Wearable Sensor System for Objective Movement Disorder Scoring
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Solution Overview
Problem
Current methods for evaluating the severity of movement disorders, such as Parkinson's disease, are subjective and lack objectivity, leading to varying scores between clinicians and inadequate monitoring of symptoms, particularly in patients with motor fluctuations, which affects treatment efficacy and patient management.
Innovation Solution
A system using miniaturized sensors like gyroscopes and accelerometers to measure kinematic features from movement data, processed by a trained algorithm to produce scores correlated with the Unified Parkinson's Disease Rating Scale (UPDRS), allowing for objective and quantitative assessment of tremor, bradykinesia, and dyskinesia, with the ability to generate scores in a short time frame.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If visual observation and subjective scoring by clinicians is used, then evaluation can be conducted without specialized equipment, but measurement precision and objectivity deteriorate due to inter-rater and intra-rater variability
Solution Approach 1:
The patent replaces the mechanical/visual observation system with an electronic sensor-based measurement system. Accelerometers and gyroscopes objectively capture movement parameters, eliminating subjective clinician variability while providing quantifiable data for movement disorder assessment.
Solution Approach 2:
The patent introduces sensors as an intermediary between the patient's movement and the clinician's assessment. The sensors act as mediators that translate physical movement into objective numerical data, which then informs clinical decision-making without requiring direct visual observation.
2Productivity
If periodic office visit monitoring is used, then treatment evaluation can be conducted, but frequency of measurement decreases limiting detection of motor fluctuations
Solution Approach 1:
The patent enables continuous monitoring of movement parameters through wearable sensors that patients can use at home. This continuous data collection captures motor fluctuations throughout the day without requiring repeated office visits, providing a comprehensive view of symptom variability.
Solution Approach 2:
The patent allows patients to self-monitor their own symptoms using portable devices at home. Patients independently collect movement data without requiring clinician presence or office visit time, empowering them to actively participate in their own assessment while reducing healthcare system burden.
3Measurement precision
If simple statistics like displacement and peak frequency are computed, then processing speed increases, but measurement precision deteriorates due to inadequate capture of movement disorder complexity
Solution Approach 1:
The patent segments the complex movement disorder assessment into multiple distinct computational components: extracting individual kinematic parameters (amplitude, frequency, velocity), analyzing temporal patterns, and integrating multiple sensor inputs. This segmentation allows comprehensive characterization while maintaining computational manageability.
Solution Approach 2:
The patent moves from simple one-dimensional statistics to multi-dimensional analysis by incorporating spatial orientation data from gyroscopes, temporal dynamics from accelerometers, and pattern recognition across multiple movement parameters. This dimensional expansion enables more precise symptom characterization.
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
The system provides objective, quantitative scores that correlate well with clinician-assigned UPDRS scores, improving the resolution and frequency of symptom evaluation, aiding in treatment protocol evaluation and patient management, and enabling more precise treatment recommendations.
Implementation Method 1
uses a miniature gyroscope to measure rotational motion on a hand
Implementation Method 2
uses a miniature 3-axis accelerometer to measure linear acceleration on a hand
Data Source
AI summary
A system and method for scoring movement disorder symptoms comprises a movement measurement data acquisition system and processing comprising kinematic feature extraction and an algorithm trained using Unified Parkinson's Disease Rating Scale (UPDRS) scores from skilled clinicians. The movement data acquisition system, or “movement measuring apparatus,” may comprise sensors such as accelerometers or gyroscopes or may utilize motion capture and/or machine vision technology or various other methods to measure tremor, bradykinesia, dyskinesia, or other movement disorders in a subject afflicted with Parkinson's disease, essential tremor or the like. The method outputs, and system displays, a score that uses the same scale as the UPDRS but has greater resolution and lower variability. In some embodiments, the system is used to diagnose and/or treat the patient by providing recommendations for treatment and/or by supplying treatment in the form of pharmaceutical drugs and/or electric stimulus as part of a closed-loop system.