Bionics engineering

Laurea Magistrale

A Milano

6001-7000 €

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Descrizione

  • Tipologia

    Laurea Magistrale

  • Luogo

    Milano

Il Corso di Laurea prevede un percorso per il rilascio di un doppio titolo con la Scuola Superiore di Studi Universitari e di Perfezionamento Sant'Anna.

Bionics engineering is a new frontier of biomedical engineering. Indeed, "bionics" is increasingly used at international level to indicate the research area which integrates the most advanced robotics and bioengineering technologies with life sciences, such as medicine and neuroscience, materials science, etc., with the ultimate goal of inventing and deploying a new generation of biomimetic machines, human-centred healthcare and (more generally) assistive technologies. Although some of them will replace traditional biomedical technologies, bionic solutions will be in general complementary and synergic to state-of-the-art biomedical engineering efforts.
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One of the primary goals of this master degree course is to challenge a selected core of very highly qualified students that, besides acquiring high-level professional skills, will also foster the progress of the research activities in the bionics field. They will be able to close the innovation loop by both translating the knowledge across application scenarios and transferring scientific insights into market opportunities. In the progress of their studies, graduate students of the Master of Science in Bionics Engineering will gather fundamentals of science and technology of biorobotics and neural engineering. They will be also progressively trained to a multi-disciplinary research attitude by means of a fruitful dialogue with scientists from different research fields, such as medicine, biology, neuroscience, as well as with clinicians in the field of rehabilitation and surgery, pioneers of emerging industrials sectors and social scientists on-exhaustive lists of experiences the students will be challenged with, is reported: - Design, development and testing of social robots and smart environments for assisted living, active ageing and wellbeing; - Design,...

Sedi e date

Luogo

Inizio del corso

Milano
Visualizza mappa
Via Santa Tecla, 5

Inizio del corso

Consultare

Profilo del corso

BIONICS ENGINEERING

Corso di laurea magistrale

Descrizione
Piano di studi
Sbocchi professionali
Sbocchi professionali
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In the last years a big number of innovative industries based on micro/nano and bio-technologies, on biomedical engineering and on advanced robotic solutions emerged. These types of companies need novel professional profiles, namely engineers characterized by a strongly interdisciplinary knowledge, a curiosity-driven and problem solving-oriented approach. They must be able to study, analyze and propose practical solutions in all the different areas of bionics engineering, thus allowing the development of highly innovative research-grounded products, leading the market through innovation. The master degree in Bionics Engineering aims to train engineers with a solid background, particularly in the areas of bioengineering, biorobotics and neural engineering, but also with clear and high-level research-oriented skills. Graduates will possess a high quality curriculum that, besides opening opportunities for high-level academic positions, will also attract the direct interest of many innovative companies operating in different high-tech sectors. The multidisciplinary training received by master graduate students in Bionics engineering will allow them to play a driving role in the mentioned industrial realities, especially concerning the design, development and commercialization of bionic devices, neural prosthesis, computer-integrated platforms, aids for the disabled, medical devices, rehabilitation systems and therapeutic micro/nano systems n universities, research centers, hospitals and industries; - designer or production responsible of advanced medical devices and automatized therapeutic systems in bioengineering industries; - designer or production responsible of advanced smart materials for medical and technological applications; - technical and/or commercial product specialist for companies operating in the biorobotics and neural engineering...

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Programma

  • Biomechanics of human motion (6 cfu)

    • 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.

  • 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.

  • Statistical Signal Processing (6 cfu)

    • 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.

  • 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.

  • Materials and instrumentation for bionics engineering (12 cfu)

    • 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.


  • 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.


  • Applied brain science (12 cfu)

    • 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: introduction to cognitive and social neuroscience; introduction to neuronal functioning, brain metabolism and intrinsic brain activity; basic principles of brain imaging methodologies,
      their uses for research and clinical purposes; introduction to the advanced methods for brain imaging analyses; the neurobiological correlates of human cognition and behavior; the mental representation of the external world; the functional neuroanatomy of perception and imagery;
      introduction to consciousness and sleep; introduction to psycholinguistics; emotions and behavior; motor control and action representation, and their implications for the development of brain-computer interfaces.
      The objectives of "Computational neuroscience" class include bio-inspired neural modelling, spiking and reservoir computing neural networks, advanced computational neural models for learning, architectures and learning methods for dynamical/recurrent neural networks for temporal data and the analysis of their properties, the role of computational neuroscience in
      real-world applications (by case studies).

