@inproceedings{595fe25df33a4d3180d2bd0d24f3059c,
title = "Live Demonstration: Speech reconstruction for speech impaired individuals using Assistive Magnetic Skin System",
abstract = "People diagnosed with a speech-sound disorder (SSD) may have any combination of problems creating or forming speech sounds needed to communicate with others, resulting in frustration, depression and social isolation. Enhanced by advances in artificial wearable skins and machine learning, natural verbal communication for SSD afflicted individuals is more feasible than ever before. An Assistive Magnetic Skin System (AM2S) is designed to assist speech impaired individuals to communicate with others by reading the mouth movement. The system measures the changes in the magnetic skin patches attached next to the lower lip through magnetic field sensors embedded in Magnetphones. The measured magnetic field signal data is processed using a Fine k-Nearest Neighbor (KNN) classifier model. Ultimately, the classified data can be deployed visually on a display or verbally on speakers. AM2S successfully identifies full English alphabets with an average accuracy rate of 94.96%.",
keywords = "machine learning, magnetic skin, wearable sensors",
author = "Angel, {Montserrat Ramirez De} and Almansouri, {Abdullah S.} and Salama, {Khaled Nabil}",
note = "Publisher Copyright: {\textcopyright} 2023 IEEE.; 2023 IEEE Biomedical Circuits and Systems Conference, BioCAS 2023 ; Conference date: 19-10-2023 Through 21-10-2023",
year = "2023",
doi = "10.1109/BioCAS58349.2023.10388857",
language = "English (US)",
series = "BioCAS 2023 - 2023 IEEE Biomedical Circuits and Systems Conference, Conference Proceedings",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
booktitle = "BioCAS 2023 - 2023 IEEE Biomedical Circuits and Systems Conference, Conference Proceedings",
address = "United States",
}