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Mastication noise reduction method for fully implantable hearing aid using piezo-electric sensor

Title
Mastication noise reduction method for fully implantable hearing aid using piezo-electric sensor
Authors
Na, Sung DaeLee, GihyounWei, QunSeong, Ki WoongCho, Jin HoKim, Myoung Nam
DGIST Authors
Lee, Gihyoun
Issue Date
2017
Citation
TECHNOLOGY AND HEALTH CARE, 25, S29-S34
Type
Article
Article Type
Article; Proceedings Paper
Keywords
DevicesFloating Mass TransducerImplantable Hearing DevicesMastication NoiseMiddle EarPiezo Electric Sensor
ISSN
0928-7329
Abstract
BACKGROUND: Fully implantable hearing devices (FIHDs) can be affected by generated biomechanical noise such as mastication noise. OBJECTIVE: To reduce the mastication noise using a piezo-electric sensor, the mastication noise is measured with the piezoelectric sensor, and noise reduction is practiced by the energy difference. METHODS: For the experiment on mastication noise, a skull model was designed using artificial skull model and a piezoelectric sensor that can measure the vibration signals better than other sensors. A 1 kHz pure-tone sound through a standard speaker was applied to the model while the lower jawbone of the model was moved in a masticatory fashion. RESULTS: The correlation coefficients and signal-to-noise ratio (SNR) before and after application of the proposed method were compared. It was found that the signal-to-noise ratio and correlation coefficients increased by 4.48 dB and 0.45, respectively. CONCLUSION: The mastication noise is measured by piezo-electric sensor as the mastication noise that occurred during vibration. In addition, the noise was reduced by using the proposed method in conjunction with MATLAB. In order to confirm the performance of the proposed method, the correlation coefficients and signal-to-noise ratio before and after signal processing were calculated. In the future, an implantable microphone for real-time processing will be developed.
URI
http://hdl.handle.net/20.500.11750/4449
DOI
10.3233/THC-171303
Publisher
IOS PRESS
Files:
There are no files associated with this item.
Collection:
Division of IoT∙Robotics Convergence Research1. Journal Articles


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