Activity Threshold Calibration for COPD Patient Monitoring
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Solution Overview
Problem
Current physical activity monitors lack a standardized measurement unit to quantify activity levels, making it difficult to distinguish between active and inactive periods, especially for COPD patients with limited exercise capacity, as they use arbitrary units and algorithms that are not universally applicable.
Innovation Solution
An apparatus and method that provide patient-tailored activity thresholds by calibrating activity data based on individual expectations, using regression analysis and receiver operating characteristic curves to classify activity levels into moderate and vigorous intensity categories, allowing for personalized assessment of activity periods and types.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Device complexity
If physical activity monitors use arbitrary measurement units and algorithms, then device complexity is reduced, but measurement precision and reliability are worsened
Solution Approach 1:
The patent changes the parameter of measurement units from arbitrary device-specific units to standardized METs (Metabolic Equivalent of Tasks). This allows different devices to report activity levels in a common, clinically meaningful scale, improving measurement precision and reliability without significantly increasing device complexity.
Solution Approach 2:
The patent creates a universal measurement framework that works across multiple devices and patient populations. By standardizing on METs and using population-based reference ranges, the system achieves universality that improves reliability while maintaining simplicity.
2Measurement precision
If physical activity monitors use standardized measurement units, then measurement precision is improved, but device complexity increases
Solution Approach 1:
The patent introduces an intermediary layer (the standardized METs calculation framework) that sits between the raw accelerometer data and the final activity classification. This intermediary standardizes measurements across devices without requiring complex device-specific algorithms, achieving precision without proportional increases in complexity.
3Ease of operation
If activity thresholds are standardized for general population, then ease of operation is improved, but adaptability is worsened for COPD patients with limited exercise capacity
Solution Approach 1:
The patent applies local quality by providing different activity threshold reference ranges for different patient populations. While the measurement framework is universal (using METs), the interpretation thresholds are localized to specific populations (e.g., COPD patients vs. general population), achieving both ease of operation through standardization and adaptability through population-specific guidelines.
Solution Approach 2:
The patent makes the system dynamic by allowing threshold selection based on patient characteristics. The same measurement framework adapts to different populations by applying appropriate reference ranges, enabling the system to be both easy to operate and highly adaptable.
4Adaptability or versatility
If activity thresholds are personalized for each subject, then adaptability is improved, but device complexity and loss of time for calibration increase
Solution Approach 1:
The patent performs preliminary action by establishing population-based reference ranges in advance. Instead of requiring personalized calibration for each patient, the system uses pre-established thresholds for different populations (e.g., COPD patients, healthy adults), reducing both device complexity and calibration time while maintaining adaptability through appropriate threshold selection.
Solution Approach 2:
The patent enables self-service by allowing the system to automatically select appropriate reference ranges based on patient characteristics without requiring complex personalized calibration procedures. The standardized framework with population-based thresholds provides adaptability through simple, automated selection rather than complex customization.
Data Source
AI summary
The present invention relates to an apparatus (100), system (200), method (300), and computer program for distinguishing between active and inactive time periods of a subject. An input unit (110) receives time-dependent activity data (120) (e.g., corresponding to a level of activity). An activity threshold providing unit (130) provides an activity threshold (140) for the subject. An activity assessment unit (150) classifies the time-dependent activity data (120) based on the activity threshold (140). The activity threshold providing unit (130) provides the activity threshold (140) individually for said subject. The present invention provides an approach to patient-tailor the activity threshold (140) for periods of activity and inactivity.