TY - CHAP A1 - Ketterl, Hermann A1 - Kiese, Constanze A1 - Landgraf, Hans-Peter A1 - Danzer, Anna-Lena A1 - Schickling, Benedikt A1 - Nicolau-Torra, Anna A1 - Reitmeier, Torsten A1 - Schulte-Mattler, Wilhelm A1 - von Schweinitz, Dietrich T1 - Intuitive Visualization of Innervation Zones Based on Surface-EMG Signals T2 - 2018 40th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC), 18-21 July 2018, Honolulu, HI, USA N2 - The purpose of this study was to develop a user-friendly presentation of surface-EMG data in near-time for intraoperative nerve-monitoring. We have built a novel surface-EMG probe as a diagnostic device to investigate innervation patterns of sphincter muscles in further clinical diagnostic studies. S-EMG data were recorded from 20 healthy volunteers from the orbicularis oris muscles. We developed an automated analysis based on correlation in order to find phase inversions and thus innervation zones automatically. We compared our automated analysis with manual, visual analysis. Both techniques were reviewed for variance and showed reproducible results. Data from automated analysis were compared to visually analyzed data showing high consistency. Based on our automated analysis, we created an intuitive visualization of all measurements per person. We displayed the quality and quantity of the phase inversions found in a subject thus allowing for simple identification of innervation zones. We conclude that our set-up showed sufficient reliability for detection of motoric endplate activity and can be used for further clinical neurophysiological studies. Y1 - 2018 U6 - https://doi.org/10.1109/EMBC.2018.8513265 SP - 3894 EP - 3897 PB - IEEE ER - TY - GEN A1 - Ketterl, Hermann A1 - Heinrich, Tobias T1 - Vivid tool for comprehensive biological soil analysis T2 - LANDSUPPORT Final Conference and the Save Our Soils Workshop, 27 -28 APRIL 2022, Portici, Italy N2 - The sample preparation for shadowing microscopy, to examinate biological soil properties, is time consuming, manual work. The outcome depends on subjective skills of the operator, furthermore the results are mostly not quantitative. The database on biological soil properties is mostly not sufficient for an integrated modelling on an multidisciplinary scale. This project combines three progressive approaches to develop a tool that is easy to use and gives in situ results that can be used for many purposes. Y1 - 2022 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:898-opus4-50078 UR - https://www.landsupport.eu/wp-content/uploads/2022/04/210422-abstract-poster-v2.pdf ER - TY - GEN A1 - Heinrich, Tobias A1 - Ketterl, Hermann T1 - AI to quantify biological diversity T2 - LANDSUPPORT Final Conference and the Save Our Soils Workshop, 27 -28 APRIL 2022, Portici, Italy N2 - The primary consumers of plant exudates – in exact fungi and bacteria, are representative for the soil succession level from bare soil, which is bacterial dominant to old growth forest constitute by fungal dominance. In a specified level of soil succession, a special kind of plant family benefits on the Fungal to Bacteria Ratio. The ability to determine this ratio in situ without complex chemical applications is part of the project Electronical Laboratory for Intelligent Soil Examination (ELISE). Several mechanical and optical tests on soil samples are covered within this Project. To analyze the fungal to bacteria ratio, samples are prepared automatically – in a defined and reproductive procedure – to generate slides for shadowing microscopy. The samples are observed by a camera, which is attached to a transmitted light microscope. The automatic analysis, done with computer vision algorithms, aims to quantify bacterial and fungal biomass in the actual sample view. Moreover, the algorithm can classify organisms according to their color and shape. To get a processable picture, several images from different focal levels must be taken through the sample thickness. Parts of each image, are in focus at the actual layer, are merged to a whole depth of field picture, by focus stacking. This produced picture is used to classify, locate and quantify – in first step filamentous organisms e.g. fungal by image sematic segmentation. The result represents an image sized mask, which indicates the class of fungi with class equivalate values at the pixel positions – covered by the organism. This information is used to calculate the fungal mass per gram soil. To quantify the bacterial biomass two approaches are implemented. For low density of bacterial existence, the individual bacteria is counted for a part of the field of view by an image detection algorithm to be extrapolate afterwards to the mass per gram soil. For high density of bacterial occurrence, specified regions of interest with only bacteria present are chosen. An image classification which has been pretrained by pictures of bacterial density patterns – previously determent by making the sample countable due to preforming sample dilutions, is done. The second option for high density bacterial count is, to automatically preform dilutions until the image detection is confidently countable. To ensure a usable confidence score a statistical approach of many fields of view is taken. Y1 - 2022 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:898-opus4-50080 UR - https://www.landsupport.eu/wp-content/uploads/2022/04/210422-abstract-poster-v2.pdf ER - TY - CHAP A1 - Ketterl, Hermann A1 - Hoelscher, Clemens A1 - Gotzler, Julian A1 - Grill, Oliver A1 - Heinrich, Tobias A1 - Mayer, Anton A1 - Reiter, Fabian A1 - Mühlbauer, Simon A1 - Weinzierl, Stefan ED - Jäkel, Jens ED - Thiel, Robert T1 - Autonomer Hackroboter T2 - Tagungsband AALE 2020: Automatisierung und Mensch-Technik-Interaktion, 17. Fachkonferenz, 4. bis 6. März 2020, Leipzig Y1 - 2020 SN - 978-3-8007-5180-8 VL - 2020 PB - VDE-Verlag ER - TY - CHAP A1 - Ketterl, Hermann A1 - Heinrich, Tobias A1 - Reitmeier, Torsten A1 - Hoelscher, Clemens ED - Jäkel, Jens ED - Thiel, Robert T1 - Emissionsabhängige Leistungsregelung für BHKW’s T2 - Tagungsband AALE 2020: Automatisierung und Mensch-Technik-Interaktion, 17. Fachkonferenz, 4. bis 6. März 2020, Leipzig Y1 - 2020 SN - 978-3-8007-5180-8 VL - 2020 PB - VDE-Verlag ER -