Courses and Teaching Staff

The M.Sc. in Bionics Engineering consists of a core curriculum, prescribed courses, liberal arts courses, and several elective courses. Overall, the two-year M.Sc. grants 120 ECTS (CFU, in Italian). Further, the M.Sc. offers two different curricula to be chosen by the student at the end of the first year:

  • the neural engineering curriculum is focused on neuro-instrumentation, neural interfaces, neural signal acquisition and processing, neural networks, bioinspired sensing systems and design of robots mimicking social behaviors;
  • the biorobotics curriculum is focused on the development of humanoid and animaloid robot models, wearable robots, bionic implantable organs, artificial upper and lower limbs, robots and platforms for diagnosis, surgery and rehabilitation, computational biomechanics, micro/nano-robots and biomaterials.


1st year courses




Biomechanics of human motion:

The objectives of this course are to provide an introduction to the biomechanics of the human movements and then to understand the main role underlying the control of spatial multiple degree-of-freedom human motion. These objectives will be reached by means of both theoretical lessons and practical activities in a lab of human movement analysis.


v.monaco @ ( subject=%5BBionicsEngineering%5D%20Contact%20Form) Vito Monaco  (SSSA)


c.stefanini @ ( subject=%5BBionicsEngineering%5D%20Contact%20Form) Cesare Stefanini  (SSSA)


Statistical signal processing:

The course will cover statistical signal processing methods, with application to bioengineering field. The students will become familiar with basic concepts of discrete representation of deterministic and random continuous-time signals, discrete-time random signal analysis, deterministic and random parameter estimation. Various estimation methods will be introduced and compared, such as the method of moments, the maximum likelihood and the linear and non-linear least squares methods. An introduction to Bayesian framework for random parameters and random signals estimation will be provided, with particular emphasis to the problem of linear smoothing, filtering, and prediction. Parametric auto-regressive moving average (ARMA) modeling and identification of discrete-time random signals will be also addressed. Advanced topics in parametric and non-parametric (adaptive and non-adaptive) methods for spectral estimation will be introduced, as well as some basic concepts of time-frequency analysis.


fulvio.gini @ ( subject=%5BBionicsEngineering%5D%20Contact%20Form) Fulvio Gini  (UNIPI)


Bioinspired computational methods

  • Neural  and fuzzy computation
  • Biological Data Mining

The course aims to introduce the main concepts and techniques used in bioinspired computational methods. The course is divided in two modules “Neural and fuzzy computation” and “Business intelligence”. The first module intends to offer students the opportunity to learn the basic concepts and models of computational intelligence, to have a thorough understanding of the associated computational techniques, such as artificial neural networks, fuzzy systems and genetic algorithms, and to know how to apply them to a wide variety of application areas. The second module will focus on the basic aspects of biological data mining: data pre-processing, frequent pattern mining, classification, prediction, clustering and outlier detection.


beatrice.lazzerini @ ( subject=%5BBionicsEngineering%5D%20Contact%20Form) Beatrice Lazzerini  (UNIPI)


f.marcelloni @ ( subject=%5BBionicsEngineering%5D%20Contact%20Form) Francesco Marcelloni  (UNIPI)


Applied brain science

  • Behavioural and cognitive neuroscience
  • Computational neuroscience

This course is divided in two modules “Behavioral and cognitive Neuroscience” and “Computational neuroscience”.

In the class “Behavioral and cognitive neuroscience” the student will learn the following topics: the neurobiological correlates of human behavior and cognition; genetic factors that affect behaviour; brain mechanisms that modulate social behaviour such as emotion and aggression; the neural bases of free will; abnormal expressions of aggressive behaviour;the mental representation of the external world; the functional neuroanatomy of perception; mental representation in the absence of visual experience; pharmacological and non-pharmacological modulation of brain activity; brain enhancement; the in vivo examination of the cerebral correlates of mental function in humans; decoding neural activity: implications for the development of brain-computer interfaces.
The objectives of “Computational neuroscience” class include architectures and learning methods for dynamical/recurrent neural networks and their properties analysis, bio-inspired neural modelling, spiking neural networks, the role of synaptic delays in a computational brain, the role of astrocytes in a computational brain, neuron-astrocyte networks, the role of computational neuroscience in robotics applications.


