35374 - Rehabilitation Bioengineering M

Learning outcomes

To give the student a framework on disability issues, aids and techniques used for the functional evaluation with particular reference to neurorehabilitation and neuroprostheses in the control of posture and movements, prosthetics and orthotics for upper and lower limbs, and remote monitoring, home automation applications and virtual reality.

Course contents

1. Introduction to the course
• Technologies for rehabilitation and their impact on health and society: individual with disabilities, the child and the elderly

2. Anatomical and physiological bases
• Anatomy and physiology of the musculoskeletal system
• Organization of the central and peripheral nervous system
• Functions of the central nervous system more often affected by traumatic/vascular events, neurodegenerative diseases, neurodevelopment disorders, and neuromotor diseases.

3. Biomechanics
• Biomechanics: definition, objectives, methodologies
• Statics, kinematics and dynamics of rigid bodies and multilink/multijoint systems
• Biomechanics of human movement: general purpose, history
• Kinematics and dynamics of human movement
• Movement analysis:Markerless and marker-based systems (e.g., stereophotogrammetry), dinamometry, and wearable sensors
• Clinical applications for adult and pediatric patients

4. Control of posture and movements
• Postural control
• Balance disorders and their clinical evaluation
• Assessment of postural control by static and dynamic posturography, stabilometric techniques
• Mathematical models of postural control
• The posturographic signal: parameters derived from the trajectory of the center of pressure
• Falls in the elderly and disabled subjects: stability analysis, determinants, dynamics, classification, prediction, assistance and rehabilitation.
• Clinical applications for adult and pediatric patients
• Exercises and projects

5. Elements of functional and cognitive assessment
• Definition of function
• Functional evaluation scales
• Functional evaluation techniques
• Basics of pattern recognition and classification techniques: statistical models and machine learning-based classification techniques.
• Assessment of cognitive function
• Applications

6. Rehabilitation techniques based on biofeedback and virtual reality
• Biofeedback: basic principles and applications
• Postural biofeedback, gait biofeedback and neurofeedback
• Virtual Reality-based rehabilitation systems
• Applications

7. Aids and systems for supporting mobility, communication, and independence
• Introduction to Disability
• ICIDH and ICF classifications
• Definition of Aid. Aids for supporting independence. Design for All and customized technologies
• Prostheses and orthoses for upper and lower limbs. Cosmetic prostheses and functional prostheses. Exoskeletal and endoskeletal prostheses. Static and dynamic orthoses. Clinical applications for adults and children. prostheses and functional prostheses. Orthosis
• Mobility aids
• Robotic systems for rehabilitation

8. Human-machine-environment interface
• Sensors for motor disabilities
• Interfaces for assistive technology
• Communication aids. Computer access solutions. Assistive keyboards and mouse emulators. Assistive software for computer access
• Home automation technology and operating standards
• Domotics and disability
• Virtual reality-based interfaces
• Brain-computer interface (BCI) based on electroencephalographic (EEG) and electromyographic (EMG) signals

Readings/Bibliography

Teacher's notes and Power Point presentations.

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

During the lectures, the general issues related to the design and development of systems for sensory-motor rehabilitation will be discussed. The first module includes topics 1-4 while the remaining 5-8 will be covered in the second module.

The course includes in-class activities that will be carried out on the students' laptops to design and simulate experiments in a realistic way.

Also, projects will be assigned to small groups of students or individually, in order to help students to familiarize themselves with algorithms theoretically presented and investigate aspects of the course through the analysis of clinical cases.

Assessment methods

The final examination includes written and oral exams. The written test consists of one exercise for Module 1 and open questions for Module 2. The oral examination includes the oral presentation of the project.

 

Teaching tools

• PowerPoint presentations
• Stereo-photogrammetric system
• Force platforms
• Wireless multi-channel electromyograph
• Wearable sensors and actuators
• Virtual reality technology
• Electroencephalography for BCI technology

 

Office hours

See the website of Silvia Orlandi