Research on the grading method of Parkinson's patients based on the analysis of complexity characteristics

Linxi He

doi:10.1117/12.2643455

9 October 2022 Research on the grading method of Parkinson's patients based on the analysis of complexity characteristics

Linxi He

Author Affiliations +

Proceedings Volume 12246, 2nd International Conference on Signal Image Processing and Communication (ICSIPC 2022); 122462C (2022) https://doi.org/10.1117/12.2643455
Event: 2nd International Conference on Signal Image Processing and Communication (ICSIPC 2022), 2022, Qingdao, China

Abstract

In this paper, a method for grading Parkinson's disease patients based on the analysis of the complexity of electrostatic gait signals is proposed. The non-contact electrostatic sensing device is used to obtain the electrostatic gait signals generated by the natural stepping process of Parkinson's patients and healthy people, and extract their features respectively. The LZ complexity, C0 complexity, multi-scale entropy (MSE) and permutation entropy (PE) were obtained, and the differences in gait characteristics of the two groups were compared and analyzed. Then, the support vector machine (SVM) algorithm was used to establish the Parkinson's disease grading model. The experimental results show that several complex features proposed in this paper can effectively distinguish Parkinson's patients with different severity levels, and the classification accuracy rate is 91.77%.

Citation Download Citation

Linxi He "Research on the grading method of Parkinson's patients based on the analysis of complexity characteristics", Proc. SPIE 12246, 2nd International Conference on Signal Image Processing and Communication (ICSIPC 2022), 122462C (9 October 2022); https://doi.org/10.1117/12.2643455

ACCESS THE FULL ARTICLE

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available