1. Ju, Z., Ouyang, G., Wilamowska-Korsak, M. et al., Surface EMG based hand manipulation identification via nonlinear feature extraction and classification. IEEE Sensors Journal 13(9):3302–3311, 2013.
2. Jali, M. H., Ibrahim, I. M., Sulaima, M. F. et al., EMG signal features extraction of different arm movement for rehabilitation device. International Journal of Applied Engineering Research 9(21):11151–11162, 2014.
3. Bohari, Z. H., Jali, M. H., Baharom, M. F. et al., EMG signal statistical features extraction combination performance benchmark using unsupervised neural network for arm rehab device. International Journal of Applied Engineering Research 9(22):12393–12402, 2014.
4. Xu, X., Zhang, Y., Xu, X. et al., Surface EMG-based human-machine interface that can minimise the influence of muscle fatigue. International Journal of Modelling Identification & Control 22(4):298–306, 2014.
5. Farina, D., Jiang, N., Rehbaum, H. et al., The extraction of neural information from the surface EMG for the control of upper-limb prostheses: Emerging avenues and challenges. IEEE Transactions on Neural Systems & Rehabilitation Engineering 22(4):797–809, 2014.