MedTech: Cognitive Processes and AI Technology
|Course offered by:||Prof. Dr. Thomas Spittler|
|Offering University:||TH Deggendorf|
|Subject Area:||Health Care / Health Management|
|Average Workload:||25 Hours||Free of Charge|
|Available from:||04.02.22||Free of Charge|
|Picture Credits: Michelle Uebrück (All rights reserved)|
What can you learn in this course?
Upon completion of this course, participants will be able to:
- ... understand the main characteristics of human-machine interaction and human-centered design
- ... explain the principles of human cognition and information processing
- ... discuss the potentials of AI technologies and understand the functioning of Machine Learning algorithms
- ... comprehend the benefits and risks of modern AI technologies in the context of health care, and more specifically, rehabilitation
- ... elaborate how AI can be used in the context of stroke rehabilitation with exoskeletons
Chapter 1: Human-Machine Interaction
We want to start our course by giving you an insight in modern technologies and the area of human-machine interaction: Which objectives are important when designing and developing technologies that involve the close interaction of humans and machines? You will learn about different theories and models that provide explanations for sociotechnical environments such as health care.
Chapter 2: Cognition
In our second chapter, we will have a look at human cognition - you will learn about how the human brain works and about the different cognitive tasks that it fulfils in our everyday life. We will focus on the aspect of information processing, in particular, and discuss the differences and importance between two different kinds of information processing: Bottom-up- and top-down-Processing. The knowledge about the human brain is not only important for the area of health care - e.g., when analysing the symptoms or consequences of a brain lesion. It also played an important role in creating first models that aimed at describing human cognition on a mathematical level. These models lead us to our next chapter, in which we will focus on Artificial Intelligence.
Chapter 3: Artificial Intelligence (AI) Technologies
Artificial Intelligence is considered one of the most important technological developments of recent years. But what exactly are the characteristics of AI Technologies? And what do you need to keep in mind when using AI applications in the context of health care? In our third chapter, we will answer these questions by giving you an overview of important concepts, such as Artificial Intelligence in general, Machine Learning and Deep Learning. We will also discuss the benefits and risks of using these technologies.
Chapter 4: AI in Rehabilitation
In Chapter 4 we will have a look at one specific area of health care, namely rehabilitation. We will introduce the goals of rehabilitation and analyse how AI technologies can be beneficial to these specific processes. We also mention disputes arising from the ethical aspects. Lastly, the chapter also provides an overview of different AI technologies that have already been developed for this context.
Chapter 5: Case Study: Exoskeletons for Stroke Rehabilitation
In our last chapter we present implications of a specific medical condition, the stroke, and introduce exoskeletons as one specific technology that uses AI to help patients with motor impairments. For this, we spoke to Dr. Elsa Kirchner, a scientist from the Deutsches Forschungszentrum für Künstliche Intelligenz, who helped in designing and developing the RECUPERA Exoskeleton, a technology that uses brain data to support movements. In an interview, you will get more insight into the way that AI is used in this technology but also how human-centered design and cognitive processes influenced its development.
Course offered by
Prof. Dr.-Ing Thomas Spittler
Vice Dean at the Technical University Deggendorf, Faculty European Campus Rottal-Inn, Pfarrkirchen, Germany
Head of the Health Informatics Program
Core competencies: Digitalization in healthcare, eHealth, Data analytics and applied artificial intelligence, health services research
Dr. Anna Kasparbauer studied Neuro-Cognitive Psychology (M.Sc.) at the Ludwig-Maximilians-University of Munich and received her doctorate in Psychology from the University of Bonn. Additionally she gained practical experience as a therapist in an outpatient pediatric psychiatry. Besides holding a research assistant position at DIT at the European Campus Rottal-Inn, she works as head psychologist at a rehabilitation clinic for parent-child recreation and respiratory disease treatment.
Veronika Reisner studied Computer Science (B.Sc.), and Psychology/Clinical Psychology and Cognitive Neurosciences (B.Sc./M.Sc.) at the Ludwig-Maximilians-University of Munich. She finished her Master degree in 2020 and worked at the Technische Hochschule Deggendorf as research assistant from 2020 to 2021. Her focus lies on AI and virtual health games. Since 2021 she works in frontend development.
Cosima Schenk studied Psychology (B.Sc./M.Sc.) at the Ludwig-Maximilians-University of Munich. During her Master degree in Clinical Psychology and Cognitive Neurosciences, she specialized in neurocognitive psychology. In 2019 she started a Bachelor degree in Computer Science at the Ludwig-Maximilians-University of Munich.
Anna Glas studied Psychology at the Julius-Maximilians-University of Würzburg (B.Sc.) and Clinical Psychology and Cognitive Neurosciences at the Ludwig-Maximilians-University of Munich (M.Sc.). She finished her Master degree in 2019. Since 2015 she also studies Art at the Academy of Fine Arts in Munich.
This course bridges the gap between health engineering and psychological concepts, therefore target groups include students and employees in health related fields such as Health Informatics, Health Science, Rehabilitation Science, Nursing Science and Engineering.
Confirmation of participation
In this course you can be awarded a certificate of participation. Please go through the entire course and answer more than 80% of all tests and questions correctly.