July 21, 2025
eSDMT
APP
The Symbol Digit Modalities Test (SDMT) is a crucial neuropsychological test used to measure information processing speed, a cognitive function that is often impaired in patients with MS.
However, the traditional paper-and-pencil version has significant limitations:
Dependence on In-person Visits: The test must be administered and supervised by a neurologist, limiting its frequency and creating a high burden on both patients and clinicians.
Learning Effect: The consistent symbol-digit key and test format can lead to patients memorizing the associations, which compromises the validity of results over time.
Limited Metrics: The traditional test only captures the total time and number of errors, missing valuable data points that could provide a deeper insight into cognitive function.
Motor Skills Correlation: While the SDMT is less dependent on motor skills than its predecesor, the Digit Symbol Substitution Test (DSST), the act of writing can still influence the results, which is a factor to consider in patients with motor issues.
Solution: The eDSMT App
The eDSMT app is a digital version of the SDMT designed to overcome these limitations. It was developed to provide a more accessible, accurate, and flexible tool for assessing cognitive deterioration in patients with MS.
Key features include:
Randomized Test Generation: The app ensures that the symbol-digit key pairing and the sequence of symbols are randomized for each test, which prevents memorization and enhances the reliability of repeated tests.
Enhanced Metrics Capture: The app goes beyond the traditional metrics by recording additional data points, This includes the time taken to respond to each symbol, which allows for the calculation of the mean and standard deviation of response times. The test is also broken down into thirds to account for factors like fatigue.
Multi-Platform Compatibility: Developed with Flutter, the app is compatible with both Android and iOS devices, including mobile phones and tablets, ensuring wide accessibility and usability.
Remote Monitoring and Data Management: The app automatically sends the collected metrics to a server, allowing neurologists to monitor their patients' cognitive function remotely. This is critical for patients with mobility issues or those living in remote areas.
The eDSMT app is a digital version of the SDMT designed to overcome these limitations. It was developed to provide a more accessible, accurate, and flexible tool for assessing cognitive deterioration in patients with MS.
Key features include:
Technical architecture and implementation
The eDSMT app's architecture is meticulously designed to support its core functions while ensuring usability and data integrity. The project follows a hybrid methodology, incorporating an iterative-incremental approach similar to Scrum.
The eDSMT app's architecture is meticulously designed to support its core functions while ensuring usability and data integrity. The project follows a hybrid methodology, incorporating an iterative-incremental approach similar to Scrum.
The architecture is structured into several key components:
Screens: This directory contains the UI components for each screen, such as the splash screen, the home screen, the test screen, and the results screen. The UI is built using Flutter widgets and is designed to be as intuitive as possible.
State Management: The app utilizes the Provider library for managing state. This helps to share data between different widgets and ensures that the UI updates correctly.
Utilities (Utils): This section houses various helper functions and classes that are used throughout the application. It includes classes for defining constants, creating custom buttons, and handling the logic for user profiles and tests.
Data Persistence: To save data locally, like user profiles and test history, the app uses SharedPreferences, a Flutter package for storing simple key-value pairs. For data transmission, the app communicates with a backend server, which is essential for remote monitoring.
Security and Privacy: The app prioritizes privacy by using a unique reference code instead of personal identifiers like names. This ensures that even if data is breached, users cannot be personally identified.
Impact and future directions
The eDSMT app has significant impact on both the social and environmental fronts. By making cognitive testing more accessible and convenient for patients, it contributes to SDG 3: Good Health and Well-Being. It also aligns with SDG 9: Industry, Innovation, and Infrastructure by providing an innovative technological solution for healthcare. Additionally, by moving away from paper-based tests, the app contributes to SDG 13: Climate Action by reducing the consumption of paper and ink.
Future plans for the project include:
Clinical Validation: The app requires formal validation according to international standards (e.g., ISO/IEC 62366-1 and ISO 14971) to ensure its accuracy and reliability for clinical use.
Data Analysis and Diagnosis Models: Once a sufficient amount of data is collected, a model of cognitive diagnosis can be developed with the help of AI and machine learning.
Extend Use and Research: The app can be used to gather more data to study the effects of factors like fatigue and the test's responsiveness to changes in cognitive performance over time.
Impact and future directions
The eDSMT app has significant impact on both the social and environmental fronts. By making cognitive testing more accessible and convenient for patients, it contributes to SDG 3: Good Health and Well-Being. It also aligns with SDG 9: Industry, Innovation, and Infrastructure by providing an innovative technological solution for healthcare. Additionally, by moving away from paper-based tests, the app contributes to SDG 13: Climate Action by reducing the consumption of paper and ink.
Future plans for the project include:
