@inproceedings{HauslerGensleinRothetal., author = {Hausler, Peter and Genslein, Christa and Roth, Carina and Vitzthumecker, Thomas and Hirsch, Thomas and Bierl, Rudolf}, title = {Miniaturized Surface Plasmon Resonance based Sensor System}, series = {Proceedings of the 6th International Conference on Photonics, Optics and Laser Technology - PHOTOPTICS, Funchal, Madeira, Portugal}, booktitle = {Proceedings of the 6th International Conference on Photonics, Optics and Laser Technology - PHOTOPTICS, Funchal, Madeira, Portugal}, publisher = {SciTePress}, isbn = {978-989-758-286-8}, doi = {10.5220/0006555400630066}, pages = {63 -- 66}, abstract = {We describe the miniaturization of the Surface Plasmon Resonance (SPR) technology which mainly finds its applications in pharmaceutical screening and biotechnology so far. SPR spectroscopy is a label-free, non-destructive and highly sensitive measurement principle detecting changes in the refractive index in striking distance to a gold surface. A transfer of this technology to a miniaturized sensor will broaden the range of possible applications. A promising feature which is included in the miniaturized system is the angle-dependent recording of the SPR signals without moving parts. Commercial SPR assays are mainly working with a small number of sensing spots. In contrast, the SPR imaging system shown here will allow to use an array of many sensing spots. In combination with chemical receptors designed as an artificial nose, the simultaneous detection of many analytes is envisioned for future applications.}, language = {en} } @article{GensleinHauslerKirchneretal., author = {Genslein, Christa and Hausler, Peter and Kirchner, Eva-Maria and Bierl, Rudolf and Baeumner, Antje J. and Hirsch, Thomas}, title = {Graphene-enhanced plasmonic nanohole arrays for environmental sensing in aqueous samples}, series = {Beilstein Journal of Nanotechnology}, journal = {Beilstein Journal of Nanotechnology}, number = {7}, doi = {10.3762/bjnano.7.150}, url = {http://nbn-resolving.de/urn:nbn:de:bvb:355-epub-398623}, pages = {1564 -- 1573}, abstract = {The label-free nature of surface plasmon resonance techniques (SPR) enables a fast, specific, and sensitive analysis of molecular interactions. However, detection of highly diluted concentrations and small molecules is still challenging. It is shown here that in contrast to continuous gold films, gold nanohole arrays can significantly improve the performance of SPR devices in angle-dependent measurement mode, as a signal amplification arises from localized surface plasmons at the nanostructures. This leads consequently to an increased sensing capability of molecules bound to the nanohole array surface. Furthermore, a reduced graphene oxide (rGO) sensor surface was layered over the nanohole array. Reduced graphene oxide is a 2D nanomaterial consisting of sp2-hybridized carbon atoms and is an attractive receptor surface for SPR as it omits any bulk phase and therefore allows fast response times. In fact, it was found that nanohole arrays demonstrated a higher shift in the resonance angle of 250-380\% compared to a continuous gold film. At the same time the nanohole array structure as characterized by its diameter-to-periodicity ratio had minimal influence on the binding capacity of the sensor surface. As a simple and environmentally highly relevant model, binding of the plasticizer diethyl phthalate (DEP) via π-stacking was monitored on the rGO gold nanohole array realizing a limit of detection of as low as 20 nM. The concentration-dependent signal change was studied with the best performing rGO-modified nanohole arrays. Compared to continuous gold films a diameter-to-periodicity ratio (D/P) of 0.43 lead to a 12-fold signal enhancement. Finally, the effect of environmental waters on the sensor was evaluated using samples from sea, lake and river waters spiked with analytically relevant amounts of DEP during which significant changes in the SPR signal are observed. It is expected that this concept can be successfully transferred to enhance the sensitivity in SPR sensors.}, language = {en} } @inproceedings{HauslerGensleinRothetal., author = {Hausler, Peter and Genslein, Christa and Roth, Carina and Hirsch, Thomas and Bierl, Rudolf}, title = {Mikro-Opto-Elektro-Mechanisches Sensorsystem zur Oberfl{\"a}chenplasmonenresonanzspektroskopie}, series = {MikroSystemTechnik Kongress 2017 : MEMS, Mikroelektronik, Systeme 23.-25. Oktober 2017 in M{\"u}nchen}, booktitle = {MikroSystemTechnik Kongress 2017 : MEMS, Mikroelektronik, Systeme 23.