Machine Learning Based Analysis of the Upper Limb Freezing During Handwriting in Parkinson's Disease Patients. Issue 29 (2022)

• Record Type: Journal Article
• Authors: Gorbatsov, Vassili; Valla, Elli; Nõmm, Sven; Medijainen, Kadri; Taba, Pille; Toomela, Aaro
• Is Part Of: IFAC-PapersOnLine. Volume 55:Issue 29(2022)
• Page Start: 91
• Page End: 95
• Publication Date: 2022
• Subjects: Computer aided diagnosis -- Parkinson's disease -- machine learning -- drawing test -- hand freezing; Automatic control -- Periodicals; 629.805
• DOI: 10.1016/j.ifacol.2022.10.237
• Languages: English
• ISSNs: 2405-8963

Abstract

Abstract: Freezing of the upper limb in Parkinson's disease patients occurring during writing tests constitutes the research subject of the present paper. Digitisation of the writing and drawing tests coupled with artificial intelligence techniques have demonstrated accurate results in supporting the diagnostics of Parkinson's disease. In the digital setting, the analysis of freezing episodes did not get much attention. The main goal of the present paper is to determine if the neighbourhood of the point where freezing occurred possesses sufficient discriminating power to distinguish between the Parkinson's disease patients and healthy control individuals. For each freezing episode, time intervals of one second before and after are considered. These intervals are described by the hand movement's kinematic and pressure parameters. These parameters are used as features for the standard machine learning workflow that applies a nested cross-validation loop. The paper's main findings have demonstrated that analysis of the freezing neighbourhoods allows distinguishing Parkinson's disease patients from age matched healthy controls. The best results were achieved based on the movements occurring one second after the freezing episode. Kinematic and pressure-based features describing these movements have allowed training classifiers whose accuracy, precision, and recall have reached the values of 0.86, 0.86 and 0.93, respectively. Furthermore, the achieved results are comparable to those available in the literature