Brain-machine Interface Engineering
Brain-Machine Interaction provides a unique framework for understanding the motivation and techniques of applying signal processing methodologies to brain-machine interaction (BMI) design and experimentation. Each chapter begins with a historical perspective and motivating example illustrating the need for this approach in BMI design. Included in each chapter is a list of assumptions associated with each methodological choice and the impact on BMI performance. To validate and advance the state-of-the-art of BMI modeling design, model performance is discussed and how the proposed model represents the neural-to-motor mappings. Finally, the feasibility of building BMIs (technical and practical aspects) is developed in the context of digital computational hardware.
Other editions - View all
action potentials adaptive filtering algorithm analysis approach average Bayesian behavior brain cell channel coding coefficients computational correlation cortical covariance data set decoding discrete dynamics electrode encoding Engineering ensemble experts firing rate Gaussian hand position hand trajectory hidden IEEE implanted implemented input Journal of Neurophysiology Kalman filter kinematic LFPs linear filter linear models mapping matrix methods microelectrode modulation Monte Carlo motor BMIs motor control motor cortex movement neural activity neural data neural engineering neural ensemble neural interfaces Neural Networks neural recordings neuronal firing neuronal subset neuroprosthetic Neuroscience noise nonlinear observation optimal output particle filter performance Pico point process Poisson posterior density probe problem reconstruction recursive representation response RMLP samples segments sequential estimation shown in Figure signal processing solution spike sorting spike trains statistical TDNN techniques threshold tion topology tuning function update variable selection weights Wiener filter wireless
Page 15 - Visual perception in a blind subject with a chronic microelectronic retinal prosthesis', Vision Res., 43(24), 2573-2581.
Page 229 - Kennedy, PR, The cone electrode: a long-term electrode that records from neurites grown onto its recording surface.
Page 18 - Comparisons of MEG, EEG, and ECoG source localization in neocortical partial epilepsy in humans.