-25. Oktober 2017 in M{\"u}nchen}, number = {CD-ROM}, publisher = {VDE-Verlag}, address = {Berlin}, isbn = {978-3-8007-4491-6}, pages = {645 -- 647}, abstract = {Gezeigt wird die Miniaturisierung eines Messsystems f{\"u}r Oberfl{\"a}chenplasmonenresonanzspektroskopie (SPR), einer markierungs-, sowie zerst{\"o}rungsfreien als auch hoch sensitiven Technologie. Aufgrund der hohen Kosten klassischer SPR-Ger{\"a}te wird sie bisher jedoch vornehmlich in der Bio- und Medizintechnik eingesetzt. Das Messprinzip erm{\"o}glicht die Erfassung von Brechungsindex{\"a}nderungen nahe einer Oberfl{\"a}che. Der Transfer dieser Technologie von Laborger{\"a}ten hin zu einem miniaturisierten Sensorsystem senkt die Kosten, macht das System robuster und erm{\"o}glicht so ein wesentlich breiteres Anwendungsspektrum. Ein sehr vielversprechendes Merkmal des hier vorgestellten Systems ist die M{\"o}glichkeit den SPR-Effekt winkelabh{\"a}ngig zur Lichtquelle ohne bewegliche Bauteile zu verfolgen. The miniaturization of Surface Plasmon Resonance (SPR) technology, which mainly finds its applications in pharmaceutical screening and biotechnology so far, is described. SPR spectroscopy is a label-free, non destructive and highly sensitive measurement principle which is capable of detecting changes in the refractive index in striking distance to a gold surface. A transfer of this technology to a miniaturized sensor will broaden the range of possible applications. A promising feature which is included in the miniaturized system is the angle-dependent recording of the SPR signals without moving parts.}, language = {de} } @inproceedings{GensleinHauserKirchneretal., author = {Genslein, Christa and Hauser, Peter and Kirchner, Eva-Maria and Bierl, Rudolf and Baeumner, Antje J. and Hirsch, Thomas}, title = {Detection of small molecules with surface plasmon resonance by synergistic plasmonic effects of nanostructured surfaces and graphene}, series = {SPIE Proceedings, Plasmonics in Biology and Medicine XIV, 2017, San Francisco, California}, volume = {10080}, booktitle = {SPIE Proceedings, Plasmonics in Biology and Medicine XIV, 2017, San Francisco, California}, number = {1008001F}, doi = {10.1117/12.2252256}, abstract = {Surface plasmon resonance depends on the dielectric medium at the vicinity and makes it a quasi-universal detector. Therefore, and due to the label-free nature, SPR is a widely used sensing tool for real-time monitoring molecular interactions of various analytes. However, detection of highly diluted analytes and small molecules (< 400 Da) is still challenging. Gold nanohole arrays provide plasmonic hotspots with improved surface sensitivity and 2D carbon nanomaterials enable binding near the surface. Both effects together are promising in the development of SPR sensors for the efficient determination of small molecules. Graphene is known for efficient binding of molecules with delocalized aromatic π-systems. Additionally, the electromagnetic field is locally enhanced and modulated by the interaction of graphene photonics with the plasmonics of metal nanostructures. The advantages of chemical vapor deposition (CVD) graphene over reduced graphene oxide (rGO) is illustrated by a proof of concept study. In comparison to substrates consisting of a continuous film the surface sensitivity is enhanced for a nanohole arrays and further improved for CVD graphene functionalization in contrast to rGO. The feasibility of the sensor was demonstrated for the detection of adenine down to a concentration of 0.9 μM.}, language = {en} } @inproceedings{HauslerHollerHirschetal., author = {Hausler, Peter and Holler, Sven and Hirsch, Thomas and Bierl, Rudolf}, title = {High integrated miniaturized sensor based on Surface Plasmon Resonance}, series = {International Biosensor Conference, 11th Workshop on Biosensors \& Bioanalytical Microtechniques in Environmental, Food \& Clinical Analysis, BBMEC 11, 26.-30. September 2015, Regensburg, Germany}, booktitle = {International Biosensor Conference, 11th Workshop on Biosensors \& Bioanalytical Microtechniques in Environmental, Food \& Clinical Analysis, BBMEC 11, 26.-30. September 2015, Regensburg, Germany}, language = {en} } @inproceedings{HauslerHollerHirschetal., author = {Hausler, Peter and Holler, Sven and Hirsch, Thomas and Bierl, Rudolf}, title = {Miniaturisierte Oberfl{\"a}chenplasmonenresonanz Sensorplattform}, series = {MEMS, Mikroelektronik, Systeme, MikroSystemTechnik Kongress 2015, 26.- 28. Oktober 2015, Karlsruhe, proceedings}, booktitle = {MEMS, Mikroelektronik, Systeme, MikroSystemTechnik Kongress 2015, 26.