Dynamic Sampling Rate for Fall Detection Power Efficiency
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Solution Overview
Problem
Existing fall detection systems for humans, particularly those worn by individuals, face challenges in balancing power consumption and detection accuracy, with current methods either consuming too much power or compromising on accuracy to extend battery life.
Innovation Solution
A monitoring system that adjusts the sampling rate of movement detection sub-systems based on physiological and environmental signals, switching to higher sampling rates during abnormal physiological activity or environmental changes to enhance detection accuracy while minimizing power consumption.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If the movement detection sub-system operates at a high sampling rate continuously, then the detection accuracy is improved, but the power consumption increases
Solution Approach 1:
The sampling rate of the movement detection sub-system is made dynamic rather than static. The system automatically adjusts the sampling rate based on the physiological state detected by biosensors. When abnormal physiological conditions are detected, the sampling rate increases to high levels for accurate fall detection. When physiological conditions are normal, the sampling rate decreases to low levels to conserve power. This dynamic adaptation resolves the contradiction between maintaining high detection accuracy and reducing power consumption.
Solution Approach 2:
The system changes the operational parameters (sampling rate) of the movement detection sub-system based on physiological signal analysis. By monitoring physiological parameters such as heart rate, blood pressure, or other biosensor signals, the system determines when to switch between different sampling rates. This parameter adjustment allows the system to maintain high detection accuracy only when necessary, thereby significantly reducing overall power consumption while preserving measurement precision when needed.
2Duration of action of moving object
If the sampling rate is reduced to extend battery life, then the power consumption is reduced, but the detection accuracy deteriorates
Solution Approach 1:
The system implements periodic monitoring of physiological signals to determine when high-accuracy movement detection is needed. Instead of continuously operating at high sampling rates, the system periodically checks physiological status and adjusts movement detection accordingly. This periodic action allows the system to extend battery life by operating at low sampling rates during normal periods while ensuring detection accuracy is maintained during abnormal periods when falls are more likely to occur.
Solution Approach 2:
The system performs preliminary detection of physiological signals to predict or identify abnormal states before falls occur. By monitoring physiological parameters in advance, the system can prepare to switch to high sampling rate mode when abnormal conditions are detected, ensuring that detection accuracy is maintained precisely when needed. This preliminary action prevents the need for continuous high-power operation while preserving detection capability.
3Measurement precision
If physiological signal monitoring is continuously performed, then the detection accuracy is improved, but the power consumption increases
Solution Approach 1:
The system applies partial monitoring of physiological signals rather than continuous full-scale monitoring. Instead of constantly analyzing all physiological parameters at high resolution, the system performs partial monitoring that is sufficient to detect abnormal states. This partial action provides enough information to trigger appropriate movement detection modes without consuming excessive power, thus resolving the contradiction between detection accuracy and power consumption.
Data Source
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AI summary
To improve the power efficiency of a monitoring system, especially for worn devices, the present invention provides a monitoring system (300) comprising a physiological signal monitor (310) configured to monitor at least one physiological signal; a processor (320) configured to receive the output signal of the physiological signal monitor and detect an abnormal occurrence of at least one physiological signal; and a movement detection sub-system (330) coupled to receive the output signal of the processor and configured to monitor the movement of a target body, based on the output signal of the processor, for detecting the abnormal situation. The power consumption of the whole system can be decreased by using the monitoring result of physiological signals as a trigger for the movement detection sub- system.