Towards a Comprehensive Mobile-Based Neurocognitive Digital Health Assessment System (NDHAS)
Staging methods and clinical assessments including the Hoehn and Yahr Scale (H&Y), MDS - Unified Parkinson’s Disease Rating Scale (MDS-UPDRS), Dean - Woodcock Neuropsychological Assessment System (DWNAS), and the Neurobehavioral Functioning Inventory (NFI) are among the current gold standards for doctors and clinicians in the preliminary assessment and monitoring of individuals with neurodegenerative diseases. Recently, a transition of clinical assessments to mobile devices for the benefits of their configurable built-in sensors, scoring, interpretation, and storage capabilities has occurred. As mobile technology becomes increasingly accepted in healthcare among both users and clinicians, the ability to use device capabilities (e.g., device positional data and screen interactions) for subject monitoring also increases. With this transition of pen-and-paper style clinical tests to mobile platforms, the current 'gold standard' of testing must be updated to include these new beneficial, objective, capabilities.
The primary goal of this dissertation was the formation and implementation of a usable and more comprehensive mobile-based neurocognitive digital health assessment system (NDHAS) for the objective evaluation of neurocognitive functions and subsequent formation of personalized intervention protocols as they relate to individuals with neurodegenerative diseases. The proposed approach included updating previous versions of testing for a usable, comprehensive, systematic implementation of mobile technology. This systematic approach included the implementation of a mobile device's sensors and user device interactions in addition to patient reported outcomes. All collected data was then interpreted using statistical analysis and machine learning methods to allow for higher-quality, objective, longitudinal analysis. This new standard is intended to aid clinicians in the accurate and objective diagnosis of neurological conditions, monitor the development of symptom-specific deficits over time, while providing individuals with efficient, evidence-based, personalized, rehabilitation programs.
History
Date Modified
2022-04-13Defense Date
2022-03-07CIP Code
- 40.0501
Research Director(s)
Christian PoellabauerCommittee Members
Ronald Metoyer Sandra Schneider Patrick Flynn Aaron StriegelDegree
- Doctor of Philosophy
Degree Level
- Doctoral Dissertation
Alternate Identifier
1310409528Library Record
6184015OCLC Number
1310409528Additional Groups
- Computer Science and Engineering
Program Name
- Computer Science and Engineering