References

Abdel-Hamid, O., A.R. Mohamed, H. Jiang, L. Deng and G. Penn et al., 2014. Convolutional neural networks for speech recognition. IEEE. ACM. Trans. Audio Speech lang. Process., 22: 1533-1545.
CrossRef  |  Direct Link  |  

Abreu, J.G., J.M. Teixeira, L.S. Figueiredo and V. Teichrieb, 2016. Evaluating sign language recognition using the Myo armband. Proceedings of the 2016 18th International Symposium on Virtual and Augmented Reality (SVR), June 21-24, 2016, IEEE, Gramado, Brazil, ISBN:978-1-5090-4149-7, pp: 64-70.

Arief, Z., I.A. Sulistijono and R.A. Ardiansyah, 2015. Comparison of five time series EMG features extractions using Myo Armband. Proceedings of the 2015 International Symposium on Electronics (IES), September 29-30, 2015, IEEE, Surabaya, Indonesia, ISBN:978-1-4673-9345-4, pp: 11-14.

Krizhevsky, A., I. Sutskever and G.E. Hinton, 2012. Imagenet Classification with Deep Convolutional Neural Networks. In: Advances in Neural Information Processing Systems, Leen, T.K., G.D. Thomas and T. Volker (Eds.). MIT Press, Cambridge, Massachusetts, USA., ISBN:0-262-12241-3, pp: 1097-1105.

Mulling, T. and M. Sathiyanarayanan, 2015. Characteristics of hand gesture navigation: A case study using a wearable device (MYO). Proceedings of the 2015 International Conference on British HCI, July 13-17 2015, ACM, Lincoln, Lincolnshire, UK., ISBN:978-1-4503-3643-7, pp: 283-284.

Murillo, P.U., R.J. Moreno and O.F.A. Sanchez, 2016. Individual robotic arms manipulator control employing electromyographic signals acquired by Myo armbands. Int. J. Applied Eng. Res., 11: 11241-11249.
Direct Link  |  

Noce, E., L. Zollo, A. Davalli, R. Sacchetti and E. Guglielmelli, 2016. Experimental analysis of the relationship between neural and muscular recordings during hand control. Proceedings of the 2016 6th IEEE International Conference on Biomedical Robotics and Biomechatronics (BioRob), June 26-29, 2016, IEEE, Singapore, Singapore, ISBN:978-1-5090-3287-7, pp: 1104-1109.

Simonyan, K. and A. Zisserman, 2014. Very deep convolutional networks for large-scale image recognition. Master Thesis, Cornell University, Ithaca, New York.

Singer, M.A. and S. Goldin-Meadow, 2005. Children learn when their teacher's gestures and speech differ. Psychol. Sci., 16: 85-89.
Direct Link  |  

Thalmic Labs Inc., 2017. Myo SDK manual: Getting started. Thalmic Labs Inc., Kitchener, Ontario. https://developer.thalmic.com/docs/api_reference/platform/getting-started.html.

Thalmic Labs Inc., 2017. Technical specifications. Thalmic Labs Inc., Kitchener, Ontario. https://www.myo.com/techspecs.

Wand, M. and T. Schultz, 2014. Pattern learning with deep neural networks in EMG-based speech recognition. Proceedings of the 2014 36th Annual International Conference on Engineering in Medicine and Biology Society (EMBC), August 26-30, 2014, IEEE, Chicago, Illinois, ISBN:978-1-4244-7929-0, pp: 4200-4203.

Welch, P.D., 1967. The use of fast Fourier transform for the estimation of power spectra: A method based on time-averaging over short, modified periodograms. IEEE Trans. Audio Electroacoust., 15: 70-73.
CrossRef  |