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Development of a personalized tinnitus detection and treatment instrument
Journal of Tsinghua University (Science and Technology) 2023, 63(12): 2076-2084
Published: 15 December 2023
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Objective

The treatment of subjective tinnitus is a global problem in hearing clinics. Currently, the technical defects and bottlenecks of tinnitus detection and treatment in hearing clinics include the lack of portable tinnitus detection and treatment equipment that integrates personalized and accurate detection with targeted rehabilitation, lack of precise treatment plans using pleasant music in the background to eliminate patients' discomfort and rejection to secondary hearing damage caused by clinical white noise masking therapy, and lack of effective treatment options for high-frequency tinnitus. This study pioneers the development of a personalized tinnitus detection and treatment instrument.

Methods

In this study, the STM32 embedded single-chip microcomputer is used as the core module to run the software, execute device control and algorithms, control and operate different functional modules, and provide audio decoding conversion module, power conversion module, earphones, and charging interfaces. The audio-decoding chip is designed to realize high-quality stereo multimedia digital signal processing. Staticrandom access memory (SRAM) provides the external memory for the microcontroller unit (MCU). The flash chip stores audio, text, and data. The SD card stores audio files and fonts required by tinnitus detection and treatment equipment, user information, and other large-capacity information. The sound output of this detection and treatment device is transmitted to the patient through the transducer (earphone), and the patient enables human-computer interactions with the device through buttons and screen, all of which form the operation adjustment of tinnitus detection and treatment. Batteries provide power to the whole device. The software adopts object-oriented programming and realizes functions by designing top-level, middle-level, and bottom-level functions. Top-level functions refer to the graphical user interface (GUI) part that targets user programs and functions related to user control. Middle-level functions include each specific page, functions inside the page, and the function of each button operation. Bottom-level functions target the hardware to control and configure peripheral register functions such as memory, screen, audio decoding, keys, SD card, LED, and others.

Results

The proposed tinnitus detection and treatment instrument enabled personalized and precise detection of tinnitus and targeted rehabilitation treatment. Its features included tinnitus ear selection, tinnitus detection, tinnitus treatment, data storage of prescriptions, equipment calibration, and information saving and scanning. It pioneered several comprehensive notching and masking personalized sound treatment solutions and resolved technical defects and bottlenecks of current clinical tinnitus detection and treatment equipment. The treatment results of the first four participants who finished the 8-week treatment using this therapeutic instrument showed a therapeutic effectiveness close to 100%. The tinnitus handicap inventory (THI) score and tinnitus loudness of patients with tinnitus showed a significant downward trend. Significant therapeutic effectiveness was observed among patients with high-frequency tinnitus. Obvious changes to the mismatch negativity occurred in patients with significantly lower THI scores and lower tinnitus loudness.

Conclusions

The proposed portable instrument, not only provides a portable treatment method integrating tinnitus detection and treatment for clinics, its personalized and accurate detection and targeted rehabilitation treatment functions, but also have laid the application foundation for the quantitative and objective diagnoses and treatment standards and prescription establishment.

Issue
Small-Space Microphone Array Fractional Delay Algorithm Based on FIR Filter for Cochlear Implant
Tsinghua Science and Technology 2011, 16(1): 90-94
Published: 01 February 2011
Abstract PDF (446.2 KB) Collect
Downloads:3

Directional speech enhancement of signals from microphone arrays is an effective way to improve speech recognition for cochlear implant users. The strict implant size limitation results in a short distance between microphones. The fractional delay problem due to the short distance between microphones is solved by a maximal flat (Maxflat) finite impulse response (FIR) filter, using the Maxflat error criteria at a low frequency containing most of the speech information and energy. The fractional Maxflat FIR filter approximates the ideal digital fractional filter at the magnitude response, phase response, and phase delay characteristics, and is also very low order. The results demonstrate that the Maxflat FIR filter accurately and effectively solves the fractional digital delay and is very suitable for real-time speech processing in practical cochlear implant products.

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