- 28. Oktober 2015, Karlsruhe, proceedings}, publisher = {VDE Verlag}, address = {Berlin}, isbn = {978-3-8007-4100-7}, language = {de} } @article{PangerlMoserMuelleretal., author = {Pangerl, Jonas and Moser, Elisabeth and M{\"u}ller, Max and Weigl, Stefan and Jobst, Simon and R{\"u}ck, Thomas and Bierl, Rudolf and Matysik, Frank-Michael}, title = {A sub-ppbv-level Acetone and Ethanol Quantum Cascade Laser Based Photoacoustic Sensor- Characterization and Multi-Component Spectra Recording in Synthetic Breath}, series = {Photoacoustics}, volume = {30}, journal = {Photoacoustics}, publisher = {Elsevier}, issn = {2213-5979}, doi = {10.1016/j.pacs.2023.100473}, pages = {1 -- 12}, abstract = {Trace gas analysis in breath is challenging due to the vast number of different components. We present a highly sensitive quantum cascade laser based photoacoustic setup for breath analysis. Scanning the range between 8263 and 8270 nm with a spectral resolution of 48 pm, we are able to quantify acetone and ethanol within a typical breath matrix containing water and CO2. We photoacoustically acquired spectra within this region of mid-infra-red light and prove that those spectra do not suffer from non-spectral interferences. The purely additive behavior of a breath sample spectrum was verified by comparing it with the independently acquired single component spectra using Pearson and Spearman correlation coefficients. A previously presented simulation approach is improved and an error attribution study is presented. With a 3σ detection limit of 6.5 ppbv in terms of ethanol and 250 pptv regarding acetone, our system is among the best performing presented so far.}, language = {en} } @incollection{WeiglMuellerPangerletal., author = {Weigl, Stefan and M{\"u}ller, Max and Pangerl, Jonas and R{\"u}ck, Thomas}, title = {Scopes and Limits of Photoacoustic Spectroscopy in Modern Breath Analysis}, series = {Breath Analysis}, booktitle = {Breath Analysis}, publisher = {Springer nature}, isbn = {978-3-031-18526-7}, doi = {10.1007/11663_2022_22}, pages = {101 -- 159}, abstract = {Photoacoustic spectroscopy is a viable tool for trace gas detection in various application fields. In recent years, this technique has been exploited more and more for modern breath analysis as well. Within this chapter, a holistic overview of photoacoustic spectroscopy is presented, while maintaining the relationship to breath analysis. Therefore, a concise description of the fundamentals of photoacoustic spectroscopy is provided. This is essential for understanding the scopes and limits of this outstanding measurement technique being described within this chapter. In the past several different types of photoacoustic measurement setups for trace gas detection have emerged, including different light sources, modulation techniques, and detection schemes. These are described shortly and advantages as well as disadvantages, especially in relation to breath analysis, are highlighted. Though being a promising sensor principle, measurement devices based on photoacoustic spectroscopy are still rare on the sensor market, especially when it comes to trace gas detection in complex gas matrices, e.g., human breath exhale. One main reason is due to possible molecular interactions influencing the relaxational behavior of the analyte altering the sensor signal. Recent results shedding light on the intricate relaxational processes within complex gas matrices are discussed in detail, providing approaches to overcome this issue. Finally, various applications of photoacoustic spectroscopy in breath analysis are described demonstrating the great potential of this technology.}, language = {en} } @misc{OlbrichPongratzBierletal., author = {Olbrich, Florian and Pongratz, Christian and Bierl, Rudolf and Ehrlich, Ingo}, title = {Method and System for Evaluating a Structural Integrity of an Aerial Vehicle}, series = {Europ{\"a}isches Patentblatt (09.12.2020) zur Anmeldung: OTH Regensburg, Anmeldenummer: 19179054.2, Patentnummer 1001/3748327, Ver{\"o}ffentlichungsnummer: 3 748 327}, journal = {Europ{\"a}isches Patentblatt (09.12.2020) zur Anmeldung: OTH Regensburg, Anmeldenummer: 19179054.2, Patentnummer 1001/3748327, Ver{\"o}ffentlichungsnummer: 3 748 327}, pages = {395 -- 396}, language = {en} } @inproceedings{HauslerFischerWunderlichetal., author = {Hausler, Peter and Fischer, Johannes and Wunderlich, Lukas and Recum, Patrick and Peller, Sebastian and Hirsch, Thomas and Bierl, Rudolf}, title = {Miniaturisierte Sensoren basierend auf Oberfl{\"a}chenplasmonenresonanz, Chancen und Herausforderungen}, series = {DGaO-Proceedings 2021}, booktitle = {DGaO-Proceedings 2021}, publisher = {Dt. Gesellschaft f{\"u}r angewandte Optik}, address = {Erlangen-N{\"u}rnberg}, abstract = {Derzeit gibt es zahlreiche Bereiche, wie Umwelt Monitoring und zivile Infrastruktur in denen geeignete Sensoren f{\"u}r die {\"U}berwachung der Systeme fehlen. SPR-basierte Sensoren haben das Potential diese L{\"u}cke zu schließen. Um f{\"u}r den Einsatz in der Umwelt tauglich zu werden, m{\"u}ssen die Sensoren noch robuster werden. Hier wird eine m{\"o}gliche L{\"o}sung gezeigt.