Jahr | Name |
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2023 |
Reporter emission multiplexing in digital PCRs (REM-dPCRs)The Analyist. Authors: Silvia Calabrese, Anja M. Markl, Maximilian Neugebauer, Stefanie J. Krauth, Nadine Borst, Felix von Stetten and Michael Lehnert Kurzfassung einblendenDigital PCRs (dPCRs) are widely used methods for the detection and quantification of rare abundant sequences relevant to fields such as liquid biopsy or oncology. In order to increase the information content and save valuable sample materials, there is a significant need for digital multiplexing methods that are easy to establish, analyse, and interpret, and ideally allow the usage of existing lab equipment. Read the full abstract here: https://pubs.rsc.org/en/content/articlelanding/2023/an/d3an00191a |
2023 |
Carbon black supported Ag nanoparticles in zero-gap CO2 electrolysis to CO enabling high mass activityK. Seteiz, J. N. Häberlein, P. A. Heizmann, J. Disch, S. Vierrath RSC Advances 27, 2023, doi: 10.1039/D3RA03424K |
2023 |
A Comparative Study of Conditioning Methods for Hydrocarbon-Based Proton-Exchange Membrane Fuel Cells for Improved PerformanceH. Nguyen, J. Stiegeler, H. Liepold, C. Schwarz, S. Vierrath, M. Breitwieser Energy Technol. 2023, 2300202, doi: 10.1002/ente.202300202 |
2023 |
394 Gene expression based molecular test proves clinical validity as diagnostic aid for the differential diagnosis of psoriasis and eczema in formalin fixed and paraffin embedded tissueF. Fischer, A. Doll, D. Uereyener, S. Roenneberg, C. Hillig, L. Weber, V. Hackert, P. Seiringer, J. Thomas, P. Anand, L. Graner, F. Schlenker, R. Zengerle, M. Jargosch, F. J. Theis, C. B. Schmidt-Weber, T. Biedermann, M. Howell, K. Reich, M. Menden, N. Garzorz-Stark, F. Lauffer, S. Eyerich British Journal of Dermatology, Volume 188 (3), doi: 10.1093/bjd/ljad162.019 |
2023 |
DropletAI: Deep Learning-Based Classification of Fluids with Different Ohnesorge Numbers during Non-Contact DispensingP. Sardana, M. Zolfaghari, G. Miotto, R. Zengerle, T. Brox, P. Koltay, S. Kartmann Fluids 2023, 8, 183, doi: 10.3390/fluids8060183 |
2023 |
Autonome visuelle, industrielle Roboterinteraktion durch Künstliche Intelligenz (AutoVikki)P. Selle Kurzversion des Abschlussberichts zum IGF-Vorhaben Nr. 20896 BG "AutoVikki" Kurzfassung einblendenAutoVikki vereint innovative Algorithmen und Ansätze zur automatisierten (Nach-) Bearbeitung individueller (oder natürlichen) Industrieprodukten. Die wesentliche Innovation besteht in der Kombination mehrerer 3D-Kameras und einer Künstlichen Intelligenz (KI), sodass sensorische und kollaborierende Robotergreifer sehr variable und feingranulare Objekte analysieren, klassifizieren, greifen, bearbeiten und wieder absetzen können. Es kommen aktuelle Lösungsansätze aus der Deep-Learning-Forschung zum Einsatz, wie Generative Adversarial Networks, Domain Randomization und Federated Learning, um mit möglichst wenig Trainingsdaten die KI für die Struktur- und Oberflächenanalyse, sowie für das Greifen und das Bearbeiten des Objektes zu trainieren. Für die Kommunikation zwischen den Komponenten der Roboterzelle werden eine zentrale Plattform sowie flexible Schnittstellen entwickelt. |
2023 |
Modellbasiertes reaktives Fügen zur Erhöhung der Prozesssicherheit und -zuverlässigkeit (MoReBond)A. Schumacher Abschlussbericht zum IGF-Vorhaben Nr. 20896 BG Kurzfassung einblendenDas Ziel dieses Forschungsvorhabens bestand darin, die reaktive Fügetechnologie durch Erhöhung der Prozesssicherheit und -zuverlässigkeit für industrielle Anwendungen zugänglicher zu machen. Weiterhin sollen Einstiegshürden in die reaktive Fügetechnologie für Kleine und Mittelständische Unternehmen (KMU) abgebaut werden. Die mathematische Modellierung und numerische Simulation des reaktiven Fügeprozesses und der reaktiven Multischichtsysteme (RMS) trägt dazu bei, die Technologie „maßgeschneidert“ an verschiedene Anwendungsfälle anpassen zu können, ohne aufwändige, experimentelle Parameterstudien ausführen zu müssen. Der folgende Bericht fasst die wichtigsten erzielten Ergebnisse, aufgeteilt nach den einzelnen Arbeitspaketen, zusammen. |
2023 |
Additive Fertigung, Laserdirektstrukturierung und chemische Metallisierung von Duroplasten: Material- und Prozessentwicklung (FLaeDle)Tobias Vieten, Dr. Kerstin Gläser Ziel des Projekts ist die Herstellung von dreidimensionalen Schaltungsträgern (mechatronic integrated device, MID) über das additive Fertigungsverfahren digital light processing. |
2023 |
Intelligentes Monitoringsystem zur Steigerung der Prozessqualität und Ressourceneffizienz in gewerblichen Wäschereien (IMPRESS) |
2023 |
Interfacing centrifugal microfluidics with linear-oriented 8-tube strips and multichannel pipettes for increased throughput of digital assaysY.-K. Lai, Y.-T. Kao, J. Hess, S. Calabrese, F. von Stetten, N. Paust Lab on a Chip …, doi: 10.1039/d3lc00339f |
2023 |
Alternative and facile production pathway towards obtaining high surface area PtCo/C intermetallic catalysts for improved PEM fuel cell performanceP. A. Heizmann, H Nguyen, M. von Holst, A. Fischbach, M. Kostelec, F. J. Gonzalez Lopez, M. Bele, L. Pavko, T. Đukić, M. Šala, F. Ruiz-Zepeda, C. Klose, M. Gatalo, N. Hodnik, S. Vierrath, M. Breitwieser RSC Adv., 2023,13, 4601-4611, doi: 10.1039/D2RA07780A |
2023 |
Nanobead handling on a centrifugal microfluidic LabDisk for automated extraction of cell-free circulating DNA with high recovery ratesF. Schlenker, P. Juelg, J. Lüddecke, N. Paust, R. Zengerle, T. Hutzenlaub Analyst, 2023,148, 932-941, doi: 10.1039/D2AN01820A |
2022 |
