A survey on Alzheimer’s disease detection using gait analysis

Authors

  • Hasani Mehraban, Afsoon Dept. of Occupational Therapy, Faculty of Rehabilitation Sciences, Iran University of Medical Sciences and Health Sciences, Tehran, Iran
  • Khamseh, Fatemeh Neurologist, Iran Alzheimer’s Association, Tehran. Iran
  • Seyfollahi, Mahmoud Dept. of Electronic Engineering, Facluty of Electrical and Computer Engineering, Semnan University, Semnan, Iran
  • Soltanizadeh, Hadi Dept. of Electronic Engineering, Facluty of Electrical and Computer Engineering, Semnan University, Semnan, Iran
Abstract:

Introduction: Early detection of Alzheimer's disease (AD), as a neurodegenerative disease and the most common cause of dementia in the elderly people, using gait analysis have been particularly noted by researcher in recent years. Because this novel method is non-invasive, less cost, and feasible in non-clinical and laboratory environments. Therefore, in this Meta-Analysis review article, detection of AD using gait analysis based on information technology tools surveyed in previous studies. Materials and Methods: The search for previous articles was done in databases such as Google Scholar, Pubmed, IEEE, Springer, and Elsevier. After finding articles in these databases, appropriate articles were selected to survey based on criteria such as focusing of the study on elderly patients with AD or mild cognitive impairment, the detection and assessment of AD, and the use of sensor technology to record gait. Results: AD can be detected, even in the early stages and also at a stage of mild cognitive impairment based on gait analysis using new technologies with sensors and information technologies. Also, it is possible to quantitatively evaluate and more accurately detect the disease based on the combination of different sensor technologies and the use of artificial intelligence techniques. Conclusion: Although gait analysis can be a novel tool for early detection of AD, but it is essential to be developed and improved based on sensors and artificial intelligence in order to be used as a reliable clinical tools.

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Journal title

volume 22  issue 1

pages  10- 27

publication date 2020-01

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