scholarly journals A Comparison of Environment Classification Among Premium Hearing Instruments

2021 ◽  
Vol 25 ◽  
pp. 233121652098096
Author(s):  
Anusha Yellamsetty ◽  
Erol J. Ozmeral ◽  
Robert A. Budinsky ◽  
David A. Eddins
Keyword(s):  
Signal Processing ◽  
Hearing Aids ◽  
Signal To Noise Ratio ◽  
Human Subjects ◽  
Signal To Noise ◽  
Environmental Classification ◽  
Hearing Instruments ◽  
Wide Range ◽  
Noise Ratio ◽  
Acoustic Environments

Hearing aids classify acoustic environments into multiple, generic classes for the purposes of guiding signal processing. Information about environmental classification is made available to the clinician for fitting, counseling, and troubleshooting purposes. The goal of this study was to better inform scientists and clinicians about the nature of that information by comparing the classification schemes among five premium hearing instruments in a wide range of acoustic scenes including those that vary in signal-to-noise ratio and overall level (dB SPL). Twenty-eight acoustic scenes representing various prototypical environments were presented to five premium devices mounted on an acoustic manikin. Classification measures were recorded from the brand-specific fitting software then recategorized to generic labels to conceal the device company, including (a) Speech in Quiet, (b) Speech in Noise, (c) Noise, and (d) Music. Twelve normal-hearing listeners also classified each scene. The results revealed a variety of similarities and differences among the five devices and the human subjects. Where some devices were highly dependent on input overall level, others were influenced markedly by signal-to-noise ratio. Differences between human and hearing aid classification were evident for several speech and music scenes. Environmental classification is the heart of the signal processing strategy for any given device, providing key input to subsequent decision-making. Comprehensive assessment of environmental classification is essential when considering the cost of signal processing errors, the potential impact for typical wearers, and the information that is available for use by clinicians. The magnitude of differences among devices is remarkable and to be noted.

scholarly journals CMUT-Based Sensor for Acoustic Emission Application: Experimental and Theoretical Contributions to Sensitivity Optimization

Sensors ◽  
2021 ◽  
Vol 21 (6) ◽  
pp. 2042
Author(s):  
Redha Boubenia ◽  
Patrice Le Moal ◽  
Gilles Bourbon ◽  
Emmanuel Ramasso ◽  
Eric Joseph
Keyword(s):  
Signal Processing ◽  
Signal To Noise Ratio ◽  
Ultrasonic Transducer ◽  
Operating Conditions ◽  
Geometrical Parameters ◽  
Signal To Noise ◽  
Coupling Conditions ◽  
Sensor Structure ◽  
Noise Ratio ◽  
Electrical Connections

The paper deals with a capacitive micromachined ultrasonic transducer (CMUT)-based sensor dedicated to the detection of acoustic emissions from damaged structures. This work aims to explore different ways to improve the signal-to-noise ratio and the sensitivity of such sensors focusing on the design and packaging of the sensor, electrical connections, signal processing, coupling conditions, design of the elementary cells and operating conditions. In the first part, the CMUT-R100 sensor prototype is presented and electromechanically characterized. It is mainly composed of a CMUT-chip manufactured using the MUMPS process, including 40 circular 100 µm radius cells and covering a frequency band from 310 kHz to 420 kHz, and work on the packaging, electrical connections and signal processing allowed the signal-to-noise ratio to be increased from 17 dB to 37 dB. In the second part, the sensitivity of the sensor is studied by considering two contributions: the acoustic-mechanical one is dependent on the coupling conditions of the layered sensor structure and the mechanical-electrical one is dependent on the conversion of the mechanical vibration to electrical charges. The acoustic-mechanical sensitivity is experimentally and numerically addressed highlighting the care to be taken in implementation of the silicon chip in the brass housing. Insertion losses of about 50% are experimentally observed on an acoustic test between unpackaged and packaged silicon chip configurations. The mechanical-electrical sensitivity is analytically described leading to a closed-form amplitude of the detected signal under dynamic excitation. Thus, the influence of geometrical parameters, material properties and operating conditions on sensitivity enhancement is clearly established: such as smaller electrostatic air gap, and larger thickness, Young’s modulus and DC bias voltage.

scholarly journals Evaluation of an Adaptive Dynamic Compensation System in Cochlear Implant Listeners

2020 ◽  
Vol 24 ◽  
pp. 233121652097034
Author(s):  
Florian Langner ◽  
Andreas Büchner ◽  
Waldo Nogueira
Keyword(s):  
Signal Processing ◽  
Cochlear Implant ◽  
Speech Intelligibility ◽  
Discrimination Task ◽  
Signal To Noise Ratio ◽  
Compensation System ◽  
Signal To Noise ◽  
Dynamic Compensation ◽  
Front End ◽  
Noise Ratio