pietro.pietrini @ ( subject=%5BBionicsEngineering%5D%20Contact%20Form) Pietro Pietrini  (UNIPI)


Materials and instrumentation for bionics engineering

  • Instrumentation and measurement for bionic systems
  • Soft and smart materials

The course “Materials and instrumentation for bionics engineering” is composed of two modules: “Instrumentation and measurement for bionic systems” and “Soft and smart materials”.
Instrumentation and measurement for bionic systems introduces to the methods and technologies involved in the development of equipment for measuring physical and electrical variables during monitoring and control of bionic systems. The students will be exposed to a system-oriented approach to the theory and practice of bionic measurement systems, cutting across several disciplines, including electronics, systems theory, digital signal processing, statistics and artificial intelligence.
Soft and smart materials aims at providing an advanced knowledge on novel soft and smart materials for bionics. Different technologies will be analysed from the basic principles to their exploitation as smart sensors or actuators. The course will enable the student to implement a comparative analysis for the choice of the most suitable technologies for specific engineering problems. The student will be asked to use advanced design principles and tools (like CAD and FEM) as well as to carry out hands-on lab activities.


angelo.sabatini @ ( subject=%5BBionicsEngineering%5D%20Contact%20Form) Angelo Maria Sabatini  (SSSA)


m.cianchetti @ ( subject=%5BBionicsEngineering%5D%20Contact%20Form) Matteo Cianchetti  (SSSA)


Elective courses (12 ECTS)

Economic assessment of medical technologies and robotics for healthcare:

The course will provide the rationale and the technical tools for assessing the economic, social, usability, and acceptability dimensions of a new medical technology. The methodologies gained will enable students to assess a new medical technology both during the R&D process and in the pre-marketing phase, increasing the probability of its successful transfer and adoption in the market. A special focus will be devoted to robotics for healthcare.


g.turchetti @ ( subject=%5BBionicsEngineering%5D%20Contact%20Form) Giuseppe Turchetti  (SSSA)


Electronics for bionics engineering:

The student who successfully completes the course will be able to demonstrate a solid knowledge of the main issues related to the design of sensor based electronic systems for bionics engineering.  He or she will acquire the ability to master trade-offs to map sensor signal processing (sensor data acquisition, conditioning and data fusion) into mixed-signal microelectronics architectures according to main performance metrics (area, speed, power consumption, flexibility, cost and time-to-market). He or she will have the opportunity to practically experience the overall design flow from specification to rapid prototyping for relevant sensor conditioning electronics by exploiting state-of-the-art computer aided design tools and FPGA technologies.


luca.fanucci @ ( subject=%5BBionicsEngineering%5D%20Contact%20Form) Luca Fanucci  (UNIPI)


Principles of bionics engineering:

The course will introduce attendants to biological methods and systems found in nature which can be used as source of inspiration to study and design advanced engineering systems, technologies and algorithms. Examples will include: human and animal locomotion, biomechanics, sensorimotor control hypotheses and systems. The course will devote special attention to biomechatronic and biorobotic components and systems.



paolo.dario @ ( subject=%5BBionicsEngineering%5D%20Contact%20Form) Paolo Dario  (SSSA)


Neuromorphic engineering:

The course will explore computational and physical models that emulate the neural dynamics of biological neurons of peripheral and central nervous system. A particular focus will be dedicated to real-time implementation of spiking artefacts that could be integrated in neurophysiological studies and in closed loop hybrid-bionic systems to restore missing sensorimotor functions.


c.oddo @ ( subject=%5BBionicsEngineering%5D%20Contact%20Form) Calogero Maria Oddo  (SSSA)

a.mazzoni @ ( subject=%5BBionicsEngineering%5D%20Contact%20Form) Alberto Mazzoni  (SSSA)




2nd year courses

Curriculum Neural Engineering (42 ECTS)