  • 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: introduction to cognitive and social neuroscience; introduction to neuronal functioning, brain metabolism and intrinsic brain activity; basic principles of brain imaging methodologies,
    their uses for research and clinical purposes; introduction to the advanced methods for brain imaging analyses; the neurobiological correlates of human cognition and behavior; the mental representation of the external world; the functional neuroanatomy of perception and imagery;
    introduction to consciousness and sleep; introduction to psycholinguistics; emotions and behavior; motor control and action representation, and their implications for the development of brain-computer interfaces.
    The objectives of "Computational neuroscience" class include bio-inspired neural modelling, spiking and reservoir computing neural networks, advanced computational neural models for learning, architectures and learning methods for dynamical/recurrent neural networks for temporal data and the analysis of their properties, the role of computational neuroscience in
    real-world applications (by case studies).

  • Bioinspired computational methods (12 cfu)

    • 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 “Biological data mining”. 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.

  • 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 “Biological data mining”. 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.

  • 12 cfu a scelta nel gruppo Free choice

    • List of classes that the student chooses freely. These classes will be automatically approved by the board of the Master Degree Course
    • Principles of bionics engineering (6 cfu)

      • The “Principles of Bionics Engineering” course aims to introduce attendants to the vast and interdisciplinary field of bionics and related scientific areas, such as biorobotics and bioengineering. Bionics aims at gathering specific knowledge through the analysis/modeling of living organisms/ecosystems and applies it to the development of newly inspired advanced devices. Bionics also focuses on artificial systems deeply connected to body tissues. The application of bionics principles is nowadays widespread in many engineering sub-fields. During this course, several case studies will be presented that will allow to properly understand the whole loop from scientific insights to engineering innovation. In particular, the course will focus on the key principles of biological locomotion, swarm robotics, artificial organs, morphological computation, energy issues, structural design and fabrication technologies.
    • Economic assessment of medical technologies and robotics for healthcare (6 cfu)

      • 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.
    • Electronics for Bionics Engineering (6 cfu)

      • 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.
    • Neuromorphic engineering (6 cfu)

      • 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.
    • Mechanics of elastic solids and bio-robotic structures (6 cfu)

      • The course will focus on the principles governing the elastic response of solids and of engineering structures (rods, beams, plates, and shells), on how these principles are operative in biological systems, and how they can be exploited in soft robotics applications. Examples will include locomotion and manipulation tasks inspired by invertebrate organisms, and morphological computation principles used for motility by unicellular organisms.

  • List of classes that the student chooses freely. These classes will be automatically approved by the board of the Master Degree Course

  • Principles of bionics engineering (6 cfu)

    • The “Principles of Bionics Engineering” course aims to introduce attendants to the vast and interdisciplinary field of bionics and related scientific areas, such as biorobotics and bioengineering. Bionics aims at gathering specific knowledge through the analysis/modeling of living organisms/ecosystems and applies it to the development of newly inspired advanced devices. Bionics also focuses on artificial systems deeply connected to body tissues. The application of bionics principles is nowadays widespread in many engineering sub-fields. During this course, several case studies will be presented that will allow to properly understand the whole loop from scientific insights to engineering innovation. In particular, the course will focus on the key principles of biological locomotion, swarm robotics, artificial organs, morphological computation, energy issues, structural design and fabrication technologies.

  • The “Principles of Bionics Engineering” course aims to introduce attendants to the vast and interdisciplinary field of bionics and related scientific areas, such as biorobotics and bioengineering. Bionics aims at gathering specific knowledge through the analysis/modeling of living organisms/ecosystems and applies it to the development of newly inspired advanced devices. Bionics also focuses on artificial systems deeply connected to body tissues. The application of bionics principles is nowadays widespread in many engineering sub-fields. During this course, several case studies will be presented that will allow to properly understand the whole loop from scientific insights to engineering innovation. In particular, the course will focus on the key principles of biological locomotion, swarm robotics, artificial organs, morphological computation, energy issues, structural design and fabrication technologies.

  • Economic assessment of medical technologies and robotics for healthcare (6 cfu)

    • 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.

  • 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.

  • Electronics for Bionics Engineering (6 cfu)

    • 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.

  • 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.

  • Neuromorphic engineering (6 cfu)

    • 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.

  • 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.

  • Mechanics of elastic solids and bio-robotic structures (6 cfu)

    • The course will focus on the principles governing the elastic response of solids and of engineering structures (rods, beams, plates, and shells), on how these principles are operative in biological systems, and how they can be exploited in soft robotics applications. Examples will include locomotion and manipulation tasks inspired by invertebrate organisms, and morphological computation principles used for motility by unicellular organisms.
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  • The course will focus on the principles governing the elastic response of solids and of engineering structures (rods, beams, plates, and shells), on how these principles are operative in biological systems, and how they can be exploited in soft robotics applications ield of bionics and related scientific areas, such as biorobotics and bioengineering. Bionics aims at gathering specific...
  • Chiama il centro

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    Bionics engineering

    6001-7000 €