Cochlear implant (CI) sound processing typically uses a front-end automatic gain control (AGC), reducing the acoustic dynamic range (DR) to control the output level and protect the signal processing against large amplitude changes. It can also introduce distortions into the signal and does not allow a direct mapping between acoustic input and electric output. For speech in noise, a reduction in DR can result in lower speech intelligibility due to compressed modulations of speech. This study proposes to implement a CI signal processing scheme consisting of a full acoustic DR with adaptive properties to improve the signal-to-noise ratio and overall speech intelligibility. Measurements based on the Short-Time Objective Intelligibility measure and an electrodogram analysis, as well as behavioral tests in up to 10 CI users, were used to compare performance with a single-channel, dual-loop, front-end AGC and with an adaptive back-end multiband dynamic compensation system (Voice Guard [VG]). Speech intelligibility in quiet and at a +10 dB signal-to-noise ratio was assessed with the Hochmair–Schulz–Moser sentence test. A logatome discrimination task with different consonants was performed in quiet. Speech intelligibility was significantly higher in quiet for VG than for AGC, but intelligibility was similar in noise. Participants obtained significantly better scores with VG than AGC in the logatome discrimination task. The objective measurements predicted significantly better performance estimates for VG. Overall, a dynamic compensation system can outperform a single-stage compression (AGC + linear compression) for speech perception in quiet.

Effect of signal to noise ratio on a convolutional neural network for source ranging and environmental classification

2019 ◽  
Vol 146 (4) ◽  
pp. 2961-2962
Author(s):  
Kira Howarth ◽  
David F. Van Komen ◽  
Tracianne B. Neilsen ◽  
David P. Knobles ◽  
Peter H. Dahl ◽  
...  
Keyword(s):  
Neural Network ◽  
Convolutional Neural Network ◽  
Signal To Noise Ratio ◽  
Signal To Noise ◽  
Environmental Classification ◽  
Noise Ratio

Dual-Tree Wavelet Packet Transform for Ultrasonic Data Transmission Through Metal Structures

2015 ◽  
Author(s):  
Jinjiang Wang ◽  
Robert X. Gao ◽  
Xinyao Tang ◽  
Zhaoyan Fan ◽  
Peng Wang
Keyword(s):  
Signal Processing ◽  
Data Transmission ◽  
Signal To Noise Ratio ◽  
Wavelet Packet ◽  
Experimental Studies ◽  
Wavelet Packet Transform ◽  
Signal To Noise ◽  
Metallic Structures ◽  
Time Frequency ◽  
Noise Ratio

Data communication through metallic structures is generally encountered in manufacturing equipment and process monitoring and control. This paper presents a signal processing technique for enhancing the signal-to-noise ratio and high-bit data transmission rate in ultrasound-based wireless data transmission through metallic structures. A multi-carrier coded-ultrasonic wave modulation scheme is firstly investigated to achieve high-bit data rate communication while reducing inter-symbol inference and data loss, due to the inherent signal attenuation, wave diffraction and reflection in metallic structures. To improve the signal-to-noise ratio, dual-tree wavelet packet transform (DT-WPT) has been investigated to separate multi-carrier signals under noise contamination, given its properties of shift-invariance and flexible time frequency partitioning. A new envelope extraction and threshold setting strategy for selected wavelet coefficients is then introduced to retrieve the coded digital information. Experimental studies are performed to evaluate the effectiveness of the developed signal processing method for manufacturing.

Multi-Wavelet Application Based on Engineering Building Deformation Monitoring

2013 ◽  
Vol 353-356 ◽  
pp. 3420-3423
Author(s):  
Yong Hong He ◽  
Peng Wei Jin
Keyword(s):  
Signal Processing ◽  
Signal To Noise Ratio ◽  
Small Deformation ◽  
Deformation Monitoring ◽  
Biorthogonal Wavelet ◽  
Signal To Noise ◽  
Actual Problem ◽  
Wavelet Method ◽  
Noise Ratio

In order to separate effectively small deformation from GPS signal containing the error, Based on multiwavelet theory, the paper makes DGHM for GPS deformation monitoring signal processing, because the DGHM biorthogonal wavelet is with short support, orthogonality, symmetry ( antisymmetry ) and two approximation and other characteristics, in the same length of filtering, multi-wavelet method is more superior than traditional wavelet method, improves the signal to noise ratio, obtains higher accuracy, confirms correct and practical in the actual problem, the algorithm has opened a new way for deformation monitoring signal processing

Sign in / Sign up

Export Citation Format

Share Document