Author: Sebastian Schroeder

Motion analysis takes on new meaning. In the fascinating world of human body understanding and the importance of artificial intelligence, new frontiers of possibility are constantly being explored and expanded. In the process, groundbreaking developments in medical research and technology are revolutionizing the overall understanding of the human body, as artificial intelligence enables doctors and scientists to make more precise diagnoses, drives the development of personalized treatments, and provides access to previously undiscovered insights. Motion analysis based on AI – In this field of innovation, Sebastian Schröder, as an expert in medical AI research, is on hand with his extensive knowledge and provides comprehensive information on this exciting topic in the following guest article. His findings inspire and allow the reader to experience how artificial intelligence is taking the idea of health and well-being to a whole new level. Sebastian Schröder is a PhD student at the renowned Center for Tactile Internet (CETI) at Dresden University of Technology, which conducts groundbreaking research in the field of tactile communication. With a focus on human-in-the-loop computing and human motion analysis systems, he is dedicated to exploring innovative technologies. In addition to his academic career, Sebastian Schröder is also the managing director of Enari GmbH. It is a company that aims to make CETI research results accessible to end users. Sebastian Schröder wants to strengthen the connection between science and practice. Motion analysis up to now The recording and assessment of human movements carried out to date has mainly been done in a qualitative way. This means that physicians, therapists or trainers observe the movement patterns and provide feedback based on their experience and the expert knowledge they have acquired over the years. In doing so, they rely on their ability to perceive subtle details and recognize movement patterns. However, assessing movement quality is challenging because there is often a lack of reliable “ground truth” data from the field. For example, it proves difficult to accurately track and analyze the movements of a tennis player during a match. This is partly because conventional approaches to motion analysis, such as video- and sensor-based motion capture and muscle activation measurements (EMG), can provide important information but do not represent the entire musculoskeletal system in its complexity. Moreover, such measurements are usually performed under controlled laboratory conditions, leading to certain assumptions and bias. AI enables new tools and alignments Through innovative systems like those of Enari GmbH, it is now possible to capture the entire chain of action of human movements in the field.… weiterlesen