Dataset Information

Vowel production of Mandarin-speaking hearing aid users with different types of hearing loss.

ABSTRACT: In contrast with previous research focusing on cochlear implants, this study examined the speech performance of hearing aid users with conductive (n = 11), mixed (n = 10), and sensorineural hearing loss (n = 7) and compared it with the speech of hearing control. Speech intelligibility was evaluated by computing the vowel space area defined by the Mandarin Chinese corner vowels /a, u, i/. The acoustic differences between the vowels were assessed using the Euclidean distance. The results revealed that both the conductive and mixed hearing loss groups exhibited a reduced vowel working space, but no significant difference was found between the sensorineural hearing loss and normal hearing groups. An analysis using the Euclidean distance further showed that the compression of vowel space area in conductive hearing loss can be attributed to the substantial lowering of the second formant of /i/. The differences in vowel production between groups are discussed in terms of the occlusion effect and the signal transmission media of various hearing devices.

SUBMITTER: Hung YC

PROVIDER: S-EPMC5456089 | biostudies-literature | 2017

REPOSITORIES: biostudies-literature

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Vowel production of Mandarin-speaking hearing aid users with different types of hearing loss.

Hung Yu-Chen YC Lee Ya-Jung YJ Tsai Li-Chiun LC

PloS one 20170602 6

In contrast with previous research focusing on cochlear implants, this study examined the speech performance of hearing aid users with conductive (n = 11), mixed (n = 10), and sensorineural hearing loss (n = 7) and compared it with the speech of hearing control. Speech intelligibility was evaluated by computing the vowel space area defined by the Mandarin Chinese corner vowels /a, u, i/. The acoustic differences between the vowels were assessed using the Euclidean distance. The results revealed ...[more]

PMID: 28575087

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Project description:Measurement of outcomes has become increasingly important to assess the benefit of audiologic rehabilitation, including hearing aids, in adults. Data from questionnaires, however, are based on retrospective recall of events and experiences, and often can be inaccurate. Questionnaires also do not capture the daily variation that typically occurs in relevant events and experiences. Clinical researchers in a variety of fields have turned to a methodology known as ecological momentary assessment (EMA) to assess quotidian experiences associated with health problems. The objective of this study was to determine the feasibility of using EMA to obtain real-time responses from hearing aid users describing their experiences with challenging hearing situations.This study required three phases: (1) develop EMA methodology to assess hearing difficulties experienced by hearing aid users; (2) make use of focus groups to refine the methodology; and (3) test the methodology with 24 hearing aid users. Phase 3 participants carried a personal digital assistant 12 hr per day for 2 weeks. The personal digital assistant alerted participants to respond to questions four times a day. Each assessment started with a question to determine whether a hearing problem was experienced since the last alert. If "yes," then up to 23 questions (depending on contingent response branching) obtained details about the situation. If "no," then up to 11 questions obtained information that would help to explain why hearing was not a problem. Each participant completed the Hearing Handicap Inventory for the Elderly (HHIE) both before and after the 2-week EMA testing period to evaluate for "reactivity" (exacerbation of self-perceived hearing problems that could result from the repeated assessments).Participants responded to the alerts with a 77% compliance rate, providing a total of 991 completed momentary assessments (mean = 43.1 per participant). A substantial amount of data were obtained with the methodology. It is important to note that participants reported a "hearing problem situation since the last alert" 37.6% of the time (372 responses). The most common problem situation involved "face-to-face conversation" (53.8% of the time). The next most common problem situation was "telephone conversation" (17.2%) followed by "TV, radio, iPod, etc." (15.3%), "environmental sounds" (9.7%), and "movies, lecture, etc." (4.0%). Comparison of pre- and post-EMA mean HHIE scores revealed no significant difference (p > 0.05), indicating that reactivity did not occur for this group. It should be noted, however, that 37.5% of participants reported a greater sense of awareness regarding their hearing loss and use of hearing aids.Results showed participants were compliant, gave positive feedback, and did not demonstrate reactivity based on pre- and post-HHIE scores. We conclude that EMA methodology is feasible with patients who use hearing aids and could potentially inform hearing healthcare (HHC) services. The next step is to develop and evaluate EMA protocols that provide detailed daily patient information to audiologists at each stage of HHC. The advantages of such an approach would be to obtain real-life outcome measures, and to determine within- and between-day variability in outcomes and associated factors. Such information at present is not available from patients who seek and use HHC services.

Project description:Debilitating hearing loss (HL) affects ~6% of the human population. Only 20% of the people in need of a hearing assistive device will eventually seek and acquire one. The number of people that are satisfied with their Hearing Aids (HAids) and continue using them in the long term is even lower. Understanding the personal, behavioral, environmental, or other factors that correlate with the optimal HAid fitting and with users' experience of HAids is a significant step in improving patient satisfaction and quality of life, while reducing societal and financial burden. In SMART BEAR we are addressing this need by making use of the capacity of modern HAids to provide dynamic logging of their operation and by combining this information with a big amount of information about the medical, environmental, and social context of each HAid user. We are studying hearing rehabilitation through a 12-month continuous monitoring of HL patients, collecting data, such as participants' demographics, audiometric and medical data, their cognitive and mental status, their habits, and preferences, through a set of medical devices and wearables, as well as through face-to-face and remote clinical assessments and fitting/fine-tuning sessions. Descriptive, AI-based analysis and assessment of the relationships between heterogeneous data and HL-related parameters will help clinical researchers to better understand the overall health profiles of HL patients, and to identify patterns or relations that may be proven essential for future clinical trials. In addition, the future state and behavioral (e.g., HAids Satisfiability and HAids usage) of the patients will be predicted with time-dependent machine learning models to assist the clinical researchers to decide on the nature of the interventions. Explainable Artificial Intelligence (XAI) techniques will be leveraged to better understand the factors that play a significant role in the success of a hearing rehabilitation program, constructing patient profiles. This paper is a conceptual one aiming to describe the upcoming data collection process and proposed framework for providing a comprehensive profile for patients with HL in the context of EU-funded SMART BEAR project. Such patient profiles can be invaluable in HL treatment as they can help to identify the characteristics making patients more prone to drop out and stop using their HAids, using their HAids sufficiently long during the day, and being more satisfied by their HAids experience. They can also help decrease the number of needed remote sessions with their Audiologist for counseling, and/or HAids fine tuning, or the number of manual changes of HAids program (as indication of poor sound quality and bad adaptation of HAids configuration to patients' real needs and daily challenges), leading to reduced healthcare cost.

Dataset Information

Vowel production of Mandarin-speaking hearing aid users with different types of hearing loss.

Publications

Vowel production of Mandarin-speaking hearing aid users with different types of hearing loss.

Similar Datasets

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