Patented method for the diagnosis of depression
14.06.2023 -
As part of this year's "World Intellectual Property Day", which was dedicated to women, German Patent and Trade Mark Office together with the Patent Information Centre Magdeburg, presented various women inventors, designers and trade mark owners.
In this article Isabel Heidemann, a graduate in oecotrophology, Nora Beiermann and Sandy Reß, master hearing aid acousticians, and Laila Ghaoui, a graduate engineer and mathematician, report on their projects, all of which also have registered property rights.
Laila Gbaoui, a medical engineer at the OVGU, is researching the analysis and characterisation of psychiatric illnesses and mental stress. She is developing a new non-invasive diagnostic procedure for depression. Colleagues from our "Medical Systems" working group, led by Professor Christoph Hoeschen, are also involved in this in cooperation with the medical team of Professor Thomas Frodl, Department of Psychiatry and Psychotherapy at OVGU and Department of Psychiatry, Psychotherapy and Psychosomatics at RWTH Aachen University Hospital.
Currently, psychiatry lacks proper quantitative biomarkers that allow clear diagnosis of psychiatric disorders. In contrast to the conventional interview-based diagnostic procedure, the new method is based on the identification and quantification of huge data sets of chemical particles in the exhaled air. Furthermore, the current diagnostic procedure is inexpensive and particularly easy to apply to children and elderly as well as multimorbid patients. In recent years, the analysis of chemical particles in exhaled air has proven to be a promising method for the identification of biomarkers for the diagnosis and monitoring of various metabolic diseases, cancer, asthma and so on.
What is special about this research area is the bridging between Artificial Intelligence (AI) and psychiatry, which holds out the prospect of new horizons for computational (digitised) psychiatry. The analysis of chemical Big Data with the various algorithms of AI could help extract new quantitative biomarkers for the early detection, diagnosis, treatment, progression and prevention of recurrent psychiatric episodes. In this way, treatments could be determined, optimised and thus also personalised by AI. And this especially against the background that over 350 million people worldwide are affected by mental illnesses and the prevalence is increasing in Germany and worldwide.
https://www.dpma.de/dpma/veroeffentlichungen/patentefrauen/womeninip/magdeburg/index.html (in german)