Touchscreen typing-pattern analysis for detecting fine motor skills decline in early-stage Parkinson's disease

Scientific Reports
Dimitrios IakovakisLeontios J Hadjileontiadis

Abstract

Parkinson's disease (PD) is a degenerative movement disorder causing progressive disability that severely affects patients' quality of life. While early treatment can produce significant benefits for patients, the mildness of many early signs combined with the lack of accessible high-frequency monitoring tools may delay clinical diagnosis. To meet this need, user interaction data from consumer technologies have recently been exploited towards unsupervised screening for PD symptoms in daily life. Similarly, this work proposes a method for detecting fine motor skills decline in early PD patients via analysis of patterns emerging from finger interaction with touchscreen smartphones during natural typing. Our approach relies on low-/higher-order statistical features of keystrokes timing and pressure variables, computed from short typing sessions. Features are fed into a two-stage multi-model classification pipeline that reaches a decision on the subject's status (PD patient/control) by gradually fusing prediction probabilities obtained for individual typing sessions and keystroke variables. This method achieved an AUC = 0.92 and 0.82/0.81 sensitivity/specificity (matched groups of 18 early PD patients/15 controls) with discriminant...Continue Reading

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Citations

Nov 13, 2019·Annals of Clinical and Translational Neurology·Brit YoungmannDavid Arkadir
Sep 19, 2019·Scientific Reports·Rafail-Evangelos MastorasLeontios J Hadjileontiadis
Oct 3, 2020·Annals of Biomedical Engineering·Abdul Haleem ButtFilippo Cavallo
Jul 30, 2020·Scientific Reports·Dimitrios IakovakisLeontios J Hadjileontiadis
Aug 23, 2019·Molecules : a Journal of Synthetic Chemistry and Natural Product Chemistry·Rim WehbeZiad Fajloun
Nov 6, 2020·Multiple Sclerosis : Clinical and Laboratory Research·K H LamJ Killestein
Mar 5, 2021·Current Neurology and Neuroscience Reports·Jamie L AdamsRuth B Schneider

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Methods Mentioned

BETA
feature extraction
feature vector extraction

Software Mentioned

Android Operating System ( OS )

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