Gait Analysis Approaches

DOI

10.2991/978-94-6463-784-7_7How to use a DOI?

Keywords

Gait Measurements; Gait Analysis; Machine Learning

Abstract

The Internet of Things (IoT) has brought significant advancements in health monitoring by creating smart environments where interconnected devices can collect and share health data in real-time. IoT systems can integrate various data sources, offering a comprehensive view of an individual’s health status. However, the implementation of IoT-based health monitoring faces several challenges, including system complexity, high costs, and concerns related to data security and interoperability. Further, IoT systems provide the potential for continuous monitoring, they require a robust network infrastructure and effective data management systems, which can be obstacles to adoption in less developed or rural areas. This chapter describes the utilization of IoT along with the application of Artificial Intelligence and Machine Learning techniques that can be realized to monitor the human gait analysis.

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  - Mohd Irfan
PY  - 2025
DA  - 2025/07/28
TI  - Gait Analysis Approaches
BT  - Proceedings of the IoT AND LiDAR Technologies in Healthcare Workshop (ILTH 2024)
PB  - Atlantis Press
SP  - 69
EP  - 76
SN  - 2589-4919
UR  - https://doi.org/10.2991/978-94-6463-784-7_7
DO  - 10.2991/978-94-6463-784-7_7
ID  - Irfan2025
ER  -