}, language = {de} } @article{MoserJobstBierletal., author = {Moser, Elisabeth and Jobst, Simon and Bierl, Rudolf and Jenko, Frank}, title = {A Deep Learning System to Transform Cross-Section Spectra to Varying Environmental Conditions}, series = {Vibrational Spectroscopy}, volume = {122}, journal = {Vibrational Spectroscopy}, number = {September}, publisher = {Elsevier}, issn = {0924-2031}, doi = {10.1016/j.vibspec.2022.103410}, abstract = {Absorption cross-sections provide a basis for many gas sensing applications. Therefore, any error in molecular cross-sections caused by varying environmental conditions propagates to spectroscopic applications. Original molecular cross-sections in varying environmental conditions can only be simulated for some molecules, whereas for most multi-atom molecules, one must rely on high-precision measurements at certain environmental configurations. In this study, a deep learning system trained with simulated absorption cross-sections for predicting cross-sections at a different pressure configuration is presented. The system's capability to transfer to measured, multi-atom cross-sections is demonstrated. Thus, it provides an alternative to (pseudo-) line lists whenever the required information for simulation is unavailable. The predictive performance of the system was evaluated on validation data via simulation, and its transfer learning capabilities were demonstrated on actual measurement chlorine nitrate data. From the comparison between the system and line lists, the system shows slightly worse performance than pseudo-line lists but its predictive quality is still deemed acceptable with less than 5\% relative integral change with a highly localized error around the peak center. This opens a promising way for further research to use deep learning to simulate the effect of varying environmental conditions on absorption cross-sections.}, language = {en} } @inproceedings{MoserPangerlJobstetal., author = {Moser, Elisabeth and Pangerl, Jonas and Jobst, Simon and Weigl, Stefan and Bierl, Rudolf}, title = {Modeling the Photoacoustic Spectrum of a Quantum Cascade Laser for Human Breath}, series = {Optical Sensors and Sensing Congress 2022 (AIS, LACSEA, Sensors, ES): July 11 - 15, 2022, Vancouver, British Columbia Canada}, booktitle = {Optical Sensors and Sensing Congress 2022 (AIS, LACSEA, Sensors, ES): July 11 - 15, 2022, Vancouver, British Columbia Canada}, publisher = {Optica Publishing Group}, isbn = {978-1-957171-10-4}, doi = {10.1364/AIS.2022.ATu3G.2}, abstract = {A modeling approach to create a photoacoustic spectrum from synthetic data is presented and evaluated. The resulting model reaches a MAPE score of 2.7\% and can be used to enable data-driven development in future work.}, subject = {Quantenkaskadenlaser}, language = {en} } @article{GoldschmidtMoserNitzscheetal., author = {Goldschmidt, Jens and Moser, Elisabeth and Nitzsche, Leonard and Bierl, Rudolf and W{\"o}llenstein, J{\"u}rgen}, title = {Improving the performance of artificial neural networks trained on synthetic data in gas spectroscopy - a study on two sensing approaches}, series = {tm - Technisches Messen}, journal = {tm - Technisches Messen}, edition = {Online ver{\"o}ffentlicht}, publisher = {Oldenbourg Wissenschaftsverlag}, doi = {10.1515/teme-2023-0051}, abstract = {Artificial neural networks (ANNs) are used in quantitative infrared gas spectroscopy to predict concentrations on multi-component absorption spectra. Training of ANNs requires vast amounts of labelled training data which may be elaborate and time consuming to obtain. Additional data can be gained by the utilization of synthetically generated spectra, but at the cost of systematic deviations to measured data. Here, we present two approaches to train ANNs with a combination of comparatively small, measured data sets and synthetically generated data. For the first approach a neural network is trained hybridly with synthetically generated infrared absorption spectra of mixtures of