Toward Quantitative Neurology: Sensors to Assess Motor Deficits in Dementia

Article type: Systematic Review

Authors: Hamedani, Mehrnaz^{a; 1; *} | Caneva, Stefano^{a; 1} | Mancardi, Gian Luigi^a | Alì, Paolo Alessandro^a | Fiaschi, Pietro^{a; b} | Massa, Federico^{a; b} | Schenone, Angelo^{a; b} | Pardini, Matteo^{a; b}

Affiliations: [a] Department of Neurosciences, Rehabilitation, Ophthalmology, Genetic and Maternal and Infantile Sciences (DINOGMI), University of Genoa, Genoa, Italy | [b] IRCCS Ospedale Policlinico San Martino, Genoa, Italy

Correspondence: [] Correspondence to: Mehrnaz Hamedani, Department of Neurosciences, Rehabilitation, Ophthalmology, Genetic and Maternal and Infantile Sciences (DiNOGMI), University of Genoa, Largo Paolo Daneo 3, Genova, 16132, Italy. E-mail: mehrnaz.hamedani@medicina.unige.it.

Note: [1] These authors contributed equally to this work.

Abstract: Background:Alzheimer’s disease (AD) is the most common neurodegenerative disorder which primarily involves memory and cognitive functions. It is increasingly recognized that motor involvement is also a common and significant aspect of AD, contributing to functional decline and profoundly impacting quality of life. Motor impairment, either at early or later stages of cognitive disorders, can be considered as a proxy measure of cognitive impairment, and technological devices can provide objective measures for both diagnosis and prognosis purposes. However, compared to other neurodegenerative disorders, the use of technological tools in neurocognitive disorders, including AD, is still in its infancy. Objective:This report aims to evaluate the role of technological devices in assessing motor involvement across the AD spectrum and in other dementing conditions, providing an overview of the existing devices that show promise in this area and exploring their clinical applications. Methods:The evaluation involves a review of the existing literature in the PubMed, Web of Science, Scopus, and Cochrane databases on the effectiveness of these technologies. 21 studies were identified and categorized as: wearable inertial sensors/IMU, console/kinect, gait analysis, tapping device, tablet/mobile, and computer. Results:We found several parameters, such as speed and stride length, that appear promising for detecting abnormal motor function in MCI or dementia. In addition, some studies have found correlations between these motor aspects and cognitive state. Conclusions:Clinical application of technological tools to assess motor function in people with cognitive impairments of a neurodegenerative nature, such as AD, may improve early detection and stratification of patients.

Keywords: Alzheimer’s disease, cognitive impairment, dementia, mild cognitive impairment, motor function, sensors, technology assessment

DOI: 10.3233/JAD-240559

Journal: Journal of Alzheimer's Disease, vol. 101, no. 4, pp. 1083-1106, 2024