Significant progress has been made in systems that interpret the electrical signals of the
brain in order to control an actuator. One version of these systems senses neuronal …

A successful biomaterial–neural tissue interface should demonstrate biocompatibility,
cytocompatibility, the ability to integrate properly within neural tissues, and the prolonged …

This second edition of a bestseller presents systematic and extensive coverage of the
primary areas of research and development within VE technology. It brings together a …

Cortical control of neuroprosthetic devices is known to require neuronal adaptations. It
remains unclear whether a stable cortical representation for prosthetic function can be …

This paper introduces and demonstrates a novel brain–machine interface (BMI) architecture
based on the concepts of reinforcement learning (RL), coadaptation, and shaping. RL allows …

An increasing number of complex systems are now modeled as networks of coupled
dynamical entities. Nonlinearity and high-dimensionality are hallmarks of the dynamics of …

When the sensory–motor integration system is malfunctioning provokes a wide variety of
neurological disorders, which in many cases cannot be treated with conventional …

Heart function measured by electrocardiograms (ECG) is crucial for patient care. ECG
generated waveforms are used to find patterns of irregularities in cardiac cycles in patients …

The Kalman filter is commonly used in neural interface systems to decode neural activity and
estimate the desired movement kinematics. We analyze a low-complexity Kalman filter …

Background In the development of Brain Machine Interfaces (BMIs), there is a great need to
enable users to interact with changing environments during the activities of daily life. It is …