Proceedings of the IoT AND LiDAR Technologies in Healthcare Workshop (ILTH 2024)

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AI-Powered Real-Time Gait Detection Using LiDAR for Healthcare Monitoring

Authors
Anuroop Gaddam1, *, Muhammad Zeeshan Khan1, Dhananjay Thiruvady1
1School of Information Technology, Deakin University, Geelong, VIC, 3216, Australia
*Corresponding author. Email: anuroop.gaddam@deakin.edu.au
Corresponding Author
Anuroop Gaddam
Available Online 28 July 2025.
DOI
10.2991/978-94-6463-784-7_9How to use a DOI?
Keywords
LiDAR; Internet of Things (IoT); Real-Time Healthcare Monitoring; Gait Anomaly Detection; Elderly Fall Risk; Smart Health Systems
Abstract

Leveraging the advanced capabilities of AI, real-time detection of gait anomalies through LiDAR technology is revolutionizing healthcare monitoring. This innovative approach enables precise and immediate assessment of patients’ walking patterns, highlighting deviations that may indicate underlying health issues. By utilizing the detailed spatial mapping of LiDAR sensors, healthcare professionals can better understand an individual’s mobility, allowing for timely interventions and personalized care strategies. This integration of cutting-edge technology promises to enhance patient outcomes by enabling more proactive and informed healthcare decisions.

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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Volume Title
Proceedings of the IoT AND LiDAR Technologies in Healthcare Workshop (ILTH 2024)
Series
Atlantis Highlights in Intelligent Systems
Publication Date
28 July 2025
ISBN
978-94-6463-784-7
ISSN
2589-4919
DOI
10.2991/978-94-6463-784-7_9How to use a DOI?
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.

Cite this article

risenwbib
TY  - CONF
AU  - Anuroop Gaddam
AU  - Muhammad Zeeshan Khan
AU  - Dhananjay Thiruvady
PY  - 2025
DA  - 2025/07/28
TI  - AI-Powered Real-Time Gait Detection Using LiDAR for Healthcare Monitoring
BT  - Proceedings of the IoT AND LiDAR Technologies in Healthcare Workshop (ILTH 2024)
PB  - Atlantis Press
SP  - 84
EP  - 95
SN  - 2589-4919
UR  - https://doi.org/10.2991/978-94-6463-784-7_9
DO  - 10.2991/978-94-6463-784-7_9
ID  - Gaddam2025
ER  -