Wearable Accelerometer Motion Symptom Assessment
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Solution Overview
Problem
Current methods for monitoring and managing Parkinson's disease symptoms, particularly bradykinesia and dyskinesia, are subjective and lack objective measures, making it difficult for clinicians to determine the progression of the disease and the need for advanced therapies, leading to inadequate or excessive medication dosages and delayed referrals for treatments like deep brain stimulation.
Innovation Solution
A method using a wearable accelerometer to collect kinetic data over an extended period, processing it to measure dispersion in kinetic states, and generating outputs indicating whether symptoms are at an initial or advanced stage, providing a quantitative tool for clinicians to assess disease progression and therapy needs.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If conventional clinical observation methods are used, then clinicians can assess patient symptoms during brief visits, but the assessment is subjective and lacks objective measures to accurately determine disease progression
Solution Approach 1:
The patent replaces subjective clinical assessment with objective accelerometer-based kinetic state measurement. The accelerometer device automatically quantifies motor fluctuations (bradykinesia and dyskinesia) through mechanical motion detection, eliminating the need for subjective physician evaluation and patient self-reporting during clinical visits.
Solution Approach 2:
The system enables self-monitoring where the accelerometer device automatically collects and processes kinetic state data without requiring active patient participation or clinical intervention. The device continuously monitors motor symptoms during everyday activities and automatically determines disease progression stage, freeing patients from the burden of manual symptom tracking.
2Reliability
If clinicians increase monitoring frequency to track disease progression, then more accurate dosage control can be achieved, but patient burden and loss of time increase significantly
Solution Approach 1:
The accelerometer device provides continuous monitoring of kinetic state during everyday activities over extended periods (weeks to months). This continuous data collection captures the full pattern of motor fluctuations throughout the day and across multiple days, enabling reliable dosage control decisions without requiring frequent clinical visits or intensive patient reporting.
Solution Approach 2:
The system creates an objective digital copy of the patient's motor symptom pattern through accelerometer data. This digital representation of kinetic state replaces the need for repeated subjective patient recollections and written diaries, providing a permanent, objective record that can be analyzed to determine disease progression and guide dosage adjustments.
3Loss of information
If subjective patient self-reporting is used to monitor kinetic state, then continuous data can be collected, but patients cannot provide objective scores and motor fluctuations make recording difficult
Solution Approach 1:
The accelerometer device performs self-measurement of kinetic state without requiring patient action. The device automatically detects and quantifies motor fluctuations during everyday activities, eliminating the need for patients to manually record symptoms or provide subjective scores. This self-measuring capability ensures complete and objective data collection regardless of patient cognitive state or motor impairment.
4Reliability
If delayed referral for advanced therapies occurs, then conventional treatment can be maintained longer, but the window for effective deep brain stimulation may be missed
Solution Approach 1:
The patent replaces complex clinical expertise-based assessment with automated accelerometer-based kinetic state analysis. The device objectively quantifies motor fluctuations and automatically determines when disease progression indicates readiness for advanced therapies, removing dependence on clinician experience and ensuring timely, consistent referral decisions.
Data Source
AI summary
A state of progression in an individual of a disease or treatment having motion symptoms is determined. A time series of accelerometer data is obtained from an accelerometer worn on an extremity of the person, over an extended period during everyday activities of the person. The accelerometer data is processed to produce a plurality of measures of kinetic state of the individual at a respective plurality of times throughout the extended period, each measure of kinetic state comprising at least one of: a measure for bradykinesia, and a measure for dyskinesia. A measure of dispersion of the measures of kinetic state is determined. An output is generated, indicating that motion symptoms are at an initial stage if the measure of dispersion is less than a threshold, or indicating that motion symptoms are at an advanced stage if the measure of dispersion is greater than the threshold.