Evaluation of Motor and Cognitive Dual Task Effects on Mild Cognitive Impairment Subjects

Author: Mr Gianmaria Mancioppi STSM Period: 2020-02-09 – 2020-02-19


Hosting institution: CoBTeK, Université Cote D’Azur

From ITC: No



The contribution proposed was to enlarge a preexisting sample of clinical subjects suffering from «Mild Cognitive Impairment» (MCI) and «Subjective Cognitive Impairment» (SCI). The experimentation, carried out by the use of SensFoot and SensHand tools, in the framework of the MARCO-SENS protocol, aimed at the evaluation of several Motor and Cognitive Dual-Tasks (MCDT).
Particularly, it refers to the lower (walking and foot-tapping), and upper limb (finger-tapping) motorcognitive interface. To achieve this goal, different grades of cognitive load and levels of motor difficulties have been provided and combined, namely: CL0 (no cognitive load), CL1 (counting backward by 1), CL2 (counting backward by 3), CL3 (counting backward by 7).
The final goal of our research is to collect data from 40 subjects (20 MCI, 20 SCI), within the visiting period at CoBTeK I managed to include 10 de novo subjects, as proposed.


To accomplish the aforementioned aim, we collaborate with the staff of “Les Centres Mémoire de Ressources et de Recherche (CMRR)” of Nice. We pre-screened about 15 subjects per day, to identify the subjects that well fitted in our protocol. Protocol’s inclusion criteria were: subjects must not exhibit any motor dysfunction due to central or peripheral issues, either be affected by any psychiatric disorders.
Besides, the minimum level of global cognitive status had to be 24 at the Mini-Mental State Examination. Information gathered during the visiting period belongs to 3 different areas per subject: sociodemographics information (gender, age, educational level), clinical report (neuropsychological examination, and data about any comorbidities), and experimental data (kinematics information gathered through the use of SensHand and SensFoot).
The data gathered have been organized as follow: demographic data, neuropsychiological data, and experimental data. Demographic data: gender, age, educational level, diagnosis, weight, height, frailty level). Neuropsychological data: each subject underwent a neuropsychological assessment, including the following tests: mini-mental state examination (global cognition status), Bref (executive functions), verbal fluency (language), free and cue selective reminding test (memory), digiti span direct and invers version (working memory), trailing making test forma A and form B (selective attention and divieded attention).
Experimental data: Upper Limb: index Tapping (FTAP) at 4 increasing level of cognitive load, thumb-index tapping (THFF) at 4 increasing level of cognitive load and alternate finger taping (ALFT) at 4 increasing level of cognitive load. Lower Limb: Foot: toe tapping (TTHP) at 4 increasing level of cognitive load; heel tapping (HTTP) at 4 increasing level of cognitive load; alternate toe-heel tapping (HETO) at 4 increasing
level of cognitive load. Walk: 10 meters free walking at 4 increasing level of cognitive load; Time up and go test at 4 increasing level of cognitive load; figure of 8 test at 4 increasing level of cognitive load.


In conclusion, there were not been missing data, and the following motor parameters can be extracted: number of tapping, tapping frequency, tapping frequency standard deviation, movement amplitude, movement amplitude standard deviation, opening velocity, opening velocity standard deviation, closing velocity, closing velocity standard deviation, gait time, number of strides, velocity, stride length, stride height, stride height standard deviation, stride time, stride time standard deviation, swing time, swing time standard deviation, stance time, stance time standard deviation, relative stance, dorsoplantar excursion, dorsoplantar excursions standard deviation, latency time. Future steps will encompass the combination of these data through the aid of different statistical analyses. Differences among the clinical sub-groups (MCI and SCI) and control groups (Healthy Older Adults and Healthy Younger Adults) will be studied through comparisons analyses. Moreover, correlations between several demographic data (age, gender, educational level) as well as the cognitive state of subjects will be calculated. Characterization of motor phenotypes concerning different neurocognitive domains will be taken into account. Furthermore, the investigation of the most informative MCDT, or combination of MCDTs, will be performed. Such analyses will be the object of future scientific publications.


Based on the result that will come from the current experimentation, an extension of the research can be considered. Future collaborations could be organized ton further enlarge the sample size, and to test the protocol, not only with an assessment purpose, but also with a simulation point of view. Future collaboration could test the possibility to use the MCDT approach as a stimulation approach for elderly
people with a higher risk to develop neurodegenerative diseases.

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