Computerized Cognitive Motor Testing System with Dynamic Difficulty Adjustment
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Current systems for assessing neuromotor and neurocognitive disorders, such as Alzheimer's and Parkinson's Disease, lack the ability to objectively and qualitatively measure cognitive and motor functions, and do not dynamically adjust test difficulty based on user performance, nor provide data on medication effects or Deep Brain Stimulation parameters.
Innovation Solution
A computerized system that records and analyzes positional and time data at a high sampling rate to assess user movement quality, generating kinematic data and adjusting test parameters based on performance, allowing for the classification and tracking of disorders, and correlating results with treatment changes.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If computerized systems measure only reaction time and completion time, then testing efficiency is improved, but measurement precision of cognitive and motor functions deteriorates
Solution Approach 1:
The system segments the measurement process into multiple independent components: reaction time measurement, movement trajectory analysis, speed and acceleration calculation, and quality assessment. Each component provides specific insights, allowing comprehensive evaluation without sacrificing efficiency. The segmentation enables parallel processing of different measurement aspects simultaneously.
Solution Approach 2:
The patent transitions from one-dimensional time-based measurement to multi-dimensional analysis by incorporating spatial coordinates (x, y positions), velocity vectors, acceleration vectors, and quality metrics. This dimensional expansion allows the system to capture the complexity of cognitive and motor functions while maintaining automated testing efficiency.
2Device complexity
If test difficulty is fixed, then system complexity is reduced, but adaptability to user performance deteriorates
Solution Approach 1:
The system implements dynamic test adjustment where difficulty parameters (such as target size, distance between targets, or movement requirements) are automatically modified based on real-time performance analysis. The system monitors speed, accuracy, and movement quality, then adapts subsequent test items to match the user's current ability level, creating a personalized testing experience without requiring complex manual intervention.
Solution Approach 2:
The system incorporates continuous feedback loops where performance data from each test item is analyzed and used to adjust subsequent test parameters. The feedback mechanism ensures that the test difficulty aligns with user performance, maintaining optimal challenge levels while reducing the need for pre-programmed fixed difficulty scenarios.
3Measurement precision
If high sampling rate is used for movement analysis, then measurement precision of movement quality is improved, but data processing complexity increases
Solution Approach 1:
The system extracts and processes only the critical components of movement data at high sampling rates: position coordinates, velocity vectors, acceleration vectors, and quality metrics. By selectively extracting and analyzing only these essential parameters rather than processing every raw data point, the system maintains high measurement precision while managing data processing complexity through targeted analysis of meaningful variables.
Data Source
AI summary
A cognitive and/or motor skill testing system and method may include a processor that records respective time information for each of multiple positions of a display device that are traced during administration of a test, that determines speed and/or velocity values based on the recorded time information, and that outputs test result information based on the determined values. The test result information may be based on a comparison between a graphed curve of such values to an ideal curve. The positions may correspond to a path between displayed targets whose size and/or distance therebetween depend on past test performance. The system and/or method may output a change expected with a change to therapy parameters for a patient, where the expected change is determined based on changes which occurred in other patients having similar test results and therapy parameters as those of the patient.