Auditory Perceptual Systems for Hearing Threshold Calibration
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Solution Overview
Problem
Current hearing aids and audiometric methods fail to address the neural changes caused by hearing loss, leading to limited success in speech perception, and existing audiometric devices are not user-friendly or accessible for individuals to operate independently, lacking personalized training and accurate sound calibration.
Innovation Solution
A new audiometric assessment method and training system that uses game-based tone recognition and auditory perceptual training, allowing individuals to identify hearing thresholds and adjust sound processing parameters for personalized hearing aid or cochlear implant calibration, focusing on regions of hearing impairment and using interoaudioceptive calibration to normalize cortical responses.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If traditional audiometric methods are used, then hearing thresholds can be measured, but the methods require trained audiologists and are not accessible to laypersons
Solution Approach 1:
The system enables individuals to perform their own audiometric assessments and auditory training without requiring a trained audiologist. The automated platform guides users through hearing threshold measurements and personalized training exercises, making the service self-sufficient and accessible to laypersons while maintaining measurement quality.
Solution Approach 2:
The patent replaces the mechanical system of manual audiometric testing by trained professionals with an automated computer-based system. The platform uses software algorithms to conduct hearing threshold measurements, present auditory stimuli, and deliver training exercises, substituting human expertise with automated computational processes.
2Measurement precision
If hearing aids amplify sound, then hearing thresholds are improved, but the devices do not correct pathological neural function in the cortex
Solution Approach 1:
The system performs preliminary assessment of an individual's hearing thresholds and cortical processing deficiencies before delivering training. By first measuring hearing thresholds across different frequencies and identifying specific neural processing weaknesses, the platform can then tailor training exercises to address these pre-identified deficits, improving both hearing threshold detection and neural processing reliability.
Solution Approach 2:
The platform incorporates continuous feedback mechanisms where users' responses to auditory stimuli are monitored and used to adjust training parameters. This feedback loop allows the system to adapt training intensity, frequency, and type based on real-time performance, thereby correcting pathological neural function while maintaining accurate hearing threshold measurement.
3Reliability
If auditory perceptual training is provided, then speech perception improves, but the training is not tailored to individual hearing needs
Solution Approach 1:
The system applies local quality by customizing auditory training to address specific frequency ranges and processing deficits unique to each user. Based on individual hearing threshold assessments, the platform delivers targeted training exercises that focus on the particular frequencies and auditory discriminations most relevant to that user's hearing loss pattern, rather than applying generic training to all users.
Solution Approach 2:
The training program is dynamic and adapts continuously based on user performance. The system adjusts training parameters such as stimulus intensity, frequency, duration, and complexity in real-time according to the user's improving abilities, ensuring the training remains optimized for each individual's evolving hearing capabilities throughout the training process.
4Measurement precision
If sound output is increased for audiometry, then hearing thresholds are detected, but harmonic distortion and noise interfere with accuracy
Solution Approach 1:
The system uses an intermediary approach by presenting auditory stimuli through a computer-based platform that can precisely control sound output levels and characteristics. This intermediary system allows for accurate hearing threshold detection without the harmful effects of excessive sound intensity, as the automated platform can deliver stimuli at optimal levels and filter out distortion and noise that would occur with traditional high-intensity audiometric equipment.
Data Source
AI summary
A new hearing profile assessment plays each of a plurality of frequency tones multiple times at a plurality of loudness levels. For each frequency, the patient indicates which tones that they can hear, establishing minimum-amplitude thresholds for each frequency. The assessment adapts loudness levels until the patient indicates consistent minimum-amplitude thresholds for each frequency. Also, a new system for training the hearing of a subject is disclosed. The system instructs the subject to vocalize various sound items and remember the sounds that they vocalize. The system plays either recorded samples of the subject's own voice, or comparison samples of a synthesized voice or other's vocalizations of the same sound items. The system prompts the subject to compare the played samples with the sounds they remembered vocalizing. The system uses the feedback to adjust sound processing parameters for a hearing aid, cochlear implant, sound output devices, or a training program.