35374 - Rehabilitation Bioengineering M

Learning outcomes

Provide students with an overview of disability issues, the aids used, and the techniques for functional assessment, with particular reference to neurorehabilitation and neuroprosthetics in posture and movement control, prosthetics and orthoses for upper and lower limbs, and remote monitoring, home automation applications, and virtual reality.

Course contents

Contents
1. Introduction to the Course
• Rehabilitation Technologies and Their Impact on Health and Society: Disabled People, Children, and the Elderly

2. Anatomical and Physiological Bases
• Anatomy and Physiology of the Musculoskeletal System
• Organization of the Central and Peripheral Nervous System
• Central nervous system functions most often affected by traumatic/vascular events, neurodegenerative, neurodevelopmental, and neuromotor diseases.

3. Biomechanics
• Biomechanics: definition, objectives, methodologies
• Statics, kinematics, and dynamics of rigid bodies and articulated systems
• Biomechanics of human movement: general objectives, historical overview
• Kinematics and dynamics of human movement
• Movement analysis: Markerless and marker-based systems (e.g., stereophotogrammetry), dynamometry, and wearable sensors
• Clinical applications in adult and pediatric patients
• Biomechanical exercises

4. Posture and movement control
• Postural control
• Balance disorders and their clinical assessment
• Instrumental assessment of postural control: static and dynamic posturography, stabilometric techniques
• Models of postural control
• The posturographic signal: parameters derived from the trajectory of the center of pressure
• Falls in elderly or disabled subjects: stability analysis, determinants of falls, dynamics, classification, prediction, assistance, and rehabilitation
• Clinical applications in adult and pediatric patients Pediatric
• Exercises

5. Elements of Functional and Cognitive Assessment
• Definition of Function
• Functional Assessment Scales
• Instrumental Techniques for Functional Assessment
• Extracting Information from Data: Using Statistical Models and Machine Learning-Based Classification Techniques.
• Assessment of Cognitive Function
• Application Examples

6. Rehabilitation Techniques Based on Biofeedback and Virtual Reality
• Biofeedback: Basic Principles and Applications
• Postural Biofeedback, Gait Biofeedback, and Neurofeedback
• Rehabilitation Systems Based on Virtual Reality
• Case Studies

7. Aids and Systems for Mobility, Communication, and Independence
• Introduction to Disability
• ICIDH and ICF Classification
• Definition of Aid. Aids for Independence. Design for All and Customized Technologies.
• Prosthetics and Orthoses for Upper and Lower Limbs. Aesthetic Prosthetics and Functional Prosthetics. Exoskeletal and endoskeletal prosthetics. Static and dynamic orthoses. Clinical applications for adults and children.
• Mobility aids
• Exoskeletons and robotic systems for rehabilitation

8. Human-computer-environment interfaces
• Sensors for motor disabilities
• Interfaces for assistive technologies.
• Technological and IT aids for communication. Computer access systems. Special keyboards and mouse emulators. Software for easier PC access.
• Home automation systems and standards. Data transmission methods in home automation systems.
• Home automation and disability
• Virtual reality-based interfaces
• Brain-computer interfaces (BCIs) based on electroencephalography (EEG) and electromyography (EMG) signals
Invia commenti

Readings/Bibliography

1. Cappello A., Cappozzo A., di Prampero P.E. (Eds.). (2003). Bioingegneria della Postura e del Movimento, Patron Editore.
2. Winter D.A. (2009), Biomechanics and Motor Control of Human Movement, John Wiley & Sons.
3. Ozkaya N., Nordin M., Goldsheyder D., Leger D. (Eds. Angelo Cappello, Lorenzo Chiari) (2021) Fondamenti di Biomeccanica. Equilibrio, movimento e deformazione, Piccin Editore.
4. Farina, D., Jensen, W., & Akay, M. (Eds.). (2013). Introduction to neural engineering for motor rehabilitation (Vol. 40). John Wiley & Sons.
5. Salisbury, D. B., Dahdah, M., Driver, S., Parsons, T. D., & Richter, K. M. (2016, April). Virtual reality and brain computer interface in neurorehabilitation. In Baylor university medical center proceedings (Vol. 29, No. 2, pp. 124-127). Taylor & Francis.
6. Reinkensmeyer, D. J., & Dietz, V. (Eds.). (2016). Neurorehabilitation technology. New York: Springer.
7. 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.
8. Chen, S. C., Bodine, C., & Lew, H. L. (2021). Assistive Technology and Environmental Control Devices. In Braddom's Physical Medicine and Rehabilitation (pp. 374-388). Elsevier.
9. Gupta, D., Sharma, M., Chaudhary, V., & Khanna, A. (Eds.). (2021). Robotic Technologies in Biomedical and Healthcare Engineering. CRC Press.
10. Chui, K. K., Jorge, M., Yen, S. C., & Lusardi, M. M. (2020). Orthotics and prosthetics in rehabilitation.

Teaching methods

Lectures and exercises in the classroom and laboratory

Assessment methods

The final exam includes a written and an oral test. The written test consists of an exercise for Module 1 and open-ended questions for Module 2. The oral exam involves a project presentation.

Teaching tools

• PowerPoint Presentations
• Stereo-photogrammetric system
• Dynamometric platforms
• Multi-channel wireless electromyograph
• Wearable sensors and actuators
• Virtual reality headsets
• Electroencephalograph for BCI

Office hours

See the website of Rita Stagni

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