34811 - Rehabilitation Bioengineering (2nd cycle)

Academic Year 2019/2020

  • Docente: Lorenzo Chiari
  • Credits: 9
  • SSD: ING-INF/06
  • Language: Italian
  • Teaching Mode: Traditional lectures
  • Campus: Cesena
  • Corso: Second cycle degree programme (LM) in Biomedical Engineering (cod. 9243)

Learning outcomes

At the end of the course the student will acquire the basic knowledge for: - the quantitative assessment of the motor function - the design and informed use of the main ICT tools for sensory-motor rehabilitation - the selection and customization of assistive technologies.

Course contents

Aims

Students will acquire the basic knowledge and the essential tools for the analysis and the design of the most widespread ICT-based tools for functional assessment, assistance and rehabilitation. Students will:

- learn the basic psychometric properties of measurements of human functions;

- learn the more common tools for statistical data analysis and experiment design;

- learn the basic physiopathology of the sensory-motor and cognitive systems;

- learn how to quantitatively evaluate the sensory-motor and cognitive function;

- acquire the basic knowledge for the design and the usage of the most widespread tools for sensory-motor and cognitive rehabilitation;

- learn how to solve problems related to the selection and the personalization of the assistive technologies and their correct and safe usage;

- learn how to face and conduct projects of industrial relevance in the field of rehabilitation technologies.

Contents

1) The rehabilitation paradigms. ICF Biopsychosocial model. Major determinants of the rehabilitation space: Theoretical models; Outcome assessment; Tools and paradigms. The challenges of rehabilitation engineering. New technologies in rehabilitation: general trends. Key enabling technologies. Population ageing and active & healthy ageing.

2) Theoretical models: neurophysiopathology of motor systems. Neuroplasticity. The reward circuit. Mirror neurons. Neurocomputational models of motor learning and rehabilitation.

3) Basic statistical tools for testing differences among and within groups. Sample statistics and hypothesis testing. Analysis of variance. Intraclass correlations. Relationships among variables. Feature selection methods. Measurement theory for biopsychosocial sciences. The role of instrumental measures in rehabilitation. Measures and noise. Main properties of research variables: Validity; Reliability; Sensibility. Psychometric properties of common scales used in rehabilitation.

4) The challenges of measuring body functions and behaviours. Functional and performance tests. Balance control: physiopathology, neurobiomechanics, models, measures. Locomotion: physiopathology, neurobiomechanics, models, measures. Cognition: physiopathology, models, measures.

5) EMG measurements. Inertial sensors for human movement analysis. Working principles, mathematical models and calibration issues. Linear and nonlinear Kalman filter model for sensor fusion. mHealth applications for assessment, rehabilitation and precision medicine.

6) Prostheses, ortheses, assistive and rehabilitation technologies. The augmented feedback paradigm: biofeedback and neurofeedback systems. Sensory replacement. General architecture and design dimensions of a biofeedback system. Examples and demos of sEMG, balance, gait, HRV, EEG biofeedback systems. Unisensory vs multisensory feedback. Design of experiment for biofeedback-based experimental trials. Virtual Reality for rehabilitation. Brain-Machine-Interfaces. Functional electrical stimulation. Robotic exoskeletons. Ambient assisted living and telerehabilitation.

Readings/Bibliography

  • Lecture notes and ppt presentations provided by the lecturer
  • A. Cappello, A. Cappozzo, P.E. di Prampero (Eds.), Bioingegneria della Postura e del Movimento, Patron Editore, Bologna, 2003.
  • D. Popovic, T. Sinkjaer, Control of Movement for the Physically Disabled, Sprinter-Verlag, London, 2000.
  • J. Thomas, J. Nelson, S. Silverman, Research Methods in Physical Activity - 7th Edition, Human Kinetics, 2015.
  • Teaching methods

    During the lessons the general problems associated with the design, development and analysis of bioengineering systems for sensory-motor and cognitive rehabilitation are presented and discussed.
    The course will be complemented by experiments carried out in the Laboratory of Biomedical Engineering, by solving problems with the aid of Matlab, and by specialistic seminars. A relevant fraction of time will be dedicated to project work, carried out in teams. This will allow students to investigate theoretical aspects of the course through a first-hand experience, under the supervision of an academic tutor.

    Assessment methods

    The learning process will be assessed:
    1) during the lessons, by means of Q&A, weekly tasks and exercises solved by the lecturer interacting with students;
    2) in the lab, by means of practical exercises solved with Matlab;
    3) by means of self-conducted team projects (mandatory);
    4) by means of the final exam (written test and oral presentation of the projects).

    In the written test students will be asked to solve 3 exercises and to answer 3 multiple-choice questions.

    Final grade will be the average of the grades obtained in the written test and in the project presentation.

    Teaching tools

  • Power Point Slides
  • 1 Stereo-photogrammetric system (6 cameras)
  • 2 force platforms
  • 1 Multichannel EMG wireless system
  • 1 EEG system
  • Wearable sensors (IMUs)
  • Mobile devices (smartphones and smartwatches)
  • PC with Matlab
  • Any other materials needed for carrying out project activities
  • Office hours

    See the website of Lorenzo Chiari

    SDGs

    Good health and well-being Quality education Decent work and economic growth Industry, innovation and infrastructure

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