Journal
SCIENTIFIC REPORTS
Volume 12, Issue 1, Pages -Publisher
NATURE PORTFOLIO
DOI: 10.1038/s41598-022-21445-4
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Funding
- National Brain Research Program II [2017-1.2.1-NKP-2017-00002, PD-132652]
- Janos Bolyai Research Scholarship of the Hungarian Academy of Sciences [EFOP-3.6.3-VEKOP-16-2017-00009]
- EU Joint Programme-Neurodegenerative Disease Research (JPND) project
- National Research, Development and Innovation, Hungary [2019-2.1.7-ERA-NET-2020-00006]
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The study aimed to develop an automated, rapid screening tool for the recognition of mild cognitive impairment (MCI) based on hand movement analysis. Significant differences were found between MCI patients and healthy controls in mouse movement characteristics, and there were significant correlations between mouse movement parameters and neuropsychological test scores. Hand movement analysis shows potential value in the early recognition of MCI and large-scale cognitive screening.
Mild cognitive impairment (MCI) is the prodromal phase of dementia, and it is highly underdiagnosed in the community. We aimed to develop an automated, rapid (< 5 min), electronic screening tool for the recognition of MCI based on hand movement analysis. Sixty-eight individuals participated in our study, 46 healthy controls and 22 patients with clinically defined MCI. All participants underwent a detailed medical assessment including neuropsychology and brain MRI. Significant differences were found between controls and MCI groups in mouse movement characteristics. Patients showed higher level of entropy for both the left (F = 5.24; p = 0.001) and the right hand (F = 8.46; p < 0.001). Longer time was required in MCI to perform the fine motor task (p < 0.005). Furthermore, we also found significant correlations between mouse movement parameters and neuropsychological test scores. Correlation was the strongest between motor parameters and Clinical Dementia Rating scale (CDR) score (average r: - 0.36, all p's < 0.001). Importantly, motor parameters were not influenced by age, gender, or anxiety effect (all p's > 0.05). Our study draws attention to the utility of hand movement analysis, especially to the estimation of entropy in the early recognition of MCI. It also suggests that our system might provide a promising tool for the cognitive screening of large populations.
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