About this course:

  • Course Name: Robotic Neurorehabilitation
  • Course Code: ME 611
  • L-T-P-C : 3-0-0-6
  • Syllabus: NaN
  • Course Type: Department Elective


    • Robotic Neurorehabilitation

    Description:

    Syllabus

    Introduction: Overview of Robotic Neurorehabilitation. Neurophysiology of Motor Recovery.

    Biomechatronics and Design Concepts: Biomechatronics for Robot-mediated Neurorehabilitation. Robotic Architectures. Overview of Sensors and Actuators for Human-Robot Interaction. Robotic Neurorehabilitation Systems: Wearable Robotic Systems. Control Strategies. Upper-limb Exoskeletons. Robot-assisted Upper-limb Rehabilitation. Exoskeletal Devices for Lower-limb. Robot-assisted Gait Rehabilitation. Gait Analysis. Computational Neurorehabilitation: Quantitative measures – encompassing kinematic, kinetic, timing, sensory, and neuromechanical aspects of performance. Models of Neuromotor Recovery. Computational Models of Motor Learning. BCI and Neurorehabilitation: Reverse Engineer the Brain. Neurophysiological Bases of EEG. Motor Imagery Brain Computer Interface (BCI) and Neurorehabilitation. Mental Fatigue and Adaptive BCIs. Advances in Robot-assisted Rehabilitation: Haptics-enabled Interactive Robotic Neurorehabilitation. Hybrid Functional Electrical Stimulations. Design of Innovative Control Strategies. Reinforcement Learning Driven Intelligent Robotic Devices for Neurorehabilitation.

    Texts/References:

    1. Roberto Colombo, Vittorio Sanguineti, eds. Rehabilitation Robotics: Technology and Applications. Academic Press, 2018.
    2. D. Zhang, V. Dubey, W. Yu, K. H. Low, eds. Biomechatronics: Harmonizing Mechatronic Systems with Human Beings. Frontiers Media, 2019.
    3. Jose L Pons, Diego Torricelli, eds. Emerging Therapies in Neurorehabilitation. Springer, 2014.
    4. Dejan B. Popovic, Thomas Sinkjær. Control of Movement for the Physically Disabled: Control for Rehabilitation Technology. 2nd Edition, Springer, 2000.