Title: Gait analysis in the age of artificial intelligence: a comprehensive review of advances, challenges and future directions

Authors: Stobak Dutta; Anirban Mitra; Subrata Paul

Addresses: Department of Computer Science and Engineering, St. Thomas' College of Engineering and Technology, Kolkata, 700023, West Bengal, India ' Department of Computer Science and Engineering, Amity University, Kolkata, 700135, West Bengal, India ' Department of CSE-AI, Brainware University, Barasat, Kolkata, 700125, West Bengal, India

Abstract: Gait analysis, a key biometric modality, identifies individuals via unique walking patterns and is applied in security, medical diagnostics, and surveillance. Over the years, techniques have evolved from model-based and appearance-based methods to advanced artificial intelligence (AI) driven systems. AI integration has significantly enhanced feature extraction, classification accuracy, and robustness under real-world challenges. This review emphasises AI's role in gait analysis, providing a comprehensive overview of methodologies, key datasets, evaluation metrics, and classification based on body representation, temporal modelling, and sensor modalities. It highlights major AI advancements, including deep learning for cross-view gait recognition, in-the-wild scenarios, and multimodal analysis using depth and infrared sensors. The study also examines challenges such as gait variability, occlusion, and biometric privacy concerns. By synthesising existing research and identifying current gaps, this work serves as a valuable reference for researchers and practitioners, and it outlines future directions, emphasising AI's growing influence on gait analysis advancements.

Keywords: human gait analysis; machine learning algorithms; gait parameters; biomechanics; kinematics; clinical gait dataset; abnormal gait detection.

DOI: 10.1504/IJICA.2025.149776

International Journal of Innovative Computing and Applications, 2025 Vol.15 No.4, pp.220 - 235

Received: 08 May 2025
Accepted: 10 Aug 2025
Published online: 12 Nov 2025 *

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