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Back problems are generally regarded as a widespread disease Finding the exact cause of these problems is often difficult. A team of researchers from TU Kaiserslautern (TUK), the University Medical Centre in Mainz and several companies is working on a method that will enable more efficient monitoring of malpositions and strains on the back. Artificial intelligence (AI) methods are also being used to help analyse the spine individually. The team will be presenting its project at the Rhineland-Palatinate research stand (stand E80, hall 3) at the Medizintechnikmesse (Medical Technology Trade Fair) in Düsseldorf from 14 to 17 November.
Too little exercise or exercise that is too one-sided, too much sitting at a desk and in front of a computer, not only at work but also in private life. The consequence that follows: Many people have back problems. Yet there are many proven preventive measures, such as courses in back exercises or relaxation methods, which are usually also offered and reimbursed by health insurance companies.
“But all this is of little use if the cause of the pain is not clearly defined,” says Carlo Dindorf, a scientist in the Department of Sports Science at TU Kaiserslautern. This is precisely what the TUK team is working on together with Jürgen Konradi and the research team of the Interprofessional Study Centre of Motion Research at the University Medical Center of the Johannes Gutenberg University in Mainz, the medical technology company DIERS International GmbH and other project partners.
The interdisciplinary team is relying on a diagnostic technique that is already well-tested and widespread in practice. “We scan the back with a projector and a camera unit,” says Dindorf. This involves projecting a grid of light onto the back. Using so-called raster stereography, an individual model of the spine can thus be generated. A new aspect of the method is the use of AI and machine learning methods. “Our system learns with the help of the data obtained,” explains Dindorf. “The more spines are analysed, the better the system and thus our understanding of the spine improves.”
To further improve the learning of these systems in the future, the team is working on enabling multi-centre, data collection for the common good. “For this purpose, we want to combine data from different measurement centres,” explains Dindorf. “All those involved in the therapy, such as doctors and physiotherapists, can upload their movement data to the resulting platform. This allows an objective, data-based assessment of the clinical picture to be generated afterwards using the AI pipelines that have been developed.”
This knowledge can help medicine in the future, for example, to better detect malpositions and to provide personalised diagnoses that enable individualised therapy. But the technology is also of interest for professional and amateur sports as well as for basic research in general. The result is a much more differentiated picture and better insight into the function of the spine.
Offene Digitalisierungsallianz Pfalz (Open Digitalisation Alliance Palatinate) is also involved in the project. They support the research team in translating the findings into practice in collaboration with other researchers, with stakeholders from the health sector and with entrepreneurs in the region.
Offene Digitalisierungsallianz Pfalz
Offene Digitalisierungsallianz Pfalz is a joint project of Kaiserslautern University of Applied Sciences, Technische Universität Kaiserslautern and the Fraunhofer Institute for Industrial Mathematics (ITWM). The project enhances the transfer of ideas, knowledge and technology with industry and society and is based on a cooperation strategy of the two universities. Offene Digitalisierungsallianz Pfalz is funded by the Federal Ministry of Education and Research within the framework of the federal-state initiative “Innovative Hochschule”.
Klaus Dosch, Department of Technology and Innovation, is organizing the presentation of the researchers of the TU Kaiserslautern at the Medica. He is the contact partner for companies and, among other things, establishes contacts to science.
Contact: Klaus Dosch, E-mail: dosch@rti.uni-kl.de, Phone: +49 631 205-3001
Questions can be directed to:
Dr Carlo Dindorf and Prof. Dr Michael Fröhlich
Research area; Sport Science - Department of Exercise and Training Science
TU Kaiserslautern
E-mail: carlo.dindorf@sowi.uni-kl.de
Phone: +49 631 205-5172
Dr Jürgen Konradi
Interprofessionelles Studienzentrum für Bewegungsforschung [Interprofessional Study Centre for Research on Movement]
Johannes Gutenberg-Universitaet Mainz
E-mail: juergen.konradi@unimedizin-mainz.de
Phone: +49 631-17-2362
The procedure is intended to detect the causes of back problems more efficiently. Credit: Interprof ...
Credit: SZB
Interprofessionelles Studienzentrum für Bewegungsforschung (SZB)
Criteria of this press release:
Business and commerce, Journalists
Information technology, Medicine, Sport science
transregional, national
Research projects, Transfer of Science or Research
English
The procedure is intended to detect the causes of back problems more efficiently. Credit: Interprof ...
Credit: SZB
Interprofessionelles Studienzentrum für Bewegungsforschung (SZB)
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