Throat Microphone Interference Cancellation via Physiological Filtering
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Solution Overview
Problem
In noisy environments, throat microphones face challenges in distinguishing human speech from background noise and other vibrations, as they do not directly sense audible noise signals, leading to interference from secondary physiological phenomena like breathing and heartbeat.
Innovation Solution
A method and system that utilize a processor to receive vibration signals from a throat microphone, identify characteristics associated with secondary physiological phenomena, determine filter control parameters, and apply filtering to isolate the desired sonic signal, such as speech, by using a filter bank and high-pass filters to remove unwanted frequencies.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Object-affected harmful factors
If a throat microphone is used to sense vibrations, then audible noise signals are excluded, but secondary physiological phenomena (breathing, heartbeat) create interference
Solution Approach 1:
The patent extracts and removes the harmful secondary physiological phenomena (breathing, heartbeat) from the vibration signal using digital filtering techniques. The system identifies frequency components associated with these phenomena and selectively removes them while preserving the desired speech signal.
Solution Approach 2:
The patent changes the frequency domain parameters of the vibration signal by applying Fast Fourier Transform (FFT) to convert the time-domain signal to frequency-domain representation. This allows selective manipulation of frequency components to eliminate physiological interference.
2Measurement precision
If filtering is applied to remove secondary physiological phenomena, then speech clarity is improved, but signal processing complexity increases
Solution Approach 1:
The patent implements an adaptive filtering approach where the system continuously analyzes the vibration signal to identify characteristics of secondary physiological phenomena and dynamically adjusts filter parameters accordingly. This feedback mechanism optimizes speech clarity while managing processing complexity through intelligent adaptation.
Solution Approach 2:
The patent performs preliminary analysis of the vibration signal to identify frequency characteristics of physiological phenomena before applying the filtering operation. This pre-processing step allows the system to configure optimal filter parameters in advance, reducing the computational burden during the actual filtering process.
Data Source
AI summary
A throat microphone may include one or more transducers that are in contact with the skin in the region of the larynx of person, and may provide a vibration signal to a processing unit. The vibration signal may also include energy and information relating to secondary physiological phenomena such as breathing and heartbeat, in addition to the desired sonic signal. The processing unit may utilize information relating to the secondary physiological phenomena to control a filter that outputs the desired sonic signal.