Analysis of Abnormal Gait in the Diagnosis of Early Neurodegenerative Diseases: A Review

  • Hepu Zhao College of Electronic Information Engineering, Xi’an Technological University
  • Baiwei Xu College of Electronic Information Engineering, Xi’an Technological University
  • Shizhen Ti College of Electronic Information Engineering, Xi’an Technological University
Keywords: Neurodegenerative Diseases; Early Diagnosis;Abnormal Gait; Non-Contact Detection


Early detection of neurodegenerative diseases can increase the possibility to access to treatment, and assist in advance care plan-ning. At present, most of the gait researches focus on the design and application of recognition tools for disease diagnosis, such as recording the walking and movement status through wearable sensor devices, while, relatively less non-contact machine vision is used to measure gait. The non-contact gait detection method is characterized by the advantages, including the absence of human cooperation, non-invasive nature and so on, which is also suitable for long-distance perception. In this paper, we focused on some non-contact analysis methods for abnormal gait, and it is hoped that it can provide guidance for the diagnosis of neurodegenerative diseases.


[1] Joshi D, Khajuria A, Joshi P. An automatic non-invasive method for Parkinson’s disease classification. Comput Methods Programs

Biomed. 2017 Jul;145:135-145.

[2] Examination of Gait, Available from: physical-examination-gait/.

[3] Ghoraani B, Boettcher LN, Hssayeni MD, Rosenfeld A, Tolea MI, Galvin JE. Detection of Mild Cognitive Impairment and

Alzheimer’s Disease using Dual-task Gait Assessments and Machine Learning. Biomed Signal Process Control. 2021 Feb; 64: 102249.

[4] Mole SSS, Sujatha K. An efficient Gait Dynamics classification method for Neurodegenerative Diseases using Brain signals. J Med

Syst. 2019 Jun 25;43(8):245.

[5] Barrett B, Schultz SK, Luther SL, Friedman Y, Cowan L, Bulat T. Mortality and Associated Risk Factors in Community-Dwelling

Persons With Early Dementia. Alzheimer Dis Assoc Disord. 2020 Jan-Mar;34(1):40-46.

[6] Aşuroğlu, T., Açıcı, K., Erdaş, Ç. B., Toprak, M. K., Erdem, H., Oğul, H. Parkinson’s disease monitoring from gait analysis via

foot-worn sensors. Biocybernetics and Biomedical Engineering, 38(3) (2018)760-772.

[7] Balaji E., Brindha D., Balakrishnan R. Supervised machine learning based gait classification system for early detection and stage

classification of Parkinson’s disease. Applied Soft Computing Journal. 94(2020)1-15.

Review Article