A Deep Learning Based Wearable Healthcare Iot Device for AI-Enabled Hearing Assistance Automation

Fraser Young, Li Zhang, Richard Jiang, Han Liu, Conor Wall

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

With the recent booming of artificial intelligence (AI), particularly deep learning techniques, digital healthcare is one of the prevalent areas that could gain benefits from AI-enabled functionality. This research presents a novel AI-enabled Internet of Things (IoT) device operating from the ESP-8266 platform capable of assisting those who suffer from impairment of hearing or deafness to communicate with others in conversations. In the proposed solution, a server application is created that leverages Google's online speech recognition service to convert the received conversations into texts, then deployed to a micro-display attached to the glasses to display the conversation contents to deaf people, to enable and assist conversation as normal with the general population. Furthermore, in order to raise alert of traffic or dangerous scenarios, an 'urban-emergency' classifier is developed using a deep learning model, Inception-v4, with transfer learning to detect/recognize alerting/alarming sounds, such as a horn sound or a fire alarm, with texts generated to alert the prospective user. The training of Inception-v4 was carried out on a consumer desktop PC and then implemented into the AI-based IoT application. The empirical results indicate that the developed prototype system achieves an accuracy rate of 92% for sound recognition and classification with real-time performance.

Original languageEnglish
Title of host publicationProceedings of 2020 International Conference on Machine Learning and Cybernetics, ICMLC 2020
Place of PublicationPiscataway, NJ
PublisherIEEE
Pages235-240
Number of pages6
ISBN (Electronic)9780738124261
DOIs
Publication statusPublished - 2 Dec 2020
Event19th International Conference on Machine Learning and Cybernetics, ICMLC 2020 - Virtual, Online
Duration: 4 Dec 2020 → …

Publication series

NameProceedings - International Conference on Machine Learning and Cybernetics
Volume2020-December
ISSN (Print)2160-133X
ISSN (Electronic)2160-1348

Conference

Conference19th International Conference on Machine Learning and Cybernetics, ICMLC 2020
CityVirtual, Online
Period4/12/20 → …

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