Fundamentals of Brain-Computer Interfaces and Rehabilitation Robotics

Neurotechnology and robotics are transforming healthcare, offering new hope through advanced rehabilitation systems. This course provides the essential scientific and engineering groundwork to enter this exciting field. By the end of this course, you will have a clear understanding of how neural signals are captured, processed, and translated into commands for controlling external devices. You will be prepared to analyze the design principles of both non-invasive BCI systems and complex mechatronic rehabilitation aids. What you'll learn: * Learn the biological basis of neural signals (EEG, ECoG, EMG) used in Brain-Computer Interfaces. * Understand the architecture and components required for a complete BCI system, from sensors to actuators. * Apply fundamental signal processing techniques for cleaning and interpreting raw neural data. * Analyze the mechanical and control principles governing mechatronic rehabilitation systems and prosthetics. * Configure basic control loops essential for operating robotic assistive devices. * Practice evaluating the ethical considerations and safety standards critical for medical neurotechnology design. The course begins with an exploration of neurophysiology and signal acquisition, progressing through signal processing methods and control theory, and culminating in the practical application of these concepts in designing functional robotic rehabilitation devices. This course is designed for absolute beginners interested in biomedical engineering, robotics, or neurotechnology. No prior experience in signal processing, robotics, or neuroscience is required. Start building your expertise in the future of assistive technology today.