N2O and CO and measured zero-gas spectra, taken with a mid-infrared dual comb spectrometer. This improves the mean absolute error (MAE) of the network predictions from 0.46 to 0.01 ppmV and 0.24 to 0.01 ppmV for the concentration predictions of N2O and CO respectively for zero-gas measurements which was previously observed for training with purely synthetic data. At the same time a similar performance on spectra from gas mixtures of 0-100 ppmV N2O and 0 to 60 ppmV CO was achieved. For the second approach an ANN pre-trained on synthetic infrared spectra of mixtures of acetone and ethanol is retrained on a small dataset consisting of 26 spectra taken with a mid-infrared photoacoustic spectrometer. In this case the MAE for the concentration predictions of ethanol and acetone are improved by 45 \% and 20 \% in comparison to purely synthetic training. This shows the capability of using synthetically generated data to train ANNs in combination with small amounts of measured data to further improve neural networks for gas sensing and the transferability between different sensing approaches.}, language = {en} } @inproceedings{UlreichMoserOlbrichetal., author = {Ulreich, Fabian and Moser, Elisabeth and Olbrich, Florian and Ebert, Martin and Bierl, Rudolf and Kaup, Andr{\´e}}, title = {Luminance Simulation in CARLA under Cloud Coverage - Model Validation and Implications}, series = {2023 IEEE International Workshop on Metrology for Automotive (MetroAutomotive), -30 June 2023, Modena, Italy}, booktitle = {2023 IEEE International Workshop on Metrology for Automotive (MetroAutomotive), -30 June 2023, Modena, Italy}, editor = {Keil, Rudolf and Tschorn, Jan Alexander and T{\"u}mler, Johannes and Altinsoy, Mehmet Ercan}, publisher = {IEEE}, isbn = {979-8-3503-2187-6}, doi = {10.1109/MetroAutomotive57488.2023.10219098}, pages = {228 -- 233}, abstract = {To decrease the number of kilometers driven during the development of autonomous cars or driving assistance systems, performant simulation tools are necessary. Currently, domain distance effects between simulation and reality are limiting the successful application of rendering engines in data-driven perception tasks. In order to mitigate those domain distance effects, simulation tools have to be as close to reality as possible for the given task. For optical sensors like cameras, the luminance of the scene is essential. We provide within this paper a method to measure the luminance of rendered scenes within CARLA, an often used open-source simulation environment. Thereby, it is possible to validate the environment and weather models by taking real-world measurements with photometric sensors or with the help of open-source weather data, published e.g. by the German federal service for weather data (DWD - "Deutscher Wetterdienst"). Employing our proposed luminance measurement, the domain gap resulting from the simulation can be specified, which makes it possible to evaluate the statements about the safety of the automated driving system determined within the simulation. We show that the ratio between global and diffuse radiation modeled by the default atmosphere models within CARLA are under limited conditions similar to real-world measurements taken by the DWD. Nevertheless, we show, that the ratio's temporal variability in real-world situations is not modeled by CARLA.}, language = {en} } @article{MuellerWeiglMuellerWilliamsetal., author = {M{\"u}ller, Max and Weigl, Stefan and M{\"u}ller-Williams, Jennifer and Lindauer, Matthias and R{\"u}ck, Thomas and Jobst, Simon and Bierl, Rudolf and Matysik, Frank-Michael}, title = {Comparison of photoacoustic spectroscopy and cavity ring-down spectroscopy for ambient methane monitoring at Hohenpeißenberg}, series = {Atmospheric Measurement Techniques}, volume = {16}, journal = {Atmospheric Measurement Techniques}, number = {18}, publisher = {Copernicus Publications}, issn = {1867-8548}, doi = {10.5194/amt-16-4263-2023}, pages = {4263 -- 4270}, abstract = {With an atmospheric concentration of approximately 2000 parts per billion (ppbV, 10-9), methane (CH4) is the second most abundant greenhouse gas (GHG) in the atmosphere after carbon dioxide (CO2). The task of long-term and spatially resolved GHG monitoring to verify whether climate policy actions are effective is becoming more crucial as climate change progresses. In this paper we report the CH4 concentration readings of our photoacoustic (PA) sensor over a 5 d period at Hohenpeißenberg, Germany. As a reference device, a calibrated cavity ring-down spectrometer, Picarro G2301, from