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Objectives: While cochlear implants (CIs) have provided benefits for speech recognition in quiet for subjects with severe-to-profound hearing loss, speech recognition in noise remains challenging. A body of evidence suggests that reducing frequency-to-place mismatch may positively affect speech perception. Thus, a fitting method based on a tonotopic map may improve speech perception results in quiet and noise. The aim of our study was to assess the impact of a tonotopic map on speech perception in noise and quiet in new CI users.
Design: A prospective, randomized, double-blind, two-period cross-over study in 26 new CI users was performed over a 6-month period. New CI users older than 18 years with bilateral severe-to-profound sensorineural hearing loss or complete hearing loss for less than 5 years were selected in the University Hospital Centre of Rennes in France. An anatomical tonotopic map was created using postoperative flat-panel computed tomography and a reconstruction software based on the Greenwood function. Each participant was randomized to receive a conventional map followed by a tonotopic map or vice versa. Each setting was maintained for 6 weeks, at the end of which participants performed speech perception tasks. The primary outcome measure was speech recognition in noise. Participants were allocated to sequences by block randomization of size two with a ratio 1:1 (CONSORT Guidelines). Participants and those assessing the outcomes were blinded to the intervention.
Results: Thirteen participants were randomized to each sequence. Two of the 26 participants recruited (one in each sequence) had to be excluded due to the COVID-19 pandemic. Twenty-four participants were analyzed. Speech recognition in noise was significantly better with the tonotopic fitting at all signal-to-noise ratio (SNR) levels tested [SNR = +9 dB, p = 0.002, mean effect (ME) = 12.1%, 95% confidence interval (95% CI) = 4.9 to 19.2, standardized effect size (SES) = 0.71; SNR = +6 dB, p < 0.001, ME = 16.3%, 95% CI = 9.8 to 22.7, SES = 1.07; SNR = +3 dB, p < 0.001 ME = 13.8%, 95% CI = 6.9 to 20.6, SES = 0.84; SNR = 0 dB, p = 0.003, ME = 10.8%, 95% CI = 4.1 to 17.6, SES = 0.68]. Neither period nor interaction effects were observed for any signal level. Speech recognition in quiet ( p = 0.66) and tonal audiometry ( p = 0.203) did not significantly differ between the two settings. 92% of the participants kept the tonotopy-based map after the study period. No correlation was found between speech-in-noise perception and age, duration of hearing deprivation, angular insertion depth, or position or width of the frequency filters allocated to the electrodes.
Conclusion: For new CI users, tonotopic fitting appears to be more efficient than the default frequency fitting because it allows for better speech recognition in noise without compromising understanding in quiet.
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http://dx.doi.org/10.1097/AUD.0000000000001423 | DOI Listing |
Int J Audiol
September 2025
Institute of Hearing Technology and Audiology, Jade University of Applied Sciences, Oldenburg, Germany.
Objective: Determination of monaural and binaural speech-recognition curves for the Freiburg monosyllabic speech test (FMST) in quiet to update and supplement existing normative data.
Design: Monaural and binaural speech-recognition tests were performed in free field at five speech levels in two anechoic test rooms at two sites (Lübeck and Oldenburg, Germany). For the monaural tests, one ear was occluded with a foam earplug.
Front Artif Intell
August 2025
School of Computation and Communication Science and Engineering, The Nelson Mandela African Institution of Science and Technology, Arusha, Tanzania.
Computer vision has been identified as one of the solutions to bridge communication barriers between speech-impaired populations and those without impairment as most people are unaware of the sign language used by speech-impaired individuals. Numerous studies have been conducted to address this challenge. However, recognizing word signs, which are usually dynamic and involve more than one frame per sign, remains a challenge.
View Article and Find Full Text PDFZhonghua Jie He He Hu Xi Za Zhi
September 2025
Department of Respiratory and Critical Care Medicine, the First Affiliated Hospital of Guangzhou Medical University, National Center for Respiratory Medicine, National Clinical Research Center for Respiratory Disease, State Key Laboratory of Respiratory Disease, Guangzhou Institute of Respiratory He
Cough is a common symptom of many respiratory diseases, and parameters such as frequency, intensity, type and duration play important roles in disease screening, diagnosis and prognosis. Among these, cough frequency is the most widely applied metric. In current clinical practice, cough severity is primarily assessed based on patients' subjective symptom descriptions in combination with semi-structured questionnaires.
View Article and Find Full Text PDFCogn Psychol
September 2025
Graduate School of Engineering, Kochi University of Technology, Kami, Kochi, Japan. Electronic address:
Prior researches on global-local processing have focused on hierarchical objects in the visual modality, while the real-world involves multisensory interactions. The present study investigated whether the simultaneous presentation of auditory stimuli influences the recognition of visually hierarchical objects. We added four types of auditory stimuli to the traditional visual hierarchical letters paradigm:no sound (visual-only), a pure tone, a spoken letter that was congruent with the required response (response-congruent), or a spoken letter that was incongruent with it (response-incongruent).
View Article and Find Full Text PDFNanomicro Lett
September 2025
Nanomaterials & System Lab, Major of Mechatronics Engineering, Faculty of Applied Energy System, Jeju National University, Jeju, 63243, Republic of Korea.
Wearable sensors integrated with deep learning techniques have the potential to revolutionize seamless human-machine interfaces for real-time health monitoring, clinical diagnosis, and robotic applications. Nevertheless, it remains a critical challenge to simultaneously achieve desirable mechanical and electrical performance along with biocompatibility, adhesion, self-healing, and environmental robustness with excellent sensing metrics. Herein, we report a multifunctional, anti-freezing, self-adhesive, and self-healable organogel pressure sensor composed of cobalt nanoparticle encapsulated nitrogen-doped carbon nanotubes (CoN CNT) embedded in a polyvinyl alcohol-gelatin (PVA/GLE) matrix.
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