Affiliations 

  • 1 Electrical and Computer Systems Engineering & Advanced Engineering Platform, School of Engineering, Monash University, Bandar Sunway, Malaysia
PLoS One, 2019;14(6):e0219114.
PMID: 31247037 DOI: 10.1371/journal.pone.0219114

Abstract

Giancardo et al. recently introduced the neuroQWERTY index (nQi), which is a novel motor index derived from computer-key-hold-time data using an ensemble regression algorithm, to detect early-stage Parkinson's disease. Here, we derive a much simpler motor index from their hold-time data, which is the standard deviation (SD) of the hold-time fluctuations, where fluctuation is defined as the difference between successive natural-log of hold time. Our results show the performance of the SD and nQi tests in discriminating early-stage subjects from controls do not differ, although the SD index is much simpler. There is also no difference in performance between the SD and alternating-finger-tapping tests.

* Title and MeSH Headings from MEDLINE®/PubMed®, a database of the U.S. National Library of Medicine.