Social robotics and affective computing

  • Social robotics
  • Affective computing

The course is composed of two modules “Social robotics” and “Affective computing”
Social robotics is a fairly recent branch of robotics; it addresses the need for robots to correctly interpret people’s action and respond appropriately. A cross point of several disciplines, such us psychology, engineering, sociology, social robotics development will be addressed in this course, with arguments mostly based on engineering reasoning and design.
The course of Affective computing aims at showing how computational technology can be used to understand and interpret human emotions. Specifically, modelling of human emotional expression will be addressed, including software and hardware solutions to acquire, communicate, and express affective information. Understanding how emotions can be experienced can be also helpful to quantify correlated patterns of central and autonomic nervous activity in order to investigate on mood and consciousness disorders.


mazzei @ (subject=%5BBionicsEngineering%5D%20Contact%20Form) Daniele Mazzei  (UNIPI)


e.scilingo @ ( subject=%5BBionicsEngineering%5D%20Contact%20Form) Enzo Pasquale Scilingo  (UNIPI)


Neural Prostheses

  • Neural interfaces and bioelectronic medicine
  • Neural tissue engineering

The course on “Neural prostheses” is composed of two modules: “Neural interfaces and bioelectronic medicine” and “Neural tissue engineering”.
During the course on “Neural interfaces and bioelectronic medicine” the students will acquire the basic principles underlying the design and development of implantable neural interfaces for different parts of the nervous system. They will also develop a broad view on existing neuroprosthetic systems to restore motor functions and on novel solutions based on the stimulation of the autonomic nervous system, and will be able to identify current limitations and challenges for future applications. Finally, the students will learn the conceptual and practical bases for the development of a novel neuroprosthesis (group project).
During the course on “Neural tissue engineering” the students will acquire the strategies to develop grafts and scaffolds that can be implanted to promote nerve regeneration and to repair damage caused to nerves of both the central nervous system and peripheral nervous system by an injury and to eliminate inflammation and fibrosis
upon implantation. Specifically, the technological processes and the materials necessary to realise these grafts and also their interaction with physiological neural tissue.


s.micera @ ( subject=%5BBionicsEngineering%5D%20Contact%20Form) Silvestro Micera  (SSSA)


g.vozzi @ ( subject=%5BBionicsEngineering%5D%20Contact%20Form) Giovanni Vozzi  (UNIPI)


Bionic senses:

The course “Bionic senses” refers to engineering artificial sensing and perceptual systems through biological principles to implement neuroprostheses to restore lost functions, for human augmentation and bioinspired perceptional machines. The basis of needed methodology and technology will be given tutorially.



d.derossi @ ( subject=%5BBionicsEngineering%5D%20Contact%20Form) Danilo De Rossi  (UNIPI)


Integrative cerebral function and image processing

  • Integrative cerebral function
  • Advanced image processing

The course is divided in two modules:
Integrative cerebral functions – All cognitive and emotional functions are the by-product of the activity of anatomo-functional distributed and, at the same time, integrated networks. The didactic module entitled "Integrative cerebral functions" will address the following main topics: 1) Node and rich-clubs in the human connectome; 2) Sleep, mentation and dreaming; 3) Biological bases of consciousness; 4) Theory of mind and mirror neuron system; 4) Empathy in the emotional context; 5) Stress in the context of body and mind integration
Advanced image processing - This module will cover advanced image processing methods that can be applied to biomedical images of the brain. In particular, the methods used to study structural and functional connectivity, as well as brain metabolism, will be deeply covered. The students will be trained to process images acquired using different neuroimaging techniques, as those based on MRI, PET and NIRS. The course will also introduce the main approaches for the integration of biomedical images and electrophysiological recordings.


gemignan @ ( subject=%5BBionicsEngineering%5D%20Contact%20Form) Angelo Gemignani  (UNIPI)


nicola.vanello @ ( subject=%5BBionicsEngineering%5D%20Contact%20Form) Nicola Vanello  (UNIPI)




Curriculum Biorobotics (42 ECTS)




Human and animal models in biorobotics:

The course focuses on bioinspired robotics and biorobotic platforms for neuroscience and biology. The course provides the knowledge about the models of the human brain, of human intelligence, of muscle-skeletal systems, and of perceptual systems that are relevant in biorobotics. The students will learn principles of bioinspiration and biomimetics in robotics and the design methods and the technical tools for implementing such brain models and other animal models in robots. The students will have the opportunity to challenge themselves in their own design of robots inspired to functional mechanisms of human beings and other animals. Where appropriate, hands-on activities and student projects will be included in the course.



