Handheld Sensor Tool for Objective Movement Disorder Diagnosis
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Solution Overview
Problem
Current methods for diagnosing movement disorders such as Parkinson's Disease and Essential Tremor are subjective and prone to errors due to their reliance on clinical assessments and patient self-reporting, making it challenging to develop and evaluate effective treatments.
Innovation Solution
A handheld tool equipped with sensors and a task detection module that analyzes user performance during everyday tasks, providing objective data on bradykinesia, tremors, and other conditions by measuring motion and comparing it to predefined criteria, allowing for more accurate evaluation and potential compensation for unintentional muscle movements.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If clinical assessment methods are used to diagnose movement disorders, then the diagnosis can be performed with existing clinical tools, but the assessment is subjective and prone to errors due to intra-clinician variability
Solution Approach 1:
The patent replaces subjective clinical assessment with an automated sensor-based system that uses accelerometers, gyroscopes, and other sensors to objectively measure movement parameters. This substitution of mechanical/sensor-based measurement for human clinical judgment eliminates intra-clinician variability and provides consistent, quantifiable data for diagnosis and treatment evaluation.
Solution Approach 2:
The patent introduces a computational intermediary system that processes sensor data, compares movements against reference patterns, and generates diagnostic evaluations. This intermediary layer between the patient's movement and the diagnostic conclusion standardizes the assessment process and removes human subjectivity while maintaining diagnostic accuracy.
2Ease of operation
If patient self-reporting is used to evaluate symptom severity, then the evaluation can be performed at home without clinical visits, but the self-reporting is highly subjective and prone to error
Solution Approach 1:
The patent enables patients to perform self-monitoring at home using a portable device that automatically collects movement data without requiring clinical visits. The system serves itself by autonomously sensing, processing, and evaluating movement parameters, providing objective symptom severity assessment that combines the accessibility of home monitoring with the accuracy of clinical-grade measurement.
Solution Approach 2:
The patent replaces subjective patient self-reporting with automated sensor-based measurement that objectively quantifies movement symptoms. The sensor system directly measures tremor amplitude, bradykinesia severity, and other motor symptoms, eliminating the subjectivity and inaccuracy inherent in patient self-assessment while maintaining the convenience of home-based evaluation.
3Loss of time
If subjective clinical scales are used for diagnosis, then the diagnosis can be performed during brief clinical visits, but the subjective nature during brief periods makes assessments prone to errors
Solution Approach 1:
The patent enables continuous movement monitoring and data collection over extended periods, allowing the system to accumulate sufficient data for accurate diagnosis without requiring lengthy clinical visits. The continuous sensing captures multiple movement cycles and patterns, providing robust data that improves diagnostic accuracy while maintaining efficient time utilization.
Solution Approach 2:
The patent performs preliminary data collection and processing by the portable device before clinical evaluation, so that during the brief clinical visit, the clinician receives pre-processed, objective movement data that accelerates the diagnostic process. The system prepares movement logs, statistical summaries, and anomaly detections in advance, making the most of limited clinical time while ensuring diagnostic accuracy through comprehensive prior measurement.
Data Source
AI summary
Techniques and methods for evaluating an instance of a pre-defined task being performed by a user with a handheld tool. In an embodiment, measurement information is stored to a log based on sensor data generated during motion of the handheld tool. Based on a definition of a task and the logged measurement information, a determination is made as to whether the sensed motion corresponds to a performance of at least some action of the defined task. In another embodiment, the definition of the task includes or otherwise corresponds to criteria information. The performance of the task is evaluated based on the criteria information to detect bradykinesia or some other unintentional muscle performance of the user.