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Early Detection and Management of Hearing Loss
Halmstad University, School of Information Technology.
Halmstad University, School of Information Technology.
2024 (English)Independent thesis Basic level (degree of Bachelor), 10 credits / 15 HE creditsStudent thesis
Abstract [en]

This project aims to develop a portable product using Arduino technology to approximate hearing clinic tests, programmed with IAR Embedded Workbench. Designed for workplace use, the device allows individuals to evaluate their hearing in a quiet room, raising awareness and promoting regular hearing checks. The device should be placed in an environment free from other electronic devices to minimize interference. Users can conduct hearing tests independently, encouraging early detection of potential hearing issues and enabling timely intervention.The results are evaluated through direct comparisons between the product and clinic results, as well as smaller studies comparing the product’s average results in different age groups with existing data on average hearing ability in those groups. Key findings include a Mean Absolute Error (MAE) of 3.85 dB to 9.0 dB and a Mean Percentage Error (MPE) of 31.78% to 224.32% across age groups and frequencies. Clinical test comparisons show an MAE of 5.71 dB to 6.78 dB and an MPE of 20.10% to 119.04%. Significant discrepancies are noted at lower frequencies (125 Hz and 250 Hz) with higher error margins. Wide confidence intervals were observed, indicating substantial variability and suggesting that the device is less reliable at lower frequency levels. Further testing with a larger sample size is needed to enhance precision and reliability, as it would help narrow the confidence intervals and provide more robust and dependable results.

Place, publisher, year, edition, pages
2024. , p. 59
Keywords [en]
Arduino technology, Hearing impairment, Hearing ability, Embedded systems, Hearing clinic
National Category
Engineering and Technology Computer Engineering
Identifiers
URN: urn:nbn:se:hh:diva-54055OAI: oai:DiVA.org:hh-54055DiVA, id: diva2:1875582
Subject / course
Computer science and engineering
Educational program
Computer Science and Engineering, 300 credits
Supervisors
Examiners
Available from: 2024-06-02 Created: 2024-06-23 Last updated: 2025-10-01Bibliographically approved

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fulltext(1355 kB)142 downloads
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CiteExportLink to record
Permanent link

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Citation style
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
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Language
  • de-DE
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  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
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  • Other locale
More languages
Output format
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