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ROBOTICS FOR E-HEALTH

International Teaching ROBOTICS FOR E-HEALTH

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0623200006
DEPARTMENT OF INFORMATION AND ELECTRICAL ENGINEERING AND APPLIED MATHEMATICS
EQF7
INFORMATION ENGINEERING FOR DIGITAL MEDICINE
2023/2024



OBBLIGATORIO
YEAR OF COURSE 1
YEAR OF DIDACTIC SYSTEM 2022
SPRING SEMESTER
CFUHOURSACTIVITY
1ROBOTICS FOR E-HEALTH
216LESSONS
2ROBOTICS FOR E-HEALTH
216LESSONS
216EXERCISES
ANTONIO GRECO1 T Curriculum
ENRICO FERRENTINO2 Curriculum
Objectives
The module will provide the student with the basic tools to understand the structural and operative characteristics of robots in medical applications and their programming.

Knowledge and understanding
Characteristics of robots used in medical and robotics applications, including robotic surgery and the use of robots for assistive and social technologies. Safety issues of robotic systems in the medical field. Software frameworks and environments for the collection of data provided by the robot and for the programming of robots.

Applying knowledge and understanding
Programming robotic systems in the medical field for physical and social assistance and creating applications capable of reading the data provided by the robot and analyzing them for diagnostic and safety purposes.
Prerequisites
THERE ARE NO PROPAEDEUTIC COURSES.

FOR THE SUCCESSFUL ACHIEVEMENT OF THE COURSE GOALS, KNOWLEDGE ON CONTROL AND COMPUTER TECHNOLOGIES IS REQUIRED.
Contents
Didactic unit 1 - ROBOTICS FUNDAMENTALS
(LECTURE/PRACTICE/LABORATORY HOURS 7/0/0)
- 1 (2 HOURS Lecture): Introduction to robotics. Medical robots applications and characteristics: safety, sterility and surgical theater constraints.
- 2 (3 HOURS Lecture): Robot kinematics and dynamics fundamentals: definitions, typical serial and parallel structures; forward, inverse and differential kinematics; singularities; kinematic redundancy; dynamic model.
- 3 (2 HOURS Lecture): Robot control fundamentals: joint space and task space control; typical control techniques.
KNOWLEDGE AND UNDERSTANDING: Knowledge of peculiarities of medical robots. Understanding of robotics fundamentals as regards their kinematic, dynamic and control features.
APPLYING KNOWLEDGE AND UNDERSTANDING: Understand and analyze the technical documentation of commercial medical robots, as regards their functional characteristics.

Didactic unit 2 - WEREABLE ROBOTS
(LECTURE/PRACTICE/LABORATORY HOURS 10/0/0)
- 1 (1 HOUR Lecture): Introduction to wearable robots: definitions, classification, physical and cognitive interaction, biologically-inspired designs.
- 2 (4 HOURS Lecture): Robotic prostheses: classification; perception and actuation technologies; control techniques and human-robot interfaces (EMG, ENG, EEC).
- 3 (1 HOUR Lecture): Introductin to exoskeletons: classification; kinematic compatibility.
- 4 (2 HOURS Lecture): Upper-limb exoskeletons: typical deseases and therapies; interaction control fundamentals; rehabilitation exoskeletons control techniques.
- 5 (2 HOURS Lecture): Lower-limb exoskeletons: lower limb kinematics; typical deseases and therapies; gait support multi-layer control techniques.
KNOWLEDGE AND UNDERSTANDING: Knowledge of the main human intention and action estimation techniques and interfaces and control for wereable robots. Understanding of data generated and required by wereable robots and knowledge of their type.
APPLYING KNOWLEDGE AND UNDERSTANDING: Select suitable wereable robots compatible with given therapeutic indications and usage constraints.

