On-Ear Detection Using Microphone Resonance Frequency
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Existing headset technologies face challenges in accurately determining whether a headset is being worn, as previous methods using sensors or audio signal analysis can be affected by noise and hardware costs, and lack efficiency in distinguishing between on-ear and off-ear states.
Innovation Solution
The method involves analyzing resonance frequencies from internal and external microphones to determine if a headset is on-ear, using temperature-dependent microphone characteristics, and applying filtering and derivative analysis to differentiate between temperature changes and insertion/removal events, potentially using a neural network for prediction.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If sensors (capacitive, optical or infrared) are used to detect on ear condition, then detection accuracy is improved, but hardware cost and power consumption increase
Solution Approach 1:
The patent replaces physical sensors (capacitive, optical, or infrared) with an acoustic-based detection system using existing microphones. The system analyzes audio signals to detect resonance frequency changes that occur when the headset is placed on the ear, thereby substituting mechanical/sensor-based detection with acoustic signal processing using components already present in the headset.
Solution Approach 2:
The patent makes the existing microphones serve dual purposes: their primary function for audio capture and their secondary function for on-ear detection. By analyzing resonance frequency changes in the audio signals already being captured by the microphones, the system eliminates the need for dedicated detection sensors, reducing both hardware cost and power consumption while maintaining detection accuracy.
2Device complexity
If audio signals are analyzed to detect on ear condition, then hardware cost is reduced, but false positives increase due to noise sources such as wind noise
Solution Approach 1:
The patent changes the detection parameter from general audio signal analysis to specific resonance frequency analysis. By identifying and monitoring the resonance frequency of the ear canal (typically in the range of 2-5 kHz) and detecting its characteristic changes when the headset is inserted, the system distinguishes between actual on-ear conditions and noise sources like wind, thereby improving detection reliability while maintaining low hardware complexity.
Solution Approach 2:
The system continuously monitors resonance frequency changes and uses this feedback to adjust detection decisions. By analyzing the temporal pattern and magnitude of resonance frequency variations, the system can distinguish between transient noise events and genuine insertion/removal events, reducing false positives while maintaining simple hardware architecture.
3Measurement precision
If resonance frequency analysis is used for on ear detection, then detection accuracy is improved, but processing complexity increases
Solution Approach 1:
The patent applies partial action by focusing signal processing efforts only on the specific frequency range where ear canal resonance occurs (2-5 kHz), rather than analyzing the entire audio spectrum. This selective approach maintains high detection accuracy by concentrating computational resources on the most informative frequency band while reducing overall processing complexity.
Solution Approach 2:
The system performs preliminary action by pre-processing the audio signal to isolate the resonance frequency band before detailed analysis. By applying bandpass filtering and other preprocessing techniques to extract the relevant frequency components early in the signal chain, the system simplifies subsequent detection algorithms and reduces the computational burden of resonance frequency analysis.
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
This approach allows for accurate and efficient on-ear detection without adding hardware costs, reducing false positives and improving power consumption by leveraging temperature-dependent resonance frequencies and noise-robust derivatives.
Implementation Method 1
determining, from the first microphone signal, a first resonance frequency associated with an acoustic port of the first microphone, the first resonance frequency dependent on a first temperature at the first microphone
Data Source
AI summary
A method for on ear detection for a headphone, the method comprising: receiving a first microphone signal derived from a first microphone of the headphone and determining, from the first microphone signal, a first resonance frequency associated with an acoustic port of the first microphone, the first resonance frequency dependent on a first temperature at the first microphone; receiving a second microphone signal derived from a second microphone of the headphone and determining, from the second microphone signal, a second resonance frequency associated with an acoustic port of the second microphone, the second resonance frequency dependent on a second temperature at the second microphone.