Sleep Management System Using Hub Device for Accurate Non-Contact State Detection
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Solution Overview
Problem
Current sleep management systems face challenges in accurately measuring sleep states without attaching multiple sensors to the body, leading to discomfort and low accuracy compared to polysomnography.
Innovation Solution
A sleep management system comprising a hub device that processes data from multiple sensors, a user device that analyzes the processed data using a machine learning model to determine sleep state information, and a server device that controls home appliances based on the sleep state information, all without the need for sensors attached to the body.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If polysomnography is used to detect sleep disorders, then measurement precision is improved, but device complexity and discomfort increase due to various sensors attached to the body
Solution Approach 1:
The patent introduces a hub device as an intermediary between the user device and the server device. The hub device collects and processes sensor data locally, then transmits only processed information to the server, reducing the complexity of direct body attachments while maintaining measurement accuracy through centralized processing
Solution Approach 2:
The system divides functionality into separate components: user devices collect basic data, the hub device performs complex processing, and the server device analyzes sleep states. This segmentation allows each component to focus on specific tasks, reducing overall system complexity while maintaining precision
2Measurement precision
If multiple sensors are attached to measure sleep state accurately, then measurement precision is improved, but ease of operation deteriorates due to discomfort
Solution Approach 1:
The patent extracts the complex sensor processing functions from the user's body and relocates them to the hub device. This allows simple, comfortable user devices to collect basic data while the hub handles complex analysis, maintaining accuracy without body attachment discomfort
Solution Approach 2:
The system replaces direct mechanical sensor attachment to the body with a distributed processing architecture where computational functions substitute for physical sensor complexity, enabling accurate measurement without uncomfortable body attachments
3Reliability
If individual devices process all sleep data locally, then privacy is protected, but device complexity and processing burden increase
Solution Approach 1:
The patent segments data processing across multiple devices: user devices collect data, the hub device performs intermediate processing and reduces data volume, and the server device conducts final analysis. This segmentation distributes the processing burden while maintaining privacy through localized data handling
Solution Approach 2:
The hub device performs preliminary data processing and filtering before transmitting to the server, reducing the amount of data that needs to be processed later. This preliminary action decreases the overall processing burden while maintaining privacy through local data handling
Data Source
AI summary
A sleep management system includes: receiving, by a hub device, first data collected by a first sensor and second data collected by a second sensor; obtaining, by the hub device, first processed data by processing the first data and second processed data by processing the second data; transmitting, by the hub device, the first processed data and the second processed data to a user device; obtaining, by the user device, sleep state information by inputting the first processed data and the second processed data to a machine learning model of the user device, wherein the sleep state information is associated with a sleep state of a user; and transmitting, by the user device, the sleep state information to a server device.