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Artificial Intelligence in Rehabilitation and Healthcare
Last Updated: 2026-06-03 00:07:38
Abstract
In this course, students will learn about AI with a focus on building and evaluating machine learning models applied in patient data and personalized rehabilitation. Beyond performance we will emphasize fairness of AI in healthcare through collaborative projects, directly offered from leading healthcare companies with real-world rehabilitation and healthcare challenges.
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 inte-gration of advanced technology in the field of rehabilitation. The class consists of both theoret-ical and practical components. In the theoretical part, students are introduced to the funda-mental concepts of artificial intelligence, including regressions and classification in machine learning, deep neural networks, and large language models. They will explore the applications of AI in rehabilitation and healthcare, including patient monitoring, personalized treatment plans, and predictive analytics. In the practical component, each student will work with one of the clinics or technology compa-nies to identify real-world problems and gain hands-on experience in developing AI in rehabili-tation and healthcare. The practical work will be done in the course room with student assis-tants and experts from the companies. They will use Python as main language on their own laptops with ready to use Jupiter notebooks that could have access to our lab’s server if need-ed 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 out-comes. 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 healthcare problems partners: Schweizer Paraplegiker-Stiftung, Lake Lucerne Institute, Balgrist University Hospital, Ortho-Team Luzern, among others.
General Information
- Language
- English
- Levels
- DR , MSC
- Frequency
- Yearly recurring
Examination
- Type
- graded semester performance
Registration & Places
- Max Places
- 60
Course Components
| Type | Title | Time & Place | Hours |
|---|---|---|---|
| lecture with exercise | Artificial Intelligence in Rehabilitation and Healthcare | No time listed | 3 h weekly |
| independent project | Artificial Intelligence in Rehabilitation and Healthcare | No time listed | 2 h weekly |
Offered In
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Doctorate Health Sciences and Technology (More Information at: )
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Rehabilitation Technology (Students majoring in Rehabilitation and Inclusion: At least 3 CP of the courses in this focus area must be selected.)
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