (IoT); Real-Time Healthcare Monitoring; Gait Anomaly Detection; Elderly Fall Risk; Smart Health Systems

Abstract

This chapter presents the AI-Driven Real-Time detection of Gait anomalies utilizing LiDAR Technology for Advanced Healthcare Monitoring. This innovative approach leverages cutting-edge artificial intelligence and sophisticated Light Detection and Ranging technology to track and analyze individuals’ gait patterns in real time. By monitoring the walking patterns of movement, this system aims to identify and detect any anomalies that may indicate underlying health issues. The implementation of such a system in healthcare settings offers a novel method for continuous monitoring, contributing to early diagnosis, improved patient outcomes, and a deeper understanding of mobility-related conditions.

Copyright

© 2025 The Author(s)

Open Access

Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

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TY  - CONF
AU  - Anuroop Gaddam
AU  - Muhammad Zeeshan Khan
AU  - Dhananjay Thiruvady
PY  - 2025
DA  - 2025/07/28
TI  - Human Gait Anomaly Detection Using LiDAR for Healthcare Monitoring
BT  - Proceedings of the IoT AND LiDAR Technologies in Healthcare Workshop (ILTH 2024)
PB  - Atlantis Press
SP  - 96
EP  - 109
SN  - 2589-4919
UR  - https://doi.org/10.2991/978-94-6463-784-7_10
DO  - 10.2991/978-94-6463-784-7_10
ID  - Gaddam2025
ER  -