c.laschi @ ( subject=%5BBionicsEngineering%5D%20Contact%20Form) Cecilia Laschi  (SSSA)


Prosthetics and rehabilitation robotics

  • Artificial limbs
  • Robotic exoskeletons

The course is composed of two modules: Artificial limbs and Robotic exoskeletons. The overall goal is to introduce students to the main challenges to design wearable powered robots for movement assistance, rehabilitation, augmentation and/or functional replacement. Along with the analyses of the main components involved in the development of an effective human-robot interaction, students will be engaged in laboratory and hands-on activities with working devices. In particular:
Within the module “Artificial limbs” students will be introduced to and will experiment the architecture and function of the microcontroller.
Within the module “Robotic exoskeletons” students will learn how to conceive, rapid-prototype and test multi-layered control architectures running on real-time targets endowed with FPGA processors.

6+6 @ ( subject=%5BBionicsEngineering%5D%20Contact%20Form) Christian Cipriani  (SSSA)


n.vitiello @ ( subject=%5BBionicsEngineering%5D%20Contact%20Form) Nicola Vitiello  (SSSA)


Robotics for surgery and targeted therapy

  • Robotics for minimally invasive therapy
  • Miniaturized therapeutic and regenerative systems

The course “Robotics for surgery and targeted therapy” is composed by two modules: “Robotics for minimally invasive therapy” and “Miniaturized therapeutic and regenerative systems”.
The course of “Robotics for minimally invasive therapy” aims to provide students with methodology and guidelines to understand contribution and to exploit potentials of robotic technologies for minimally invasive therapy, diagnosis and surgery. The course will introduce different solutions for targeted therapies both minimally invasive and no invasive, e.g. which exploit external generators of therapeutic actions. At the end of the course the student will be able to identify the most appropriated targeting/therapeutic solutions for the different human body districts, at different scales, and for different pathologies.
The course “Miniaturized therapeutic and regenerative systems” aims at providing students with the rationale, the methods and the most recent research advancements on milli, micro and nanosystems for achieving safe and effective targeted therapies. Bioengineering solutions for regenerative
medicine, alternative to or synergic with traditional medical/surgical procedure, will be also highlighted. Where appropriate, hands-on activities will be included in the course, especially concerning micro/nano-fabrication and characterization techniques, biomaterial synthesis and functionalization and cell cultures.


a.menciassi @ ( subject=%5BBionicsEngineering%5D%20Contact%20Form) Arianna Menciassi  (SSSA)


l.ricotti @ ( subject=%5BBionicsEngineering%5D%20Contact%20Form) Leonardo Ricotti  (SSSA)


Robotics for assisted living

  • Robot companions for assisted living
  • Cloud robotics

The course “Robotics for assisted living” is composed by two modules: “Robot companions for assisted living” and “Cloud robotics”.
The aim of the module “Robot companions for assisted living” is to present the main advanced technologies and methodologies to build robot companions for assisting people in daily life activities. It will focus on systems and services adequate to the end-users’ needs, adaptive to the environment and end-users’s behaviour, embedded not invasively in the environments, easily wearable by end-users, pro-active with Ambient Intelligence (AmI) capabilities and highly usable with advanced human machine interfaces. The main technological contents include wireless sensor network, wearable technology, service and cloud robotics.
The module “Cloud robotics” will focus on the main basis for developing intelligent systems for Robot Companions applications. It will revolve around the analysis of middleware solutions for integration of smart environments and service robotics and the implementation of Wireless Sensor Network with the Microcontroller STM32W with ZigBee stack. Additionally it will introduce the main concepts of cloud computing and propose how to develop Cloud robotics applications.


s.mazzoleni @ ( subject=%5BBionicsEngineering%5D%20Contact%20Form) Stefano Mazzoleni  (SSSA)


f.cavallo @ ( subject=%5BBionicsEngineering%5D%20Contact%20Form) Filippo Cavallo  (SSSA)



Common (18 ECTS)




Lab training

This activity will consist of 75 h of Lab training that the student will perform in dedicated facilities and laboratories, with the aim to increase his/her experience in laboratory practice.



Educational and orientation Internships

Final examination

The final examination involves the preparation of a report on a research activity, and in its presentation and discussion.