Mattress Pressure Arrays for Privacy-Safe Sleeping Posture Recognition
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Solution Overview
Problem
Existing methods for recognizing sleeping posture at night are hindered by the obstruction of blankets and violate user privacy through camera-based image recognition.
Innovation Solution
A sleeping posture recognition system using a pressure sensor array on a mattress to detect body pressure data, which is converted into a two-dimensional array and processed by a deep neural network for accurate posture recognition, addressing privacy concerns and improving accuracy.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If a camera is used to capture sleeping posture images, then image recognition can be performed, but user privacy is violated and data capture is blocked by blankets
Solution Approach 1:
The patent replaces the optical measurement system (camera) with a mechanical pressure sensing system. Pressure sensors embedded in the mattress detect body pressure distribution to determine sleeping posture, eliminating the need for visual capture and thus resolving privacy concerns and blanket obstruction issues while maintaining recognition capability
Solution Approach 2:
The patent introduces pressure distribution data as an intermediary between the user's body and the recognition system. Instead of directly capturing images of the user, the system measures pressure patterns indirectly, which then serve as the basis for posture recognition through deep learning models
2Ease of operation
If blankets are used during nighttime sleep, then user comfort and privacy are maintained, but camera-based data capture is blocked
Solution Approach 1:
The patent replaces optical detection with mechanical pressure sensing, allowing users to sleep with blankets without interfering with detection. The pressure sensors beneath the mattress surface can detect body position through the blanket, maintaining both user comfort and detection capability
Solution Approach 2:
The patent extracts the detection function from the visual domain to the mechanical domain. By removing the camera and introducing pressure sensors, the system separates detection from visual capture, allowing blankets to remain in place while still enabling posture recognition through pressure distribution patterns
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
Enhances sleeping posture recognition accuracy and resolves privacy issues by utilizing a mattress-integrated pressure sensor array and deep neural network, ensuring precise posture identification without camera intrusion.
Implementation Method 1
a pressure sensor array is deployed in a sleeping position on a mattress to obtain body pressure data
Data Source
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AI summary
Disclosed in the present invention are a sleeping posture recognition method and system based on a deep neural network. The method comprises the steps of: inputting body pressure sample data into a deep neural network for training learning, to obtain a sleeping posture recognition model; obtaining a two-dimensional body pressure array in real time by using a detection device, the detection device obtaining two-dimensional body pressure analog signal data by means of a pressure sensor array, and converting the two-dimensional body pressure analog data into the two-dimensional body pressure array by means of an A/D conversion module; and transmitting the two-dimensional body pressure array to a server for preprocessing, and inputting the preprocessed two-dimensional body pressure array into the sleeping posture recognition model for recognition. According to the present invention, the pressure sensor array is provided at a sleeping position on a mattress to obtain body pressure data in different sleeping postures, and the sleeping posture recognition model is used for performing sleeping posture recognition on the basis of the two-dimensional body pressure array obtained in real time, thereby improving the accuracy of sleeping posture recognition, and solving the problem in the prior art that using a camera to recognize the sleeping posture of a user at night is unlikely to be implemented and invades the privacy of the user.