93921 - Neurorobotics and Neurorehabilitation

Academic Year 2022/2023

  • Moduli: Cristiano Cuppini (Modulo 1) Sabato Mellone (Modulo 2)
  • Teaching Mode: Traditional lectures (Modulo 1) Traditional lectures (Modulo 2)
  • Campus: Cesena
  • Corso: Second cycle degree programme (LM) in Biomedical Engineering (cod. 9266)

Learning outcomes

At the end of the course, the student: - knows the main neuroengineering methods to develop the interaction between intelligent devices and the neural system; - knows the main neuro-robotic and neurorehabilitation approaches; - knows brain-inspired systems and devices based on the interaction among body, brain and computer for the recovery of motor skills and cognitive abilities.

Course contents

Module 1

The principles of cognitive neurorehabilitation. Neuroplasticity and compensation in neurorehabilitation. Principles in evaluating cognitive rehabilitation trainings and main factors affecting successful outcome. Rehabilitation approaches for the most common cognitive impairments.

Models for sensorimotor integration and computational neuroscience of motor control. Motor learning, adaptation and re-learning after brain damage. Models of motor control system and sensorimotor integration. Neural basis for motor control in humans. Motor re-learning after brain damage: neurorehabilitation issues.

Neurorobotics and Functional Electrical Stimulation. Robotics in rehabilitation: introduction and control strategies; speech and language neurorehabilitation using robotic-based therapy; Neuro-robots for children with autism spectrum disorders. Functional Electrical Stimulation in neurorehabilitation: bioengineering issues. Applications in rehabilitation.

Module 2

Human-machine interfaces for restoring communication and mobility. Invasive and non-invasive BCIs; imaging and brain biomarkers, brain-computer interface design, covert and overt speech tasks, motor imagery and motor execution tasks, mindfulness, neurofeedback, human factors and ergonomics.


Stuss, D. T., Winocur, G., & Robertson, I. H. (Eds.). (2010). Cognitive Neurorehabilitation. Evidence and Application. Cambridge University Press.

Reinkensmeyer, D. J., & Dietz, V. (Eds.). (2016). Neurorehabilitation technology. New York: Springer.

Dimitrousis, C., Almpani, S., Stefaneas, P., Veneman, J., Nizamis, K., & Astaras, A. (2020). Neurorobotics: Review of Underlying Technologies, Current Developments and Future Directions. Neurotechnology: Methods, advances and applications

Farina, D., Jensen, W., & Akay, M. (Eds.). (2013). Introduction to neural engineering for motor rehabilitation (Vol. 40). John Wiley & Sons.

Other textbooks:

Dietz, V., & Ward, N. (Eds.). (2015). Oxford textbook of neurorehabilitation. Oxford University Press, USA.

Artemiadis, P. (Ed.). (2014). Neuro-robotics: From brain machine interfaces to rehabilitation robotics (Vol. 2). Springer.

Teaching methods

The course will consist in classroom lessons, during which the teacher will explain the subjects of this course and will discuss the most recent scientific papers in the field of neurorehabilitation to help students familiarize with the most recent approaches developed in this specific field and analyze the structure of scientific papers. Laboratory experiences (mandatory for the students) will be performed to allow practical contents to be practised and acquired by the students and seminars will be given by experts in the field of neurorehabilitation.

In consideration of the type of activity and the teaching methods adopted, the attendance of this training activity requires the prior participation of all students in the training modules 1 and 2 on safety in the study places [https://elearning-sicurezza.unibo.it/], in e-learning mode.

Assessment methods

Written assessment for Module 2 (quizzes and open-ended questions) and oral assessment for Module 1 and 2.

Teaching tools

Blackboard, notebook, projector, lecture notes, Biomedical Engineering Laboratory.

Office hours

See the website of Cristiano Cuppini

See the website of Sabato Mellone


Good health and well-being Industry, innovation and infrastructure Reduced inequalities

This teaching activity contributes to the achievement of the Sustainable Development Goals of the UN 2030 Agenda.