Smart Cushion Body Part Recognition Using Vibration Sensor Array
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Solution Overview
Problem
Existing smart cushion technologies face limitations in accurately recognizing body parts due to reliance on static pressure sensors and experience-based methods, leading to poor recognition accuracy and robustness, especially when the human body is not in a straight position.
Innovation Solution
A body part recognition method using a two-dimensional sensor array with vibration sensors to collect and analyze short-term vibration energy characteristics, employing dynamic programming or greedy algorithms to determine the position of the buttocks and other body parts, ensuring accurate and flexible identification.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Device complexity
If static pressure sensors are used to detect body parts, then the device complexity is reduced, but the measurement precision and recognition accuracy deteriorate
Solution Approach 1:
The patent replaces static pressure sensors (mechanical detection) with vibration sensors that detect dynamic vibration signals caused by breathing and heartbeat. This substitution enables more accurate body part identification through dynamic characteristics while maintaining reasonable device complexity.
Solution Approach 2:
The patent transitions from static pressure detection to dynamic vibration detection. By analyzing vibration signals that change with breathing and heartbeat, the system achieves superior recognition accuracy compared to static methods, particularly for distinguishing body parts in various positions.
2Device complexity
If experience-based methods are used to identify body parts based on pressure distribution, then the device complexity is reduced, but the reliability and robustness deteriorate
Solution Approach 1:
The patent replaces experience-based judgment methods with objective vibration signal analysis. By using algorithms to process vibration characteristics, the system achieves reliable and robust body part recognition that does not depend on subjective assumptions about body positioning.
Solution Approach 2:
The system uses the body's own physiological vibrations (breathing and heartbeat) as identification markers. This self-generated signal approach provides reliable recognition without requiring external assistance or complex preprocessing, enhancing both reliability and ease of use.
3Ease of operation
If the assumption that the human body lies straight is made for position determination, then the ease of operation is improved, but the adaptability deteriorates
Solution Approach 1:
The patent uses dynamic vibration characteristics that remain identifiable regardless of body position. The vibration signals from breathing and heartbeat provide unique patterns that can be recognized even when the body is not in a straight position, significantly improving adaptability while maintaining ease of operation.
Solution Approach 2:
The system changes from relying on spatial geometry (pressure distribution patterns that assume straight body position) to relying on temporal-dynamic parameters (vibration frequency and amplitude patterns). This parameter transformation enables the system to accurately identify body parts in various positions without complicating the operation.
4Measurement precision
If vibration sensors are used to collect dynamic vibration signals, then the measurement precision is improved, but the device complexity increases
Solution Approach 1:
The patent divides the detection task into segments: vibration sensors collect raw signals, signal processing modules extract vibration characteristics, and algorithms identify body parts. This segmentation allows the use of sophisticated detection methods while managing overall system complexity through modular design.
Solution Approach 2:
The patent introduces signal processing as an intermediary between the vibration sensors and body part identification. This intermediary layer processes raw vibration signals into meaningful characteristics, enabling accurate recognition while shielding the complexity of the algorithm from the hardware design.
5Measurement precision
If dynamic programming algorithms are used for body part recognition, then the measurement precision is improved, but the loss of time increases
Solution Approach 1:
The patent performs preliminary processing of vibration signals by extracting key characteristics (amplitude, frequency, time-domain features) before applying dynamic programming algorithms. This preliminary action reduces the complexity of the data fed into the algorithm, maintaining high recognition accuracy while reducing processing time.
Solution Approach 2:
The patent extracts essential vibration characteristics from raw signals, separating the critical identification features from redundant information. This extraction process reduces the computational burden on dynamic programming algorithms, achieving fast and accurate body part recognition simultaneously.
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
The method effectively identifies body parts with high accuracy, enabling precise recognition and flexible adaptation to different body positions, thereby enhancing the functionality of smart cushions.
Implementation Method 1
collecting a plurality of vibration signals by using a plurality of sensor units in a two-dimensional sensor array provided in a smart cushion
Data Source
AI summary
A body part recognition method and apparatus, a smart cushion, a device, and a medium. The method includes: collecting a plurality of vibration signals by using a plurality of sensor units in a two-dimensional sensor array provided in a smart cushion; obtaining statistics about short-term vibration energy characteristic of each of the sensor units on the basis of the vibration signal collected by the each sensor unit; determining a position of the each sensor unit having a highest short-term vibration energy characteristic as a position of the buttocks; and recognizing the positions of body parts other than the buttocks on the basis of the position of the buttocks using a dynamic programming algorithm or/and a greedy algorithm.