MET Data Monitoring for Cardiac Rehabilitation Adherence
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Solution Overview
Problem
Current methods for monitoring adherence to cardiac rehabilitation guidelines rely on subjective measures like Borg RPE and CR10 scales, which are unreliable due to their subjective nature and influence from factors unrelated to physical activity, such as emotional state and medication, limiting the accuracy of tracking recommended physical activity levels.
Innovation Solution
A system and method utilizing Metabolic Equivalent (MET) data collection and processing to determine if a user has met the recommended level of physical activity, comparing MET data to guideline values to provide adherence results, and identifying potential health risks by analyzing activity measures like sedentary time, calorie burn, and physical activity energy expenditure.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If subjective measures like Borg RPE and CR10 scales are used to monitor physical activity adherence, then ease of operation is improved, but measurement precision deteriorates due to subjective nature and influence from factors unrelated to physical activity
Solution Approach 1:
The patent replaces subjective, manual self-reporting methods (Borg RPE and CR10 scales) with objective, automated electronic monitoring devices that continuously track physiological parameters. This substitution eliminates human subjectivity and provides precise, quantifiable data on physical activity intensity and adherence to rehabilitation guidelines.
Solution Approach 2:
The patent introduces an intermediary electronic monitoring system that acts as a mediator between the patient's physical activity and the healthcare provider's assessment. This intermediary continuously collects, processes, and transmits objective physiological data, replacing the direct but imprecise subjective reporting chain with an automated data collection and analysis system.
2Measurement precision
If heart rate monitoring is used to objectively measure physical activity, then measurement precision is improved, but reliability deteriorates due to influence from factors not related to physical activity such as emotional state, diet and medication
Solution Approach 1:
The patent merges multiple physiological monitoring parameters (heart rate, activity intensity, duration) with contextual data (structured exercise sessions versus daily activities) to create a comprehensive adherence assessment. This combination allows the system to distinguish between heart rate changes caused by physical activity versus those caused by emotional state, diet, or medication, thereby improving reliability while maintaining objective measurement precision.
Solution Approach 2:
The patent implements dynamic monitoring that continuously adjusts baseline expectations and intensity thresholds based on individual patient progress and contextual factors. The system adapts to changing conditions by comparing actual physiological responses against dynamically updated guidelines, allowing it to account for variations due to diet, medication, or emotional state while maintaining reliable adherence assessment.
3Reliability
If structured supervised exercise sessions are used to monitor adherence, then reliability is improved through close monitoring, but productivity deteriorates due to limited coverage of total physical activity time
Solution Approach 1:
The patent implements a universal monitoring system that functions across multiple contexts - it monitors both structured supervised exercise sessions and unstructured daily physical activities. This multi-functional approach maintains the reliability of supervised session monitoring while extending coverage to all physical activity occurrences, thereby improving overall productivity without sacrificing assessment quality.
Solution Approach 2:
The patent enables continuous monitoring of physical activity throughout the day rather than仅限于 discrete supervised sessions. The electronic monitoring devices continuously collect data on intensity, duration, and type of activity, providing uninterrupted assessment that captures the full spectrum of a patient's physical activity behavior, thereby improving productivity while maintaining reliability through consistent data collection.
Data Source
AI summary
Systems and methods are disclosed for monitoring adherence to healthcare guidelines defining a recommended level of physical activity. Metabolic Equivalent (MET) data for a user over a plurality of days is analysed to determine whether sufficient MET data is available, by determining whether the obtained MET data includes at least a minimum amount of MET data within a defined time period. In response to a determination that sufficient MET data is available, the MET data is compared to guideline MET values relating to the recommended level of physical activity, to determine whether the user has achieved the recommended level of physical activity. An adherence result is outputted in accordance with the result of the comparison, indicating whether the user has achieved the recommended level of physical activity. The adherence result can be outputted in the form of a message displayed on a display unit. In some embodiments when MET data is captured over a plurality of days, it can be checked whether data has been captured for at least a minimum required number of days within a time period, for example one week.