@inproceedings{KetterlKieseLandgrafetal., author = {Ketterl, Hermann and Kiese, Constanze and Landgraf, Hans-Peter and Danzer, Anna-Lena and Schickling, Benedikt and Nicolau-Torra, Anna and Reitmeier, Torsten and Schulte-Mattler, Wilhelm and von Schweinitz, Dietrich}, title = {Intuitive Visualization of Innervation Zones Based on Surface-EMG Signals}, series = {2018 40th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC), 18-21 July 2018, Honolulu, HI, USA}, booktitle = {2018 40th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC), 18-21 July 2018, Honolulu, HI, USA}, publisher = {IEEE}, doi = {10.1109/EMBC.2018.8513265}, pages = {3894 -- 3897}, abstract = {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.}, language = {en} } @inproceedings{KetterlHeinrichReitmeieretal., author = {Ketterl, Hermann and Heinrich, Tobias and Reitmeier, Torsten and Hoelscher, Clemens}, title = {Emissionsabh{\"a}ngige Leistungsregelung f{\"u}r BHKW's}, series = {Tagungsband AALE 2020: Automatisierung und Mensch-Technik-Interaktion, 17. Fachkonferenz, 4. bis 6. M{\"a}rz 2020, Leipzig}, volume = {2020}, booktitle = {Tagungsband AALE 2020: Automatisierung und Mensch-Technik-Interaktion, 17. Fachkonferenz, 4. bis 6. M{\"a}rz 2020, Leipzig}, editor = {J{\"a}kel, Jens and Thiel, Robert}, publisher = {VDE-Verlag}, isbn = {978-3-8007-5180-8}, pages = {7}, language = {de} } @unpublished{FischerHirschReitmeieretal., author = {Fischer, Johannes and Hirsch, Thomas and Reitmeier, Torsten and Bierl, Rudolf}, title = {Real-time hardware-based processing of high-precision detector signals for surface plasmon resonance spectroscopy}, doi = {10.2139/ssrn.5971170}, pages = {16}, abstract = {Surface plasmon resonance (SPR) is limited by small-signal detectability and drift when subtraction occurs in software after digitization. We introduce an SPR detector that performs on-detector amplification and analog differential readout, eliminating moving parts and software-heavy correction. The hardware-native subtraction boosts the usable ADC range and suppresses illumination and environmental noise. In fixed-angle refractive-index steps (NaCl), the platform resolves Δn_min ≈ 1.8 × 10⁻⁷ RIU compared to 4.6-7.2 × 10⁻⁶ RIU on a commercial comparator and improves small-signal SNR by up to ∼5,000-fold, while remaining competitive at high signal levels. In a model IgG-BSA assay, the detector's low noise floor clarifies early binding and equilibrium transitions. By generating inherently clean raw signals, this hardware-native approach dramatically enhances sensitivity and long-term stability for label-free biosensing and inline process analytics while rendering AI-based or complex post-processing entirely unnecessary. The concept generalizes across platforms and opens a compact route to robust, high-fidelity SPR in complex environments, with a clear path toward multi-wavelength and arrayed detectors for high-throughput chemical monitoring.}, language = {en} }