Decoding of Hand Gestures from Electrocorticography with LSTM Based Deep Neural Network

Jathurshan Pradeepkumar, Mithunjha Anandakumar, Vinith Kugathasan, Thilina D. Lalitharatne, Anjula C. De Silva, Simon L. Kappel

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3 Citationer (Scopus)

Abstract

Hand gesture decoding is a key component of controlling prosthesis in the area of Brain Computer Interface (BCI). This study is concerned with classification of hand gestures, based on Electrocorticography (ECoG) recordings. Recent studies have utilized the temporal information in ECoG signals for robust hand gesture decoding. In our preliminary analysis on ECoG recordings of hand gestures, we observed different power variations in six frequency bands ranging from 4 to 200 Hz. Therefore, the current trend of including temporal information in the classifier was extended to provide equal importance to power variations in each of these frequency bands. Statistical and Principal Component Analysis (PCA) based feature reduction was implemented for each frequency band separately, and classification was performed with a Long Short-Term Memory (LSTM) based neural network to utilize both temporal and spatial information of each frequency band. The proposed architecture along with each feature reduction method was tested on ECoG recordings of five finger flexions performed by seven subjects from the publicly available 'fingerflex' dataset. An average classification accuracy of 82.4% was achieved with the statistical based channel selection method which is an improvement compared to state-of-the-art methods.

OriginalsprogEngelsk
Titel43rd Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2021
Antal sider4
ForlagInstitute of Electrical and Electronics Engineers Inc.
Publikationsdato2021
Sider420-423
ISBN (Elektronisk)9781728111797
DOI
StatusUdgivet - 2021
Begivenhed43rd Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2021 - Virtual, Online, Mexico
Varighed: 1 nov. 20215 nov. 2021

Konference

Konference43rd Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2021
Land/OmrådeMexico
ByVirtual, Online
Periode01/11/202105/11/2021
NavnProceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS
ISSN1557-170X

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