the meteorological observatory of the German Weather Service (DWD) was employed. Trace gas measurements with photoacoustic instruments promise to provide low detection limits at comparably low costs. However, PA devices are often susceptible to cross-sensitivities related to fluctuating environmental conditions, e.g. ambient humidity. The obtained results show that for PA sensor systems non-radiative relaxation effects induced by varying humidity are a non-negligible factor. Applying algorithm compensation techniques, which are capable of calculating the influence of non-radiative relaxation effects on the photoacoustic signal, increase the accuracy of the photoacoustic sensor significantly. With an average relative deviation of 1.11 \% from the G2301, the photoacoustic sensor shows good agreement with the reference instrument.}, language = {en} } @unpublished{PangerlMoserMuelleretal., author = {Pangerl, Jonas and Moser, Elisabeth and M{\"u}ller, Max and Weigl, Stefan and Jobst, Simon and R{\"u}ck, Thomas and Bierl, Rudolf and Matysik, Frank-Michael}, title = {A Highly Sensitive Acetone and Ethanol Quantum Cascade Laser Based Photoacoustic Sensor: Characterization and Multi-Component Spectra Recording in Synthetic Breath}, series = {SSRN Electronic Journal}, journal = {SSRN Electronic Journal}, publisher = {Elsevier}, doi = {10.2139/ssrn.4305376}, abstract = {Trace gas analysis in breath is challenging due to the vast number of different components. We present a highly sensitive quantum cascade laser based photoacoustic setup for breath analysis. Scanning the range between 8260 and 8270 nm with a spectral resolution of 48 pm, we are able to quantify acetone and ethanol within a typical breath matrix containing water and CO2. We photoacoustically acquired spectra within this region of mid-infra-red light and prove that those spectra do not suffer from non-spectral interferences. The purely additive behavior of a breath sample spectrum was verified by comparing it with the independently acquired single component spectra using Pearson and Spearman correlation coefficients. A previously presented simulation approach is improved and an error attribution study is presented. With a 3σ detection limit of 6.5 ppbV in terms of ethanol and 250 pptV regarding acetone, our system is among the best performing presented so far.}, language = {en} } @inproceedings{RothHauslerBierl, author = {Roth, Carina and Hausler, Peter and Bierl, Rudolf}, title = {Einbindung eines 2D-Photodetektors in einen hochintegrierten SPR-Imaging-Sensor}, series = {7. MikroSystemTechnik Kongress "MEMS, Mikroelektronik, Systeme", 23.-25. Oktober 2017, M{\"u}nchen}, booktitle = {7. MikroSystemTechnik Kongress "MEMS, Mikroelektronik, Systeme", 23.-25. Oktober 2017, M{\"u}nchen}, publisher = {VDE-Verlag}, address = {M{\"u}nchen}, isbn = {978-3-8007-4491-6}, pages = {848 -- 850}, abstract = {Die Oberfl{\"a}chenplasmonenresonanzspektroskopie (SPR) ist eine hochempfindliche Messmethode, die es erlaubt, Gase und Fl{\"u}ssigkeiten zerst{\"o}rungs- und markierungsfrei in Echtzeit zu analysieren. Bisher vornehmlich im Labormaßstab in der Bioanalytik und dem Wirkstoffscreening eingesetzt, soll diese Technologie nun miniaturisiert und f{\"u}r weitere Anwendungsgebiete zug{\"a}nglich gemacht werden. Dazu wird ein kompakter Micro-Opto-Electro-Mechanical Systems Sensor (MOEMS) entwickelt, der mit Hilfe des SPR Imaging {\"A}nderungen der chemischen Zusammensetzung verschiedener Fl{\"u}ssigkeiten inline messen kann.}, language = {de} } @inproceedings{BauerVitzthumeckerBierletal., author = {Bauer, Lukas and Vitzthumecker, Thomas and Bierl, Rudolf and Ehrnsperger, Matthias}, title = {Machine-learning-based detection and severity estimation of drought stress in plants using hyperspectral imaging data}, series = {Remote Sensing for Agriculture, Ecosystems, and Hydrology XXVII}, booktitle = {Remote Sensing for Agriculture, Ecosystems, and Hydrology XXVII}, publisher = {SPIE}, doi = {10.1117/12.3072011}, pages = {7}, abstract = {Growing food demand due to population growth, coupled with increasingly frequent and severe droughts caused by climate change make water increasingly scarce. To address this, accurate assessment of plant water demand is essential for precise drought treatment and water conservation. Hyperspectral imaging (HSI) captures hypercubes, a combination of spectral and spatial data and offers promising capabilities for detection of plant stresses. However, most reported approaches only use selected spectral bands or indices, neglecting the full hypercube information. This is assumed to limit the detection accuracy. To overcome these limitations, we aim to develop a measurement pipeline to generate a comprehensive dataset comprising hypercubes of plants under varying drought stress levels along with selected physiological, environmental, and illumination data. This dataset will be used to train suitable data-driven models that enable improved drought stress detection as well as the non-invasive determination of physiological parameters based on HSI data.