Touch Input Sensing via Time-Frequency Signal Analysis
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Existing touch input sensing technologies for mobile devices struggle to accurately discriminate between different types and intensities of user inputs, primarily relying on vibration volume and peak frequency, which limits their ability to understand various user interactions.
Innovation Solution
A method and device that digitally process sound/vibration signals using properties in both time and frequency domains, such as maximum amplitude, spectral centroid, and cepstral coefficients, to determine the type and intensity of touch inputs, enabling precise discrimination of touch means and inputs.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If vibration sensors are used to sense touch inputs based on volume and peak frequency, then touch actions can be discriminated, but the precision of touch type and intensity discrimination is insufficient
Solution Approach 1:
The patent transitions from analyzing vibration signals in the time domain (volume, peak frequency) to analyzing them in the frequency domain using spectrogram technology. This dimensional change allows extraction of multiple frequency components and their temporal evolution, significantly improving touch input discrimination precision without requiring additional hardware sensors.
Solution Approach 2:
The patent pre-calculates and stores reference spectrogram patterns for different touch types (finger touch, stylus touch, palm rejection) and intensity levels. During actual touch detection, the system compares real-time spectrograms against these pre-established references, enabling rapid and accurate classification without complex real-time computation.
2Adaptability or versatility
If simple vibration-based touch sensing is used, then device complexity is reduced, but the ability to understand various user inputs is limited
Solution Approach 1:
The patent segments the vibration signal analysis into multiple frequency bands using spectrogram decomposition. Each frequency band provides specific information about touch characteristics - low frequencies indicate palm touches, mid frequencies indicate finger touches, and high frequencies indicate stylus touches. This segmentation enables the system to understand various user inputs with a single sensor.
Solution Approach 2:
The patent extracts multiple parameters from the spectrogram including spectral centroid, spectral bandwidth, spectral rolloff, and zero-crossing rate. By monitoring changes in these parameters over time, the system can distinguish between different touch types and intensities, greatly enhancing user input understanding capability.
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
Enables the precise sensing and discrimination of various user inputs, allowing user interfaces to understand and respond to different touch types and intensities, enhancing the usability of mobile devices.
Implementation Method 1
uses a vibration sensor to sense that a part on or outside a touch panel of a device is touched by an object
Implementation Method 2
sense the sound or vibration generated by user touch inputs
Data Source
AI summary
A method for sensing touch inputs to a digital equipment is provided, comprising the steps of sensing a sound/vibration signal generated by a touch, digitally processing the sensed sound/vibration signal, and determining the type of touch means that has generated the touch and the intensity of the touch based on the properties of the processed sound/vibration signal, wherein the properties include at least one of the following properties of the sound/vibration signal in time domain: maximum amplitude, average amplitude, average frequency, mean, standard deviation, standard deviation normalized by overall amplitude, variance, skewness, kurtosis, sum, absolute sum, root mean square (RMS), crest factor, dispersion, entropy, power sum, center of mass, coefficients of variation, cross correlation, zero-crossings, seasonality, DC bias, or the above properties computed for the first, second, third or higher order of derivatives of the sound/vibration signal; and the following properties of the sound/vibration signal in frequency domain: spectral centroid, spectral density, spherical harmonics, total average spectral energy, band energy ratios for every octave, log spectral band ratios, linear prediction-based cepstral coefficients (LPCCs), perceptual linear prediction (PLP) cepstral coefficients, mel-frequency cepstral coefficients, frequency topology, or the above properties computed for the first, second, third or higher order of derivatives of a frequency domain representation of the sound/vibration signal. There is also provided a device for sensing touch inputs.