Wearable Device Adaptive Data Collection for Battery Life
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Solution Overview
Problem
Wearable devices face a challenge in balancing continuous data collection for health insights with limited battery life due to increased power consumption, as they need to recharge frequently and struggle to optimize data collection based on changing physiological parameters.
Innovation Solution
Implementing a data collection strategy that reduces the frequency of data acquisition when physiological parameters show little change, using different periodicities for data collection based on parameter stability, and discarding or storing data quality metrics accordingly to conserve power and memory.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If continuous data collection is performed to enable comprehensive health monitoring, then measurement precision and reliability are improved, but power consumption increases and battery life decreases
Solution Approach 1:
The patent applies dynamics by making the data collection frequency adjustable rather than fixed. The system dynamically changes the periodicity of physiological parameter measurements based on detected changes in user state or environmental conditions, allowing continuous monitoring capability while adapting to actual needs to conserve energy.
Solution Approach 2:
The patent changes the parameter of data collection periodicity based on detected conditions. When significant physiological changes are detected, the system increases monitoring frequency; when parameters remain stable, it reduces frequency. This parameter adjustment resolves the contradiction between continuous monitoring and energy conservation.
2Reliability
If data collection frequency is increased to capture significant physiological changes, then measurement reliability is improved, but power consumption increases
Solution Approach 1:
The patent implements feedback by continuously monitoring physiological parameters and using this information to adjust data collection frequency. When the system detects that parameters remain within normal ranges, it reduces sampling frequency to save energy. When significant deviations are detected, it increases frequency to capture the event, thus maintaining reliability while conserving power.
Solution Approach 2:
The patent uses periodic action by implementing variable-frequency sampling rather than continuous monitoring. The system performs measurements at regular intervals during stable periods, and increases frequency during periods of detected change, creating an adaptive periodic measurement scheme that balances reliability and energy consumption.
3Loss of information
If data is stored at high frequency to ensure complete health records, then information completeness is improved, but memory usage increases and power consumption increases
Solution Approach 1:
The patent changes the storage frequency parameter based on the importance and variability of the data being collected. High-frequency data is stored only when significant physiological events are detected, while routine stable-period data is stored at lower frequency or summarized, reducing memory usage and associated energy consumption while preserving critical health information.
Data Source
AI summary
Methods, systems, and devices for data optimization are described. A wearable device may be configured to acquire physiological data associated with a physiological parameter of a user throughout a first time interval using the one or more sensors of the wearable device, where the physiological data is acquired according to a first periodicity based on one or more deviations in the physiological data failing to satisfy a deviation threshold. The wearable device may then determine that one or more additional deviations in the physiological data satisfy the deviation threshold, and may acquire additional physiological data associated with the physiological parameter throughout a second time interval according to a second periodicity that is greater than the first periodicity based on the one or more additional deviations satisfying the deviation threshold. The wearable device may then transmit at least the additional physiological data to a user device.