Program Overview

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University Programs

The university offers a range of programs for students, including bachelor's degrees, master's degrees, and integrated bachelor-master degrees.

Bachelor's Degrees

• Bachelor Degree in Informatics Engineering
  • Enrolment: Available places
  • Curriculum: Syllabus, Reassessment, Specializations, Competences, Competences for degree subjects
  • Faculty
  • Bachelor's Thesis
  • Timetables
  • Exams
  • Academic Regulations
• Bachelor Degree in Data Science and Engineering
  • Enrolment: Available places
  • Curriculum: Syllabus, Competences, Competences for degree subjects
  • Faculty
  • Timetables
  • Exams
  • Academic Regulations and organization
• Bachelor Degree in Artificial Intelligence
  • Enrolment: Places lliures
  • Curriculum: Competences, Syllabus, Competences for degree subjects
  • Faculty
  • Timetables
  • Exams
  • Academic regulations
  • Bachelor's thesis
• Bachelor Degree in Bioinformatics
  • Enrolment: Available places
  • Curriculum: Learning Outcomes, Syllabus
  • Faculty
  • Timetables
  • Exams
  • Academic Regulations
• Integrated Bachelor Master Degree
  • Enrolment
  • Curriculum

Master's Degrees

• Master in Informatics Engineering
  • Enrolment: Available places
  • Curriculum: Syllabus, Competences, Competences for degree subjects
  • Faculty
  • Academic Regulations
  • Master's Thesis
  • Timetables
  • Exams
• Master in Informatics Engineering - Industrial Modality
  • Curriculum
• Master in Innovation and Research in Informatics
  • Enrolment: Available places
  • Curriculum: Syllabus, Specializations, Competences, Competences for degree subjects
  • Faculty
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  • Master's Thesis
  • Seminars
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  • Exams
• Master in Artificial Intelligence
  • Enrolment: Available places
  • Curriculum: Syllabus, Competences, Competences for degree subjects
  • Faculty
  • Academic Regulations
  • Master's Thesis
  • Timetables
  • Exams
  • FAQs
• Master in Cybersecurity
• Master in Data Science
  • Enrolment: Available places
  • Curriculum: Syllabus, Competences, Competences for degree subjects
  • Faculty
  • Academic Regulations
  • Timetables
  • Exams
  • Master's Thesis
    • Gender Competency
• Erasmus Mundus Master in Big Data Management and Analytics
  • Timetables
  • Curriculum: Syllabus
  • Exams
• Master in Urban Mobility
  • Curriculum
• EUMaster4HPC
  • Curriculum
• Other Masters
  • Master in Pure and Applied Logic
  • Master in Computational Modelling in Physics, Chemistry and Biochemistry

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Assistive and Health-Care Technologies

Description

Assistive technologies and their incidence on healthcare are addressed and analysed. The main objective of the course is focused on the use of appropriate technologies depending on people's needs and their environment. Emphasis will be on the improvement in the quality of life of affected people.

Credits

4.5

Types

Elective

Requirements

This subject has no requirements.

Department

EEL; ESAII

Teachers

Person in charge

• Andreu Catala Mallofre

Weekly hours

• Theory: 1
• Problems: 0
• Laboratory: 1.3
• Guided learning: 0.4
• Autonomous learning: 5

Competences

Generic Technical Competences

Generic

• CG1 - Capability to plan, design and implement products, processes, services and facilities in all areas of Artificial Intelligence.
• CG3 - Capacity for modeling, calculation, simulation, development and implementation in technology and company engineering centers, particularly in research, development and innovation in all areas related to Artificial Intelligence.

Technical Competences of each Specialization

Academic

• CEA10 - Capability to understand advanced techniques of Human-Computer Interaction, and to know how to design, implement and apply these techniques in the development of intelligent applications, services or systems.
• CEA12 - Capability to understand the advanced techniques of Knowledge Engineering, Machine Learning and Decision Support Systems, and to know how to design, implement and apply these techniques in the development of intelligent applications, services or systems.

Professional

• CEP3 - Capacity for applying Artificial Intelligence techniques in technological and industrial environments to improve quality and productivity.
• CEP4 - Capability to design, write and report about computer science projects in the specific area of Artificial Intelligence.
• CEP6 - Capability to assimilate and integrate the changing economic, social and technological environment to the objectives and procedures of informatic work in intelligent systems.
• CEP7 - Capability to respect the legal rules and deontology in professional practice.

