Decision Support System with AI-based Gait Estimation as Aid for Neurodegenerative Disease Patients

Abstract: AI-based uncertainty handling can be applied to multimodal data fusion for IMU (Inertial Measurement Units) sensor-based gait motion cap­ture in tracking gait differences in patients with Alzheimer’s disease or oth­er medical conditions. The challenge is represented by monitoring and an­alyzing gait patterns in patients with Alzheimer’s disease to detect chang­es over time and assess disease, progression, or treatment effectiveness. Ma­chine learning models are used to enhance the accuracy of gait analysis sys­tems, making them valuable tools in healthcare for diagnosis and rehabilita­tion. Thus, IMUs have evolved with multi-sensor systems, sensor fusion, and machine learning for precise gait analysis, finding applications in clinical and consumer settings. AI-based gait motion capture has advanced through deep learning and video-based methods, enabling non-invasive, markerless anal­ysis for individual identification, and enhancing healthcare diagnostics and rehabilitation. Recurrent neural networks (RNNs) or long short-term memory networks (LSTMs), are developed and trained using historical gait data from patients with Alzheimer’s disease that also include the uncertainty estimates as input features to the models. AI-based uncertainty handling integrated into gait motion capture and analysis allows continuous monitoring of gait differ­ences in patients with Alzheimer’s disease and other medical conditions.

7th International Scientific Conference on Recent Advances in Information Technology, Tourism, Economics, Management and Agriculture – ITEMA 2023 – Conference Proceedings, Hybrid (Faculty of Organization and Informatics Varaždin, University of Zagreb, Croatia), October 26, 2023

ITEMA Conference Proceedings published by: Association of Economists and Managers of the Balkans – Belgrade, Serbia

ITEMA conference partners: Faculty of Economics and Business, University of Maribor, Slovenia; Faculty of Organization and Informatics, University of Zagreb, Varaždin; Faculty of Geography, University of Belgrade, Serbia; Institute of Marketing, Poznan University of Economics and Business, Poland; Faculty of Agriculture, Banat’s University of Agricultural Sciences and Veterinary Medicine ”King Michael I of Romania”, Romania

ITEMA Conference 2023 Conference Proceedings: ISBN 978-86-80194-75-2, ISSN 2683-5991, DOI: https://doi.org/10.31410/ITEMA.2023

Creative Commons Non Commercial CC BY-NC: This article is distributed under the terms of the Creative Commons Attribution-Non-Commercial 4.0 License (https://creativecommons.org/licenses/by-nc/4.0/) which permits non-commercial use, reproduction and distribution of the work without further permission.

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