Didactic unit 3 - SURGICAL ROBOTS
(LECTURE/PRACTICE/LABORATORY HOURS 9/0/0)
- 1 (2 HOURS Lecture): Surgical robots classification: passive, active, interactive and tele-operated. Examples of typical deseases and treatments.
- 2 (2 HOURS Lecture): Kinematic characterstics of surgical robots: serial robots; parallel robots; kinematic structures for implementing the remote center of motion (RCM); Grubler's formula.
- 3 (3 HOURS Lecture): DaVinci robot: master console, slave console, safety characteristics, interface with the hospital management system.
- 4 (2 HOURS Lecture): Surgical robots control: interactive control; tele-operated control; guidance and forbidden region virtual fixtures.
KNOWLEDGE AND UNDERSTANDING: Knowledge of the main interfacing and control techniques for surgical robots. Knowledge of daVinci's technical features. Understanding of data generated and required by surgical robots and knowledge of their type.
APPLYING KNOWLEDGE AND UNDERSTANDING: Select suitable surgical robots compatible with given therapeutic indications and usage constraints. Understand and analyze daVinci's documentation, as regards its functional and technical features.

Didactic unit 4 - MEDICAL MICROROBOTS AND NANOROBOTS
(LECTURE/PRACTICE/LABORATORY HOURS 3/0/0)
- 1 (2 HOURS Lecture): Medical microrobots: typical deseases and treatments; power, locomotion and localization.
- 2 (1 HOUR Lecture): Medical nanorobots: typical deseases and treatments; benefits and challenges.
KNOWLEDGE AND UNDERSTANDING: Knowledge of the main medical microrobot and nanorobot control techniques. Understanding of data generated and required by medical microrobots and knowledge of their type.
APPLYING KNOWLEDGE AND UNDERSTANDING: Select medical microrobots compatible with given therapeutic indications and usage constraints.

Didactic unit 5 - MEDICAL ROBOTS REGULATIONS
(LECTURE/PRACTICE/LABORATORY HOURS 3/0/0)
- 1 (3 HOURS Lecture): Analysis of EU MDR 2017/745. Relationship with ISO 13485. CE certification process and post-market surveillance.
KNOWLEDGE AND UNDERSTANDING: Knowledge of the medical robots regulatory framework, and understanding of the main concepts of quality assurance. Knowledge of the CE certification process for medical robots.
APPLYING KNOWLEDGE AND UNDERSTANDING: Understand and analyze non-functional requirements for medical robots and supervise quality assurance processes.

Didactic unit 6 - SOCIALLY ASSISTIVE ROBOTS
(LECTURE/PRACTICE/LABORATORY HOURS 6/5/5)
- 1 (2 HOURS Lecture): Introduction to Socially Assistive Robotics: definitions, care robots, hospital robots, robot for autism treatment, tasks of a socially assistive robot.
- 2 (2 HOURS Lecture + 1 HOUR Practice): Introduction to assistive social robot programming (NAO): Robot Operating System (ROS) and NAOQi.
- 3 (1 HOUR Lecture + 2 HOURS Practice): Voice analysis and sound recognition: theory and practice with the robot.
- 4 (1 HOUR Lecture + 2 HOURS Practice): Object recognition and gaze estimation: theory and practice with the robot.
- 5 (2 HOURS Laboratory): Assignment and discussion of the project: a social robot for autism treatment.
- 6 (3 HOURS Laboratory): Realization of the final project with the guide of the lecturer.
KNOWLEDGE AND UNDERSTANDING: Knowledge of the concept of socially assistive robotics, of the principles for programming robots with ROS and NAOQi and of the fundamentals on audio and video analysis for the realization of a socially assistive robot.
APPLYING KNOWLEDGE AND UNDERSTANDING: Capability to realize a socially assistive robot for autism treatment, by using machine learning algorithms for audio and video analysis

