Finger Tapping Test for Assessing the Risk of Mild Cognitive Impairment.

Aim: A testing method for early diagnosis of Mild cognitive dementia (MCI) that can be easily applied in clinical practice was investigated in this study. We examined whether MCI risk can be determined through finger movements. Methods: Between 2013 and 2020, 1097 individuals were screened. After applying propensity-score matching to adjust for variability between the groups, 173 individuals each in the mild cognitive impairment and control groups were selected. Thereafter, differences between groups in mean values of parameters extracted from finger tap movements were determined using unpaired t-test and effect size. Furthermore, area under the curve, sensitivity, and specificity were calculated from the receiver operating characteristic curve for parameters with significant difference. Results: A significant difference was observed, especially in the number of taps in the MCI group compared with that in the control group (p < .001; 95% CI, -12.7 to -8.8; r = 0.51). A cut-off value of 30 taps was applied (sensitivity, 0.77; specificity, 0.67; AUC, 0.79). Significant differences were also observed in rhythm-related parameters. Conclusions: These parameters might be useful for capturing MCI risk. Finger taps are easily measured and may be suitable for screening large populations. This tool might be used as a supplemental method to increase the sensitivity of traditional cognitive tests.

Relationship between finger movement characteristics and brain voxel-based morphometry.

BACKGROUND: Aging is the most significant risk factor for dementia. Alzheimer's disease (AD) accounts for approximately 60-80% of all dementia cases in older adults. This study aimed to examine the relationship between finger movements and brain volume in AD patients using a voxel-based reginal analysis system for Alzheimer's disease (VSRAD) software. METHODS: Patients diagnosed with AD at the Center for Comprehensive Care and Research on Memory Disorders were included. The diagnostic criteria were based on the National Institute on Aging-Alzheimer's Association. A finger-tapping device was used for all measurements. Participants performed the tasks in the following order: with their non-dominant hand, dominant hand, both hands simultaneously, and alternate hands. Movements were measured for 15 s each. The relationship between distance and output was measured. Magnetic resonance imaging measurements were performed, and VSRAD was conducted using sagittal section 3D T1-weighted images. The Z-score was used to calculate the severity of medial temporal lobe atrophy. Pearson's product-moment correlation coefficient analyzed the relationship between the severity of medial temporal lobe atrophy and mean values of the parameters in the finger-tapping movements. The statistical significance level was set at <5%. The calculated p-values were corrected using the Bonferroni method. RESULTS: Sixty-two patients were included in the study. Comparison between VSRAD and MoCA-J scores corrected for p-values showed a significant negative correlation with the extent of gray matter atrophy (r = -0. 52; p< 0.001). A positive correlation was observed between the severity of medial temporal lobe atrophy and standard deviation (SD) of the distance rate of velocity peak in extending movements in the non-dominant hand (r = 0. 51; p< 0.001). CONCLUSIONS: The SD of distance rate of velocity peak in extending movements extracted from finger taps may be a useful parameter for the early detection of AD and diagnosis of its severity.

Assessment of finger motor function that reflects the severity of cognitive function.

OBJECTIVES: We conducted a finger tapping movement test using a finger tapping device with magnetic sensors (UB-2) and performed multiple regression analyses using a number of finger movements parameters to estimate the severity of cognitive impairment. METHODS: The subjects of this study were 64 patients, including 44 diagnosed with Alzheimer's disease (AD) (mean age: 73.8±7.0 years) and 20 diagnosed with mild cognitive impairment (MCI) (mean age: 76.7±4.2 years). For the finger-tapping movement tasks, we tested single-hand (left and right) tapping, simultaneous tapping of both hands, and alternate tapping between hands. After measurement, multiple regression analysis adjusted for age and sex was performed to predict the Mini-Mental State Examination (MMSE) score from the calculated hand parameters. RESULTS: Relatively high standardized partial regression coefficients were observed for the following two parameters: standard deviation (SD) of distance rate of velocity peak in extending movement and the SD of contact duration. The coefficients of determination (R2) ranged between 0.1 to 0.28. CONCLUSIONS: Our results suggest the possibility that these parameters may be used to assess cognitive function. We shall obtain large-scale data from older people to examine the possibility of these parameters to be used as an early diagnostic tool for dementia patients.