Hearing Device Walking Detection Parameter Optimization
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Solution Overview
Problem
Conventional walking detection algorithms in hearing devices struggle to accurately detect various types of walking activities, particularly slow and irregular walking patterns exhibited by elderly and disabled users due to processing constraints.
Innovation Solution
A hearing device with a processor that optimizes parameters for a walking detection algorithm by detecting cadence attributes, adjusting the cadence range and amplitude threshold, and applying these optimized parameters to accelerometer data to determine the walking state of the user, allowing for more accurate and personalized walking state detection.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If a conventional walking detection algorithm is executed by a hearing device, then processing constraints are maintained, but detection accuracy for slow and irregular walking activities deteriorates
Solution Approach 1:
The system performs preliminary actions by collecting accelerometer data over a training period and determining user-specific cadence attributes before optimization. This preliminary data collection and analysis enables the subsequent optimization of walking detection parameters tailored to individual user characteristics, thereby improving detection accuracy without requiring complex real-time processing.
Solution Approach 2:
The system changes parameters by optimizing walking detection parameters (such as cadence range and amplitude threshold) based on determined cadence attributes. This parameter optimization adapts the detection algorithm to individual user walking patterns, enabling accurate detection of slow and irregular walking activities while maintaining computational efficiency through targeted parameter adjustment rather than complex algorithmic changes.
2Reliability
If a basic walking detection algorithm is used, then processing constraints are satisfied, but detection reliability for diverse walking styles deteriorates
Solution Approach 1:
The system implements feedback by determining cadence attributes from collected accelerometer data and using this information to optimize walking detection parameters. This feedback loop creates user-specific optimized parameters that improve detection reliability for diverse walking styles while maintaining processing efficiency, as the optimization occurs through parameter adjustment rather than computationally intensive algorithm changes.
3Measurement precision
If user-specific parameter optimization is implemented, then detection accuracy for individual walking patterns improves, but processing time and computational resources increase
Solution Approach 1:
The system performs preliminary parameter optimization during a training period when the user is actively engaged in walking activities. By collecting data and determining cadence attributes during this preliminary phase, the system establishes user-specific optimized parameters before normal operation begins. This preliminary action ensures that personalized detection accuracy is achieved without imposing ongoing computational burdens or time losses during actual walking detection.
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
The optimized walking detection algorithm enhances the accuracy and efficiency of detecting walking states, enabling the hearing device to effectively adjust settings and operations based on the user's walking activity, improving detection reliability for diverse walking styles.
Implementation Method 1
an accelerometer configured to output accelerometer data representative of an acceleration of the hearing device
Data Source
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AI summary
An exemplary hearing device configured to be worn by a user includes an accelerometer (108) configured to output accelerometer data (204) representative of an acceleration of the hearing device and a processor (102) configured to maintain data representative of a walking detection algorithm (202), determine an optimized parameter (404) for the user for use with the walking detection algorithm (202), and apply, in accordance with the optimized parameter (404), the walking detection algorithm (202) to the accelerometer data (204) to determine a walking state of the user while the user wears the hearing device.