(bo_78_20_2020) Funder: Bolyai János Kutatási Ösztöndíj
Az orvos-, egészségtudományi- és gyógyszerészképzés tudományos műhelyeinek fejlesztése(EFOP-3.6.3-VEKOP-16-2017-00009)
Funder: EFOP-VEKOP
(Open access funding provided by Semmelweis University)
Subjects:
Dementia
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.