Wearable Sleep State Detection and Alert System
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Solution Overview
Problem
Wearable devices are unable to effectively manage sleep for users, leading to negative impacts on health and wellness due to inadequate insights and timing of sleep activities like napping.
Innovation Solution
A system that includes wearable devices and user devices to collect physiological data, detect sleep states, and alert users to prevent deep sleep transitions or manage nap duration based on heart rate, respiratory rate, and other data to promote improved relaxation, reduced fatigue, and increased alertness.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If wearable devices collect sleep data to provide insights, then user understanding of sleep patterns is improved, but the device's ability to actively manage sleep is insufficient
Solution Approach 1:
The system continuously monitors physiological data during sleep and provides real-time feedback through alerts and notifications. The processor analyzes heart rate, respiratory rate, and movement data to detect sleep states and delivers feedback to the user about their sleep quality and transitions, enabling active sleep management rather than passive data collection.
Solution Approach 2:
The wearable device autonomously manages sleep by automatically detecting sleep states through physiological sensors and triggering appropriate responses without requiring user intervention. The system self-adjusts by monitoring its own collected data and independently determining when to provide alerts or notifications about sleep transitions.
2Measurement precision
If the system monitors physiological data continuously to detect sleep states, then detection accuracy is improved, but energy consumption increases
Solution Approach 1:
The system employs periodic sampling of physiological data rather than continuous monitoring. The processor checks physiological parameters at intervals to detect changes in sleep states, maintaining detection accuracy while reducing overall power consumption compared to uninterrupted monitoring.
Solution Approach 2:
The monitoring intensity dynamically adjusts based on detected sleep states. During stable sleep phases, monitoring frequency is reduced to conserve energy, while during transition periods or when anomalies are detected, the system increases monitoring intensity to maintain detection accuracy.
Data Source
AI summary
Methods, systems, and devices for managing sleep are described. A method may include acquiring physiological data associated with a user from a wearable device, the physiological data including at least heart rate data associated with the user. The method may include detecting whether the user is beginning to transition into a sleep state of a set of sleep states based on the acquired physiological data. The method may include causing a user device to output a response before the user transitions into the sleep state or based on a timer lapsing before the user transitions into the sleep state.