COPD Risk Assessment via Active and Rest Activity Ratios
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Solution Overview
Problem
Current methods for predicting exacerbations in Chronic Obstructive Pulmonary Disease (COPD) patients only assess physical activity during active periods, neglecting the impact of symptoms during rest periods, which can lead to inaccurate risk assessment and increased hospitalizations.
Innovation Solution
An apparatus and system that measure and compare physical activity data during both active and rest periods, using ratios or differences in activity levels to assess the risk of exacerbation and hospitalization, with a risk assessment unit determining if the activity data meets predetermined criteria related to activity levels, and optionally generating an alarm for increased risk.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If physical activity is only monitored during active periods, then the monitoring system is simpler and easier to operate, but the risk assessment accuracy deteriorates because rest period symptoms are neglected
Solution Approach 1:
The monitoring period is segmented into active periods and rest periods, with separate activity thresholds applied to each segment. This allows comprehensive assessment without requiring continuous complex monitoring, as each segment can be evaluated independently with appropriate simplicity
Solution Approach 2:
The system monitors activity continuously but only triggers alerts when activity falls below thresholds during rest periods or below thresholds during active periods. This partial action approach focuses computational resources on critical assessment moments rather than continuous complex analysis
2Reliability
If activity thresholds are set to detect all potential exacerbations, then the detection sensitivity improves, but the number of false alarms increases
Solution Approach 1:
Different activity thresholds are applied to different time periods: a first threshold for active periods and a second, higher threshold for rest periods. This local differentiation allows sensitive detection during rest when even minor activity drops are concerning, while being less sensitive during active periods when lower activity is normal
Solution Approach 2:
The system dynamically adjusts the expected activity level based on the time of day and patient's normal patterns. During rest periods, the system expects low activity and triggers alerts only for abnormal drops, while during active periods it allows for more variability, reducing false alarms while maintaining detection sensitivity
Data Source
AI summary
The present invention relates to an apparatus, a system (100), a method (200), and a computer program for assessing the risk of an exacerbation and/or hospitalization. A patient's physical activity is measured (e.g., by an accelerometer (110)) during an active period of time (e.g., during awake hours) and during a rest period of time (e.g., during sleep hours) to gather first and second activity data. A risk of exacerbation and/or hospitalization is assessed (e.g., by a risk assessment unit (120)) based on an expression involving the respective activity data during active and rest periods fulfilling a predetermined relationship with respect to a predetermined activity level. For instance, low activity data during active periods and high activity data during rest periods indicates an increased risk of exacerbation and/or hospital readmission for the patient.