Surface Acoustic Wave Gesture Sensing With Contact Microphones
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Solution Overview
Problem
Existing methods for capturing precise user touch and interaction events require heavy instrumentation of the environment or user, or suffer from limitations in depth resolution, leading to false detection of touch events and poor user interfaces.
Innovation Solution
A system utilizing a contact microphone and signal processor to detect surface acoustic waves (SAWs) traveling along a surface, extracting features using Mel-frequency cepstral coefficients and classifying them with machine learning to identify gestures.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If heavy instrumentation is used to detect precise touch events, then measurement precision is improved, but device complexity increases
Solution Approach 1:
The patent replaces complex optical tracking systems and specialized sensors with a contact microphone that detects surface acoustic waves. This mechanical/acoustic substitution simplifies the instrumentation while maintaining the ability to detect precise touch events and gestures on surfaces.
Solution Approach 2:
The system uses the surface itself as the sensing medium by detecting surface acoustic waves that naturally propagate when touched. The surface serves its dual purpose of being both the interaction surface and the sensing element, eliminating the need for separate specialized sensors or instrumentation.
2Ease of operation
If depth cameras are used to track hand position, then ease of operation is improved, but measurement precision deteriorates due to limited depth resolution
Solution Approach 1:
The patent replaces optical depth sensing systems with acoustic wave detection. The contact microphone detects surface acoustic waves that provide precise information about touch events, substituting the mechanical/optical depth measurement system with an acoustic sensing approach that achieves superior depth resolution for gesture detection.
3Measurement precision
If surface acoustic wave detection is implemented, then measurement precision is improved for gesture detection, but device complexity increases due to signal processing requirements
Solution Approach 1:
The patent transforms the surface acoustic wave signals into a different parameter domain using Mel-frequency cepstral coefficients (MFCCs). This parameter transformation converts complex time-domain acoustic signals into frequency-domain features that are more suitable for gesture classification, simplifying the subsequent processing while maintaining high detection precision.
Solution Approach 2:
The patent replaces complex multi-sensor instrumentation systems with a single contact microphone that detects surface acoustic waves. This substitution reduces device complexity by consolidating multiple sensing functions into one acoustic sensor, while the signal processing complexity is managed through standard audio processing techniques.
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 system effectively distinguishes between various hand gestures with high accuracy, even in noisy environments and across different materials, providing a robust and natural interaction interface without extensive instrumentation.
Implementation Method 1
The contact microphone is attached to a surface of interest of an object and is configured to measure surface acoustic waves traveling along the surface of interest
Data Source
AI summary
A system is presented for detecting gestures. The system is comprised of: a contact microphone and a signal processor. The contact microphone is attached to a surface of interest of an objection and is configured to measure surface acoustic waves traveling along the surface of interest. The signal processor is interfaced with the contact microphone and is configured to receive a signal from the contact microphone, where the signal is indicative of surface acoustic waves traveling along the surface of interest. The signal processor operates to identify a gesture made by a person on the surface of interest using the signal.