TOTAL LECTURE/PRACTICE/LABORATORY HOURS 38/5/5
Teaching Methods
THE COURSE ARTICULATES INTO IN-CLASS LECTURES (38 HOURS), PRACTICE LECTURES (5 HOURS) AND LABORATORY ACTIVITIES ON SIMULATED AND PHISICAL ROBOTS (5 HOURS). IN-CLASS LECTURES WILL ALLOW THE STUDENT TO GAIN KNOWLEDGE ON THE ROBOTS USED IN THE MEDICAL SECTOR, THEIR APPLICATIONS, THEIR SAFETY ISSUES, SOFTWARE FRAMEWORK AND ENVIRONMENTS FOR DATA GATHERING ROBOT PROGRAMMING. PRACTICE LECTURES AND LABORATORY ACTIVITIES WILL ALLOW THE STUDENT TO DEVELOP THE ABILITIES TO APPLY THE KNOWLEDGE ACQUIRED IN THE THEORETICAL LECTURES TO THE PROGRAMMING OF ROBOTS IN THE MEDICAL SECTOR AND IN THE DEVELOPMENT OF APPLICATIONS TO GATHER DATA FROM SUCH SYSTEMS AND ANALYZE THEM TO SAFETY AND DIAGNOSTIC PURPOSES. THE COURSE ALSO FORESEES THE DEVELOPMENT OF A GROUP PROJECT FINALIZED TO THE ACQUISITION OF THE SKILLS NECESSARY TO PROGRAM A SOCIAL ASSISTIVE ROBOT, EMPLOYING MACHINE LEARNING ALGORITHMS.
THE COURSE ATTENDANCE IS MANDATORY AND THE ACCESS TO THE EXAM REQUIRES TO ATTEND AT LEAST 70% OF IN-CLASS, PRACTICE AND LABORATORY ACTIVITIES. THE ATTENDANCE WILL BE VERIFIED THROUGH THE PRESENCE DETECTION SYSTEM.
Verification of learning
THE STUDENTS ARE ASSESSED THROUGH THE DEVELOPMENT OF A PROJECT, FOLLOWED BY AN ORAL INTERVIEW. THE PROJECT AIMS AT PROGRAMMING AN ASSISTIVE SOCIAL ROBOT FOR AUTISM TREATMENT, BY EXPLOITING THE ROS FRAMEWORK AND MACHINE LEARNING ALGORITHMS FOR AUDIO AND VIDEO ANALYSIS. ALTHOUGH TRANSVERSAL TO ALL DIDACTIC UNITS, THE REPORT ANALYSIS ALLOWS TO VERIFY THE APPLIED KNOWLEDGE AND UNDERSTANDING SKILLS, AS ADDRESSED BY THE COURSE OBJECTIVES, IN PARTICULAR REGARDING DIDACTIC UNIT 6. THE ORAL INTERVIEW, LASTING 15-20 MINUTES FOR EACH STUDENT, FORESEES THE REPORT PRESENTATION TO THE AIM OF VERIFYING THE INDIVIDUAL PROJECT CONTRIBUTION, AS WELL AS THE ACQUISITION OF THEORETICAL KNOWLEDGE, IN PARTICULAR CONCERNING DIDACTIC UNITS 1-5. THE INTERVIEW QUESTIONS MIGHT INCLUDE THE RESOLUTION OF SIMPLIFIED USE CASES, SO THAT THE STUDENT CAN DEMONSTRATE THE ACQUISITION OF THE METHODOLOGIES PRESENTED DURING THE COURSE AND THE CRITICAL ABILITIES NECESSARY TO PROGRAM A ROBOT IN THE MEDICAL SECTOR. THE INTERVIEW SCORE DEPENDS ON THE ABILITY TO DEFEND THE PROJECTUAL CHOICES, TO EFFECTIVELY PRESENT THE CONTENTS OF THE COURSE AND TO DISCUSS THE ADDRESSED TOPICS.
Texts
B. SICILIANO, L. SCIAVICCO, L. VILLANI, G. ORIOLO, "ROBOTICS - MODELLING, PLANNING AND CONTROL", SPRINGER, LONDON, 2009, ISBN 978-1-84628-642-1

J. TROCCAZ, "MEDICAL ROBOTICS", JOHN WILEY & SONS, 2013, ISBN: 9781848213340.


Supplementary teaching material will be available on the university e-learning platform (http://elearning.unisa.it) accessible to students using their own university credentials.
More Information
THE COURSE IS HELD IN ENGLISH.
  BETA VERSION Data source ESSE3