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376-1229-00L 3 Credits DR , MSC D-HEST
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Artificial Intelligence in Rehabilitation and Healthcare

Lecturers & Examiners: Dr. Christopher Easthope Awai, Dr. Diego Felipe Paez Granados
VVZ CR n/a

Last Updated: 2026-06-01 11:30:56

Abstract

Students will delve into AI fundamentals (e.g., regression, classification, and deep neural networks) and their role in patient monitoring & personalised rehab.Collaborative projects offered by MedTech companies provide hands-on experience in developing and evaluating AI-driven solutions. This course will emphasise AI's explainability and ethical dimensions, fostering its critical analysis.

Objective

1. Evaluate the effectiveness of AI tools and algorithms in the context of rehabilitation and healthcare, and suggest modifications or improvements as needed. 2. Understand the ethical and legal considerations surrounding the use of AI in rehabilitation and healthcare and apply this knowledge to ensure patient privacy and data security. 3. Identify potential limitations and risks of using AI in rehabilitation and healthcare and propose strategies to mitigate these challenges. 4. Collaborate effectively with other students on group projects that involve developing and implementing AI-based rehabilitation and healthcare solutions.

Content

In the class "Artificial Intelligence (AI) in Rehabilitation and Healthcare", we will explore the usage of data-driven analysis to solve problems in healthcare. The lecture consists of both theoretical and practical components. In the theoretical part, students are presented to the fundamental concepts of AI, including feature selection, model selection in machine learning, and deep neural networks. They will explore applications of learnt concepts to problems of healthcare: including patient monitoring, personalised treatment plans, and predictive analytics. In the practical component, each student will work with one of the clinics or MedTech companies to identify real-world problems and gain hands-on experience in developing AI in rehabilitation and healthcare. The practical work will be done in the lecture room guided with student assistants. Python is the main language on their own laptops with ready-to-use Jupiter notebooks that could have access to our lab’s server if needed for computational resources. They will directly start using programming languages and tools to build models, analyze data, and create algorithms that can be used to improve patient outcomes. Throughout the class, students are encouraged to think critically about the ethical implications of using AI in rehabilitation. They examine the potential benefits and risks of using advanced technology in patient care and explore ways to mitigate potential negative outcomes. Practical problems partners: Schweizer Paraplegiker-Zentrum, Lake Lucerne Institute, Balgrist University Hospital, Ortho-Team Luzern, SUVA Clinics.

General Information

Language
English
Levels
DR , MSC
Frequency
Yearly recurring

Examination

Type
graded semester performance
Continuous performance assessments:- Lab assignments (pass/fail)- Final project presentations with report and code submissions

Registration & Places

Max Places
60

Course Components

Type Title Time & Place Hours
lecture with exercise Artificial Intelligence in Rehabilitation and Healthcare
  • Thu 14:15-17:00 (NO C 44)
3 h weekly

Offered In