TY - GEN
T1 - Evaluating the mindwave headset for automatic upper body motion classification
AU - Naula, Edisson
AU - Garcia, Andres F.
AU - Palacio-Baus, Kenneth
AU - Minchala, Luis I.
AU - Vazquez-Rodas, Andres
AU - Astudillo, Darwin
N1 - Publisher Copyright:
© 2017 IEEE.
PY - 2017/7/2
Y1 - 2017/7/2
N2 - This paper presents preliminary results on evaluating the NeuroSky Mindwave headset for upper body motion intention classification. An artificial neural network (ANN) is trained by using a data set built for two different feature extraction methods, one based on the wavelet transform (WT) and another based on the use of spectrograms. Since there are five different types of brain waves,(α, β, γ, Δ, θ) some data aggregation procedures are proposed to reduce the dimensionality of the data set. The classification results show that it is possible to attain a 73.1% of assertion rate.
AB - This paper presents preliminary results on evaluating the NeuroSky Mindwave headset for upper body motion intention classification. An artificial neural network (ANN) is trained by using a data set built for two different feature extraction methods, one based on the wavelet transform (WT) and another based on the use of spectrograms. Since there are five different types of brain waves,(α, β, γ, Δ, θ) some data aggregation procedures are proposed to reduce the dimensionality of the data set. The classification results show that it is possible to attain a 73.1% of assertion rate.
KW - ANN
KW - classificator
KW - data compression
KW - Mindwave
UR - https://www.scopus.com/pages/publications/85050904685
U2 - 10.1109/INCISCOS.2017.10
DO - 10.1109/INCISCOS.2017.10
M3 - Contribución a la conferencia
AN - SCOPUS:85050904685
T3 - Proceedings - 2017 International Conference on Information Systems and Computer Science, INCISCOS 2017
SP - 166
EP - 173
BT - Proceedings - 2017 International Conference on Information Systems and Computer Science, INCISCOS 2017
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2nd International Conference on Information Systems and Computer Science, INCISCOS 2017
Y2 - 23 November 2017 through 25 November 2017
ER -