TY - GEN
T1 - Think to Speak - A Piezoelectric-EEG system for Augmentative and Alternative Communication (AAC) using Recurrent Neural Networks
AU - Sowah, Robert
AU - Friedman, Ryan
AU - Ofoli, Abdul R.
AU - Sarkodie-Mensah, Baffour
N1 - Publisher Copyright:
© 2019 IEEE.
PY - 2019/9
Y1 - 2019/9
N2 - The collection of individuals with severe speech and physical impairments (SSPI), is the target audience for the Think to Speak Augmentative and Alternative Communication (AAC) system. The slow communication rate of AACs accessible to the target audience renders them undesirable, exhausting to operate, and a barrier to social and economic inclusion. This research synergizes the use of Electroencephalography (EEG) and high-sensitivity piezoelectric sensor readings with a Long Short-Term Memory Recurrent Neural Network (LSTM RNN) to create a physically accessible AAC with performance comparable to 7.8 characters per minute communication rate. Since self-expression is inextricably linked with physical, mental, and emotional health, this research is of great significance to the estimated one percent of the global population with complex communication needs.
AB - The collection of individuals with severe speech and physical impairments (SSPI), is the target audience for the Think to Speak Augmentative and Alternative Communication (AAC) system. The slow communication rate of AACs accessible to the target audience renders them undesirable, exhausting to operate, and a barrier to social and economic inclusion. This research synergizes the use of Electroencephalography (EEG) and high-sensitivity piezoelectric sensor readings with a Long Short-Term Memory Recurrent Neural Network (LSTM RNN) to create a physically accessible AAC with performance comparable to 7.8 characters per minute communication rate. Since self-expression is inextricably linked with physical, mental, and emotional health, this research is of great significance to the estimated one percent of the global population with complex communication needs.
KW - Complex Communication Needs
KW - Electroencephalography (EEG)
KW - Long Short-Term Memory
KW - Piezoelectric sensor
KW - Recurrent Neural Network
UR - http://www.scopus.com/inward/record.url?scp=85076785722&partnerID=8YFLogxK
U2 - 10.1109/IAS.2019.8912419
DO - 10.1109/IAS.2019.8912419
M3 - Conference contribution
AN - SCOPUS:85076785722
T3 - 2019 IEEE Industry Applications Society Annual Meeting, IAS 2019
BT - 2019 IEEE Industry Applications Society Annual Meeting, IAS 2019
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2019 IEEE Industry Applications Society Annual Meeting, IAS 2019
Y2 - 29 September 2019 through 3 October 2019
ER -