Markerless Tracking System for Neurological Assessment
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Solution Overview
Problem
Current methods for evaluating Parkinson's disease and other neurological disorders are limited by their subjective nature, infrequent monitoring, and inability to account for individual symptom development, relying on doctor-led evaluations that are time-consuming and not objective.
Innovation Solution
A markerless tracking system using an active 3D infrared camera and electronic processor to capture and analyze body motion data, extracting 3D coordinates for body joints, detecting movements, determining attributes, and assigning ratings based on pre-stored benchmarks, allowing for objective and frequent evaluation of motor exercises without a doctor's presence.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If doctor-led evaluations using established rating scales are used, then subjective assessment of motor exercises can be performed, but the monitoring frequency is limited to 1-2 times per year and the assessment is time-consuming
Solution Approach 1:
The system enables subjects to perform self-evaluations at home using the automated tracking system, eliminating the need for doctor presence during each assessment. Subjects can complete motor exercises and receive automated ratings anytime, transforming the evaluation process from a doctor-service model to a subject-self-service model that dramatically increases monitoring frequency
Solution Approach 2:
The patent replaces the mechanical system of doctor observation and manual rating with an automated electronic system using 3D infrared cameras, computer vision algorithms, and automated rating algorithms. This substitution eliminates the time constraints of doctor schedules and enables continuous, high-frequency monitoring without additional human resources
2Ease of operation
If doctor observation is used to evaluate motor exercises, then ratings can be assigned based on prescribed guidelines, but the guidelines are subjective and open to interpretation
Solution Approach 1:
The system replaces the subjective human judgment mechanism with an automated computer vision system that objectively measures movement parameters. The 3D infrared cameras capture precise spatial and temporal data, and algorithms automatically calculate metrics such as movement amplitude, velocity, and rhythm, eliminating interpreter variability while maintaining ease of operation through automated processing
Solution Approach 2:
The system transitions from 2D visual observation to 3D quantitative measurement by using 3D infrared cameras to capture depth information and spatial coordinates. This dimensional change enables precise measurement of movement parameters that are impossible to accurately assess through visual inspection alone, such as exact tremor amplitude in millimeters or precise gait velocity
3Adaptability or versatility
If fixed rating scales are used for all subjects, then standardized assessment can be performed, but individual symptom development rates are not accounted for
Solution Approach 1:
The system implements dynamic, adaptive rating scales that automatically adjust benchmarks based on each subject's historical performance and individual progression rate. Rather than using fixed thresholds, the system continuously learns each subject's baseline and adjusts evaluation criteria to account for individual symptom development rates, enabling personalized assessment without manual intervention
Solution Approach 2:
The system incorporates continuous feedback loops where each assessment result feeds into updating the subject's individual profile and adjusting future evaluation benchmarks. This feedback mechanism enables the system to adapt to individual progression rates over time, personalizing the assessment criteria based on each subject's unique trajectory while maintaining standardized processing
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
Enables objective and frequent monitoring of neurological disease progression, providing detailed session records that can be used to track changes in motor functions and medication efficacy, and potentially identifying early indicators of Parkinson's disease.
Implementation Method 1
an active 3D infrared camera captures depth data of a body of the subject
Implementation Method 2
captures depth data of a body of the subject during the motor exercise
Data Source
AI summary
Markerless tracking systems and methods for markerless tracking of subjects. In one embodiment, the markerless tracking system includes an active 3D infrared camera, a memory, and an electronic processor. The electronic processor is configured to extract body motion data for a subject's body from depth data captured by the active 3D infrared camera. The electronic processor is also configured to detect movements of the subject's body using the body motion data. The electronic processor is further configured to determine attributes for the movements of the subject's body using the body motion data. The electronic processor is also configured to assign a rating by comparing the determined attributes with a plurality of benchmarks included in a pre-stored movement profile in the memory. The electronic processor is further configured to create a session record for the subject. The session record includes the body motion data, the determined attributes, and the assigned rating.