Wearable Sensor Sleep State Detection Power Management
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Solution Overview
Problem
Current wearable devices face high power consumption and short battery life due to continuous physiological data collection during long-time sleep monitoring, leading to poor user experience.
Innovation Solution
A method and apparatus that detect when a user falls asleep and only enable sensors when the user is likely to be in long-time sleep, based on historical sleep data and thresholds, to reduce unnecessary data collection and power usage.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If sensors are continuously enabled to collect physiological data during long-time sleep, then sleep monitoring accuracy is improved, but power consumption increases and battery life decreases
Solution Approach 1:
The system performs preliminary detection of sleep state before enabling the sensor. The detection unit detects whether the user is in a sleep state, and only when sleep is detected does the control unit enable the sensor for physiological data collection. This preliminary action avoids unnecessary sensor activation during awake periods, resolving the contradiction between monitoring accuracy and power consumption.
Solution Approach 2:
The sensor activation state is dynamically adjusted based on detected sleep patterns. The system transitions from continuous activation to conditional activation based on sleep detection, optimizing the balance between data collection quality and energy consumption in real-time.
2Quantity of substance
If sensors are continuously enabled to collect physiological data, then complete sleep data is obtained, but battery life is reduced
Solution Approach 1:
The detection unit performs preliminary sleep state detection before sensor activation. Only when sleep state is confirmed does the system enable the sensor for physiological data collection. This ensures data is collected only during relevant periods (sleep), maximizing data quality while minimizing energy consumption and extending battery life.
Solution Approach 2:
The system extracts and isolates the specific condition (sleep state) that requires monitoring, separating it from unnecessary monitoring during awake periods. By taking out only the essential monitoring periods, the system obtains sufficient sleep data while significantly reducing overall sensor activation time and power consumption.
3Adaptability or versatility
If sensors are enabled for every sleep period including short-time sleep, then all sleep events are monitored, but power consumption increases unnecessarily
Solution Approach 1:
The system performs preliminary detection of both sleep state and wake state. By detecting wake state as a termination condition, the system can identify short-time sleep events (when wake state occurs quickly after sleep detection) and differentiate them from long-time sleep. This allows selective monitoring that covers all sleep events while avoiding unnecessary energy consumption during brief sleep periods.
Solution Approach 2:
The system uses feedback from continuous wake/sleep state detection to dynamically adjust sensor activation. The detection of wake state provides feedback that helps distinguish between short-time and long-time sleep, enabling the system to optimize sensor usage based on actual sleep patterns and reduce power consumption during brief sleep events.
Data Source
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AI summary
A physiological data collection method and apparatus, and a wearable device (100) are provided, and are applicable to the field of data collection technologies. The method includes: when it is detected that a user falls asleep, identifying whether a first quantity of times that the user enters long-time sleep within a first time period is less than a quantity-of-time threshold; when a threshold of the first quantity of times is less than the quantity-of-time threshold, enabling a first sensor, and collecting first physiological data of the user by using the first sensor; when it is detected that the user wakes up, disabling the first sensor. Compared with keeping a related sensor enabled all day, this method can reduce a large amount of sensor collection work. In addition, setting the quantity-of-time threshold makes it less probable to enable a related sensor for short-time sleep. Therefore, according to this method, a workload of collecting physiological data during long-time sleep by the sensor can be reduced as well as power consumption, for lower electricity consumption and a longer battery life of the wearable device (100).