Transversal Competences

Teamwork

• CT3 - Ability to work as a member of an interdisciplinary team, as a normal member or performing direction tasks, in order to develop projects with pragmatism and sense of responsibility, making commitments taking into account the available resources.

Appropriate attitude towards work

• CT5 - Capability to be motivated for professional development, to meet new challenges and for continuous improvement. Capability to work in situations with lack of information.

Reasoning

• CT6 - Capability to evaluate and analyze on a reasoned and critical way about situations, projects, proposals, reports and scientific-technical surveys. Capability to argue the reasons that explain or justify such situations, proposals, etc..

Analysis and synthesis

• CT7 - Capability to analyze and solve complex technical problems.

Objectives

1. A specific objective will be the specification and analysis of a health service based on technology use (functionality, patient/user perspective, requirements...). Related competences: CT3, CT5, CT7, CEA10, CEP3, CEP4, CEP6, CEP7, CG1, CG3,
2. Acquiring correct skills on Assistive technologies. Related competences: CT3, CT5, CT6, CEA12,

Contents

1. Assistive technologies. State of the Art. Challenges and perspectives. Overview on the state of the art, depending on the specific condition and domain.
2. Healthcare domain. Technology based services. Specific healthcare domain and the possible corresponding technology based services will be discussed.
3. Ambient Assisted Living approach. Principles of the AAL related technologies applied to the healthcare domain.
4. Ethical and usability aspects. Quality of life. Aspects related with ethics and user-based concepts will be treated. Improvement of the quality of life of the patients is in the focus.

Activities

Assistive technologies. Challenges and perspectives.

• Objectives: 2
• Theory: 4h
• Problems: 0h
• Laboratory: 4h
• Guided learning: 1h
• Autonomous learning: 13.8h

Healthcare domain. Technology based services.

• Objectives: 2
• Theory: 3h
• Problems: 0h
• Laboratory: 4h
• Guided learning: 1h
• Autonomous learning: 13.8h

Ambient Assisted Living approach.

• Objectives: 1 2
• Theory: 3h
• Problems: 0h
• Laboratory: 4h
• Guided learning: 1h
• Autonomous learning: 13.8h

Ethical and usability aspects. Quality of life.

• Objectives: 1 2
• Theory: 3h
• Problems: 0h
• Laboratory: 6.8h
• Guided learning: 1h
• Autonomous learning: 13.8h

Mid-term evaluation.

• Week: 8
• Theory: 0h
• Problems: 0h
• Laboratory: 0h
• Guided learning: 2h
• Autonomous learning: 10h

Final presentation.

• Week: 14
• Theory: 0h
• Problems: 0h
• Laboratory: 0h
• Guided learning: 0h
• Autonomous learning: 10h

Teaching methodology

Methodology will be mainly based on two different activities: theory sessions and practical sessions. Both will be developed with the active participation of the students.

The scheme for the theory sessions will be:

• Plenary conferences given by the teacher.
• Self-study sessions done by the students on a related topic.
• Students presentations about the conclusions on the topic (presentations will be part of the evaluation activities).

Practical aspect will follow a Project Based Learning approach:

1. The student should do a literature review of the field, detecting the most important research groups, patents and projects in his area of interest.
2. Design of a real project based on a use case.
3. Detailed analysis of the most convenient architecture and algorithmia.
4. Technologies and innovative aspects of the proposed solution. A presentation of the final project will be part of the evaluation process.

Evaluation methodology

Evaluation will be according to the implemented methodology for the course. The student will get a FINAL MARK mainly based on a continuous evaluation scheme. A personal Final Exam based on theory aspects will be done, with a specific weight in the Final Mark.

Final Mark = 0.4 PROJECT evolution mark + 0.3 PROJECT final assessment + 0.15 Presentation and reporting of theory sessions + 0.15 Final Exam mark.

Bibliography

Basic:

• Smart technologies in healthcare - Bouchard, B. (ed.), CRC Press, Taylor & Francis Group, 2017. ISBN:
• Connected health: improving care, safety, and efficiency with wearables and IoT - Krohn, R.; Metcalf, D.; Salber, P.R, Taylor & Francis, 2017. ISBN: