A Smart Nocturnal Environment Monitoring System for the Hearing Impaired

John Finlay, Stefan Greppmair, Michael Jennings, Matthew Kane, Johannes Leopold, P Catherwood, James Uhomoibhi

Research output: Contribution to conferencePaperpeer-review

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This paper presents a novel machine learning prototype to actively assist hearing-impaired people during sleeping hours. The prototype can learn ambient sounds and intelligently decide if they are indicative of dangerous situations such as warning alarms, or if they are merely unimportant background sounds. The application is targeted towards the hearing-impaired who will have removed hearing aids or external components of cochlear implants before sleep. Any sounds of importance can then be translated into vibrations to awaken the sleeping hearing impaired user. The system is suggestive of future smart interactive machines to assist and protect those with either hearing loss or profound deafness.
Original languageEnglish
Number of pages3
Publication statusPublished (in print/issue) - 6 Jul 2018
EventBritish HCI Conference 2018 - Belfast, Belfast, Northern Ireland
Duration: 2 Jul 20186 Jul 2018


ConferenceBritish HCI Conference 2018
Abbreviated titleBHCI2018
Country/TerritoryNorthern Ireland


  • Hearing
  • Intelligent
  • Machine learning
  • Prototypes


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