}, language = {en} } @inproceedings{Ehrnsperger, author = {Ehrnsperger, Matthias G.}, title = {Enhancing object recognition through camera-radar fusion and micro-doppler signature integration}, series = {Emerging Technologies and Materials for Security and Defence 2025}, booktitle = {Emerging Technologies and Materials for Security and Defence 2025}, publisher = {SPIE}, doi = {10.1117/12.3071682}, pages = {5}, abstract = {Object recognition systems based on visual sensors often struggle in degraded environmental conditions such as fog, rain, darkness, or occlusion. Radar, in contrast, offers robust detection capabilities under such conditions but lacks the spatial resolution of optical sensors. This paper presents an ongoing research effort towards a multimodal sensor fusion framework that integrates camera data with radar signals, specifically exploiting micro-Doppler (μD) signatures, with the aim of improving object recognition robustness. The proposed setup uses an Intel RealSense Depth Camera D455 and an Infineon BGT60TR13C radar sensor, deployed on a low-power embedded platform with STM32 microcontrollers. The signal processing pipeline, currently under development, combines time-frequency radar analysis with convolutional neural network-based visual feature extraction for real-time edge AI inference. We describe the system design, preliminary data acquisition setup, and planned evaluation strategy.}, language = {en} } @inproceedings{Ehrnsperger, author = {Ehrnsperger, Matthias G.}, title = {Multimodal sensor fusion for resilient perception: combining radar and imaging for all-weather object tracking}, series = {Artificial Intelligence and Image and Signal Processing for Remote Sensing XXXI}, booktitle = {Artificial Intelligence and Image and Signal Processing for Remote Sensing XXXI}, publisher = {SPIE}, doi = {10.1117/12.3071683}, pages = {5}, abstract = {This work presents the concept and initial qualitative observations of a multimodal perception system that fuses radar, lidar, and camera data to improve object detection and tracking under adverse environmental conditions. The approach focuses on building weather-impact models for each sensor modality—quantifying performance degradation effects such as color shifts and contrast loss in cameras, range reduction and spurious returns in lidar, and resolution limitations in radar. These models will later inform adaptive sensor fusion strategies deployed on embedded edge-AI hardware, using an Infineon BGT60TR13C FMCW radar, Intel RealSense D455 depth camera, and low-power processors. Preliminary visual inspection of collected datasets indicates that combining complementary sensing modalities can maintain detection continuity under conditions where single modalities fail. Future work will quantitatively evaluate these effects and demonstrate weather-adaptive perception on the embedded platform.}, language = {en} } @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} } @inproceedings{JannsenEhrnsperger, author = {Jannsen, Kai and Ehrnsperger, Matthias}, title = {Edge-efficient convolutional neural network for real-time doppler radar gesture recognition}, series = {2025 IEEE Radar Conference (RadarConf25), 4.-9. Oktober 2025, Krakow}, booktitle = {2025 IEEE Radar Conference (RadarConf25), 4.-9. Oktober 2025, Krakow}, publisher = {IEEE}, isbn = {979-8-3315-4433-1}, doi = {10.1109/RadarConf2559087.2025.11205096}, pages = {877 -- 881}, abstract = {Embedded gesture recognition using radar sensors enables intuitive and robust human-machine interfaces, which is appealing for automotive applications such as trunk opening via foot gesture. Designing a radar-based classifier that runs ondevice (edge) under strict resource constraints poses several challenges. The system must achieve real-time inference (e.g. under 200 ms) on a microcontroller unit (MCU), while maintaining high accuracy, and minimize false detections. This paper focuses on a binary classification task, while distinguishing a valid trunkopening "kick" gesture from other motions. Firstly, we