Accepted for/Published in: JMIR mHealth and uHealth
Date Submitted: Jul 16, 2019
Date Accepted: Mar 23, 2020
Date Submitted to PubMed: May 22, 2020
Warning: This is an author submission that is not peer-reviewed or edited. Preprints - unless they show as "accepted" - should not be relied on to guide clinical practice or health-related behavior and should not be reported in news media as established information.
Survey of Smartphone-Based Neurocognitive Assessments
ABSTRACT
Background:
Comprehensive exams such as the Dean-Woodcock Neuropsychological Assessment System (DWNAS), the Global Deterioration Scale (GDS), and the Boston Diagnostic Assessment of Aphasia (BDAE) are the gold standard for doctors and clinicians in the preliminary assessment and monitoring of neurocognitive function in conditions such as neurodegenerative diseases and acquired brain injuries. In recent years, there has been an increased focus on implementing these exams on mobile devices to benefit from their configurable, built-in sensors, in addition to their scoring, interpretation, and storage capabilities. Compared to their predecessors, sensor-based mobile assessments allow for the collection of substantial amounts of data through the use of inherent device capabilities, human-device interactions, and device usage approaches. Additional benefits of sensor-based assessments include the potential for earlier and more confident diagnoses of neurological conditions, mapping the development of these conditions over time, and the creation of efficient, evidence-based rehabilitation programs through the configuring of device sensors and interactions.
Objective:
This paper provides an overview and analysis of recent results in the area, investigating the cross-section between the presentation of different neurological conditions and the use of mobile devices, their built-in sensors, and human-device interactions for the assessment and monitoring of these neurocognitive functions.
Methods:
This survey presents a review of current mobile technological capabilities to enhance the assessment of neurocognitive conditions including neurodegenerative diseases and acquired brain injury. It explores how many device features can be configured for assessments as well as the enhanced capability and data monitoring that arise due to the addition of these features.
Results:
Configuring neurocognitive tests on mobile devices allows for enhanced cognitive monitoring across all functional categories due to inherent device capabilities including sensors and human device interactions. Motor, memory, speech, language, and executive function assessments can be enhanced with the use of positional sensors, media sensors, timing features, and human device interactions, in both participatory and opportunistic approaches. The assessments of behavior and emotion monitoring can be done with the use of both configurable media sensors and participatory approaches including questionnaires, diaries, and mood scales. Sleep assessments on mobile devices can be done with positional sensor configurations and participatory approaches where the user depicts their overall sleep quality. Finally, the assessment of a subset of autonomic functions on mobile devices can be completed with the use of mobile sensor configurations, participatory approaches, and opportunistic approaches, however not all autonomic functions can be assessed with these mobile devices at this time.
Conclusions:
This survey provides background and guidance on the importance of using mobile devices for the monitoring of neurocognitive functions across different types of neurological conditions. Using mobile technology for neurocognitive functional assessments and employing inherent device capabilities and human interactions will allow for a deeper understanding of different neurological diseases.
Citation
