93932 - Ageing and Rehabilitation Engineering

Academic Year 2022/2023

  • Docente: Lorenzo Chiari
  • Credits:: 9
  • SSD: ING-INF/06
  • Language: English
  • Teaching Mode: Traditional lectures
  • Campus: Cesena
  • Corso: Second cycle degree programme (LM) in Biomedical Engineering (cod. 9266)

Learning outcomes

At the end of the course, the student acquires advanced knowledge on the analysis and design of the most widespread bioengineering systems for functional assessment, sensor-motor and cognitive assistance and rehabilitation, and for geriatric prevention. In particular, the student knows how to: - bring back the main functional alterations to the pathophysiology of the systems involved and to the physiological ageing processes; - use the main tools and methods critically for the evaluation of bodily functions, determining the essential properties of the measures in a bio-psycho-social perspective; - carry out a high-level design of assistive, rehabilitative and preventive devices; - orientate among the main approaches in the neurorobotic and neurorehabilitative field.

Course contents

1. Rehabilitation engineering

1.1 The rehabilitation paradigms. The ICF Biopsychosocial model. Major determinants of the rehabilitation space: Theoretical models; Tools and paradigms; Outcome assessment. The challenges of rehabilitation engineering. New technologies in rehabilitation: general trends. Key enabling technologies.

1.2 Theoretical models: neurophysiopathology of motor systems. Neuroplasticity. The reward circuit. Mirror neurons. The basis of neuromotor learning in rehabilitation.

1.3 Tools and paradigms: 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-, and HRV-biofeedback systems. Unisensory vs multisensory feedback. Design of experiment for biofeedback-based experimental trials. Virtual Reality for rehabilitation. Exergames. Functional electrical stimulation. Robotic exoskeletons. General architecture of a telerehabilitation platform. mHealth applications for rehabilitation.

1.4 Outcome assessment: The challenges of measuring body functions and behaviours. 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. Functional and performance tests. Balance control: neurobiomechanics, models, measures. Locomotion: neurobiomechanics, models, measures. Linear and nonlinear Kalman filter model for sensor fusion.

2. Engineering for ageing and longevity

2.1 The physiology of ageing. Principal chronic disabilities of old age: Geriatric Giants. Focus on: Dementia, Falls & Dizziness, Osteoporosis, Pain in the Elderly, Frailty. Determinants of Active & Healthy Ageing.

2.2 Gerontechnology. Gerontechnology goals: Prevention; Compensation; Care; Enhancement. Design challenges for Active & Healthy Ageing. Case studies: technological solutions for prevention, compensation, care, and enhancement. Digital biomarkers of ageing.



Lecture notes, ppt slides and articles provided by the lecturer.


A. Cappello, A. Cappozzo, P.E. di Prampero (Eds.), Bioingegneria della Postura e del Movimento, Patron Editore, Bologna, 2003.

Nuno M. Garcia, Joel Jose P.C. Rodrigues (Eds.),  Ambient Assisted Living, CRC Press, 2017.

Further readings

D. Popovic, T. Sinkjaer, Control of Movement for the Physically Disabled, Sprinter-Verlag, London, 2000.

A. Bonfiglio, S. Cerutti, D. De Rossi, G. Magenes (Eds.), Sistemi indossabili intelligenti per la salute e la protezione dell’uomo, Patron Editore, Bologna, 2008.

J. Thomas, J. Nelson, S. Silverman, Research Methods in Physical Activity-7th Edition, Human Kinetics, 2015.

Teaching methods

During the lessons (in presence or from remote) the general problems associated with the design, development and analysis of bioengineering systems for rehabilitation and ageing 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.

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

Assessment methods

The learning process will be assessed:
1) during the lessons, by means of Q&A, 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.

The presentation of the projects will be arranged for groups on a different day than the dates of the written test. It will be scheduled in January or February, before lessons resume. The evaluation will be individualized and will concern: overall quality and consistency of the work done in relation to the objectives initially assigned; group autonomy; presentation effectiveness; individual contribution to the project.

The final mark will be the average of the evaluations obtained in the written test (50%) and in the project presentation (50%).

Teaching tools

  • Power Point Slides
  • 1 instrumented treadmill with biofeedback facilities
  • 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) with Android
  • PCs with Matlab
  • Any other materials needed for carrying out project activities (e.g. development kits)
  • Office hours

    See the website of Lorenzo Chiari