Perceptive Model Hearing Aid Adaptation Workflow
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Solution Overview
Problem
The existing workflow for providing individually adapted hearing aids is labor-intensive and time-consuming, requiring frequent visits to ENT specialists and acousticians, leading to long waiting times for patients due to poor patient management and repetitive feedback between manufacturers and acousticians.
Innovation Solution
A method that involves generating hearing loss data, such as audiograms, by a skilled professional and sending them to a manufacturer who uses a perceptive model to select and adapt the hearing aid type, allowing for direct delivery to the patient, potentially reducing the need for multiple visits by simplifying the adaptation process.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of time
If the traditional workflow with frequent visits to ENT specialists and acousticians is used, then individual adaptation of hearing aids is achieved, but waiting time and process complexity increase significantly
Solution Approach 1:
The system enables self-service by allowing the hearing aid adaptation process to be performed automatically by the manufacturer using the perceptive model, without requiring the patient to make multiple visits to specialists. The automated system processes hearing loss data and configures hearing aid parameters independently, reducing both waiting time and workflow complexity.
Solution Approach 2:
The perceptive model performs preliminary analysis of hearing loss data to predict optimal hearing aid settings before the hearing aid is even delivered to the patient. This preliminary configuration is done in advance by the manufacturer, eliminating the need for multiple adjustment visits and significantly reducing the overall adaptation time.
2Productivity
If manual adaptation processes are used, then individualized hearing aid settings are achieved, but labor intensity and adaptation time increase
Solution Approach 1:
The manual mechanical process of hearing aid adaptation by specialists is replaced with an automated computational system based on the perceptive model. The system automatically processes hearing loss data and generates adaptation parameters, substituting human labor with an algorithmic approach that increases productivity while maintaining simplicity for the end user.
Solution Approach 2:
The perceptive model acts as an intermediary between the hearing loss data and the hearing aid configuration. It automatically translates hearing loss measurements into optimal hearing aid settings, eliminating the need for manual intervention by specialists and significantly improving adaptation efficiency.
3Reliability
If repetitive feedback between manufacturers and acousticians is required, then optimal hearing aid settings are achieved, but process duration increases
Solution Approach 1:
The perceptive model incorporates feedback mechanisms that automatically adjust hearing aid parameters based on predicted patient response. The system uses hearing loss data to generate initial settings and refines them through automated feedback loops, achieving reliable adaptation results in a single process run without requiring multiple iterative visits between manufacturers and acousticians.
Data Source
AI summary
The provision of an individually adapted hearing aid for a patient is intended to be effected more quickly. A method is therefore provided by which, firstly, hearing loss data, in particular an audiogram, are generated by a person skilled in the art for example an ENT specialist, and the hearing loss data are transmitted to a manufacturer. Using a perceptive model based on the hearing loss data, the manufacturer selects a hearing aid and matches the hearing aid to the patient by means of the perceptive model. Finally, the manufacturer delivers the adapted hearing aid directly or indirectly to the patient. Due to the simplified workflow during the adaptation, the waiting times for the provision of the hearing aid are reduced for the patient.