Finger Tapping as a Biomarker to Classify Cognitive Status in 80+-Year-Olds.

Dieter F Kutz,Julian Rudisch,Stephanie Fröhlich,Claudia Voelcker-Rehage,Katrin Müller

doi:10.3390/jpm12020286

Abstract

This study examined the association between finger tapping and cognitive function in a group of 225 elderly participants (116 males; age 79–92 years; M = 82.5; SD = 2.4). Finger tapping was assessed in two conditions: self-selected pace and fast pace. Based on cognitive assessments, including the MoCA and CERA-NP test battery, participants were classified as cognitively healthy individuals (CHI), participants with mild cognitive impairments (MCI), and those with possible MCI (pMCI). Results of the analyses show significant differences between groups, sex and the group × sex interaction in four parameters for the self-selected pace condition and eight parameters for the fast pace condition. These parameters were used for classification by means of linear discriminant analysis (LDA). The first LDA component showed significant differences between CHI and pMCI and between CHI and MCI. Furthermore, the second LDA component showed significant differences between CHI and pMCI as well as between pMCI and MCI. Nevertheless, the algorithm correctly classified only 50% of participants, regardless of group, suggesting that tapping parameters are only partially useful for classification in early stages of dementia. We discuss these findings in terms of the diadochokinetic nature of finger tapping as associated with the age-related degeneration of cortical and subcortical motor areas.

Highlights

The study participants were classified into three groups according to their cognitive performance: cognitively healthy individuals (CHI, n = 79), participants with possible mild cognitive impairments, and participants with mild cognitive impairments (MCI, n = 66)
Upon further inspecting the distribution of LDA1 and LDA2 over all correctly classified participants and misclassified participants, we found that for LDA1, correctly classified CHI participants were different on this scale relative to correctly classified possible MCI (pMCI) and MCI participants (Figure 3a)
ANOVA revealed differences between groups (CHI, pMCI, MCI), sexes and their interaction for the self-selected pace condition and for the fast pace condition. These parameters were used for classification by means of a linear discriminant analysis (LDA)

Summary

Introduction

More and more people become affected with dementia [1]. [2], the number of people with dementia will have risen to three million by 2050. In addition to the personal cost, the disease causes substantial economic and social burdens [3]. These burdens can be alleviated by early diagnosis of dementia and its pre-stages, as such early detection can allow for more sustainable disease management and optimal health care for affected individuals [1]. It is important to identify people with pre-dementia (e.g., persons with mild cognitive impairments, or MCI) early enough so they can start programs that will help them maintain their personal lifestyle and that will continuously assess the course of the dementia as it progresses

Objectives

Results

Conclusion