evaluate classical machine learning (cML) models (Random Forests or support vector machines (SVMs)) for baseline performance, however they face difficulties with higher false positive rates and do not meet real time criteria. We then employ Convolutional Neural Networks (CNNs) and apply neural architecture search (NAS) to discover a compact CNN tailored for a 60 GHz Doppler radar dataset of 50 subjects, each with 10 leg gestures. By constraining network depth, filter sizes, and hyperparameters, NAS yields a small but accurate "edge" CNN that fits within the limited memory of a STM32 Nucleo F446RE microcontroller. The final model achieves 95.1 \% accuracy on the binary classification task with 96.6 \% precision and 2.17 \% false positive rate (FPR), and requires only 167.5 ms to run inference on the MCU.}, language = {en} } @phdthesis{Weigl, author = {Weigl, Stefan}, title = {Development of a sensor system for human breath acetone analysis based on photoacoustic spectroscopy}, doi = {10.5283/epub.44776}, url = {http://nbn-resolving.de/urn:nbn:de:bvb:355-epub-447768}, pages = {xlii, 282}, abstract = {The breath analysis section of this thesis outlines the potentials but also emphasises the concomitant challenges of human breath analysis. The section further describes the usefulness of a point-of-care (POC) device for breath acetone detection. In addition, it covers various breath analysis related subjects, which can be useful considering further developments of breath analysers. This includes an extensive summary involving the high abundant endogenous as well as the exogenous breath species present in a clinical environment. Subsequently, a detailed discussion about the theoretical aspects of absorption spectra is provided, forming the basis for the spectral interference chapter. Classical absorption spectroscopy (AS) is compared with photoacoustic spectroscopy (PAS) in view of trace gas analysis. Different modulation schemes for signal generation, i.e. amplitude modulation (AM) and wavelength modulation (WM) are part of the comparison, while the advantages and disadvantages of each technique are highlighted. As a result, PAS is considered superior to AS and hence is selected as the method of choice regarding the development of a sensor for breath acetone detection. A detailed mathematical derivation of the photoacoustic signal generation as well as the signal enhancement by means of acoustic resonance amplification is provided. Moreover, several phenomena causing signal attenuation are outlined, including vibrational-translational (VT) relaxation, vibrational-vibrational (VV) energy transfer mechanism, acoustic detuning and photodissociation. Various simulations regarding spectral interferences in the infra-red (IR) and ultraviolet (UV) region are presented, demonstrating the susceptibility towards spectral cross-sensitivities in the IR region, hence, rather suggesting the UV region for acetone detection. However, this simulation can be easily adopted to other target analytes and serves as a basis for multicomponent analysis approaches in the IR region using tuneable light sources. Ultra sensitive acetone detection employing a high power UV LED is presented and a detailed analysis considering the effects of environmental parameters onto the photoacoustic signal, including temperature, pressure, LED duty cycle and flow rate, is provided. In addition, general cross-sensitivities of the photoacoustic signal towards the high abundant species O2, CO2 and H2O have been investigated and discussed. Moreover, several LED and photoacoustic cell (PAC) combinations have been compared in order to evaluate improvement approaches regarding an enhancement of the system's sensitivity. Finally, photoacoustic sensor setups employing an interband cascade laser (ICL) or a quantum cascade laser (QCL) have been studied and compared to various UV setups in view of different key performance parameters, including the limits of detection (LOD) and the normalised noise equivalent absorption (NNEA) coefficients. The juxtaposition of the different approaches once more emphasises the extraordinary sensitivity of photoacoustic spectroscopy. To the best of the author's knowledge, the LODs (3σ) of the UV LED based photoacoustic measurement in typical breath conditions (12.5 ppbV) and the LOD of the QCL measurement (0.79 ppbV) provide two world records. First, regarding photoacoustic acetone detection using an UV LED and second, in view of other published results for photoacoustic acetone detection in general.}, language = {en} }