Less is More: Univariate Modelling to Detect Early Parkinson's Disease from Keystroke Dynamics

Milne, Antony; Farrahi, Katayoun and Nicolaou, Mihalis. 2018. 'Less is More: Univariate Modelling to Detect Early Parkinson's Disease from Keystroke Dynamics'. In: Discovery Science 2018, LNCS Proceedings. Limassol, Cyprus October 29-31, 2018. [Conference or Workshop Item]

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Abstract or Description

We analyse keystroke hold times from typing logs to detect early signs of Parkinson’s disease. We develop a feature that captures the dynamic variation between consecutive keystrokes and demonstrate that it can be be used in a univariate model to perform classification with AUC=0.85 from only a few hundred keystrokes. This is a substantial improvement on the current baseline. We argue that previously proposed methods are based on overcomplicated models—our simpler method is not only more elegant and transparent but also more effective.

Item Type:

Conference or Workshop Item (Paper)

Identification Number (DOI):

https://doi.org/10.1007/978-3-030-01771-2_28

Related URLs:

Departments, Centres and Research Units:

Computing

Dates:

DateEvent
July 2018Accepted
7 October 2018Published

Event Location:

Limassol, Cyprus

Date range:

October 29-31, 2018

Item ID:

24111

Date Deposited:

14 Sep 2018 11:27

Last Modified:

09 Jun 2021 16:16

URI:

https://research.gold.ac.uk/id/eprint/24111

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