Simulation framework for reflective PPG signal analysis depending on sensor placement and wavelengthM. Reiser, A. Breidenassel, O. Amft IEEE-EMBS International Conference on Wearable and Implantable Body Sensor Networks, 27. – 30. September 2022, Ioannina, Griechenland Kurzfassung einblendenWe analyse the influence of reflective photoplethysmography (PPG) sensor positioning relative to blood vessels. A voxel based Monte Carlo simulation framework was developed and validated to simulate photon-tissue interactions. An anatomical model comprising a multi-layer skin description with a blood vessel is presented to simulate PPG sensor positioning at the volar wrist. The simulation framework was validated against standard test cases reported in literature. The blood vessel was considered in regular and dilated states. Simulations were performed with 10 8 photon packets and repeated five times for each condition, including wavelength, relative position of PPG sensor and vessel, and vessel dilation state. Statistical weights were associated to photon packets to represent absorption and scattering effects. A symmetrical arrangement of the PPG sensor around the blood vessel showed the maximum AC …
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2022 |
Proximity-based Eating Event Detection in Smart Eyeglasses with Expert and Data ModelsA. Saphala, R. Zhang, O. Amft ACM International Symposium on Wearable Computers, 11. – 15. September 2022, Atlanta & Cambridge, USA Kurzfassung einblendenWe compare performances of an expert model-based approach and a data-based baseline for eating event detection using proximity sensor data of smart eyeglasses. Proximity sensors in smart eyeglasses can provide dynamic distance estimates of cyclic temporalis muscle contraction during chewing without skin contact. Our expert model is based on proximity signal preprocessing and two-threshold grid search. In contrast, baseline data models were based on One-class Support-Vector-Machines. We evaluate both models with in-lab and free-living data from 15 participants. Free-living data were obtained across one day of wearing smart eyeglasses with temple-integrated proximity sensors in unconstrained settings. Overall, the retrieval performance F1 score of the two-threshold-based algorithm for free-living data ranged between 0.6 and 0.7, and outperformed all tested SVM model configurations. While SVM …
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2022 |
Non-contact temporalis muscle monitoring to detect eating in free-living using smart eyeglassesA. Saphala, R. Zhang, T. Nam Thái, O. Amft IEEE-EMBS International Conference on Wearable and Implantable Body Sensor Networks, 27. – 30. September 2022, Ioannina, Griechenland Kurzfassung einblendenWe investigate non-contact sensing of temporalis muscle contraction in smart eyeglasses frames to detect eating activity. Our approach is based on infra-red proximity sensors that were integrated into sleek eyeglasses frame temples. The proximity sensors capture distance variations between frame temple and skin at the frontal, hair-free section of the temporal head region. To analyse distance variations during chewing and other activities, we initially perform an in-lab study, where proximity signals and Electromyography (EMG) readings were simultaneously recorded while eating foods with varying texture and hardness. Subsequently, we performed a free-living study with 15 participants wearing integrated, fully functional 3Dprinted eyeglasses frames, including proximity sensors, processing, storage, and battery, for an average recording duration of 8.3hours per participant. We propose a new chewing sequence …
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2022 |
Feasibility And Acceptability Of Wearable Sensor Placement For Young Children.: 744E. A Willis, D. Hales, F. Smith, R. Burney, M. C Rzepka, O. Amft, R. Barr, K. R Evenson, M. R Kosorok, D. S Ward Proceedings of the: Feasibility And Acceptability Of Wearable Sensor Placement For Young Children.: 744 Kurzfassung einblendenPURPOSE: To examine parent perceptions of young children’s acceptability of different methods for wearable sensor placement and the feasibility of a free-living 3 to 7-day wear protocol.
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2022 |
The Quest towards Automated Dietary Monitoring & Intervention in Free-livingO. Amft International Workshop on Multimedia Assisted Dietary Management, 10. Oktober 2022, Lisbon, Portugal Kurzfassung einblendenIn the first part of this talk, I will review the hunt for sensors that started of the field of automated dietary monitoring (ADM) and continues to play a role in shaping current research. Moreover, I will describe the eyeglasses-based sensors that we currently develop and their perspectives for free-living monitoring. Moving on, in part two, I will discuss digital twin-based co-simulation as a novel system design approach for wearable devices and their relevance for supporting machine learning algorithm development. Finally, in part three, I will extend the scope into technology-based dietary intervention, i.e., how ADM can support users in their daily life when targeting a diet change or body weight reduction. I will show examples from our work to create digital twins that model individual behavior, identify behavior changes, and interaction strategies to integrate in everyday life.
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2022 |
IMUAngle: Joint Angle Estimation with Inertial Sensors in Daily ActivitiesL. Uhlenberg, S. Hassan Gangaraju, O. Amft ACM International Symposium on Wearable Computers, 11.09. – 15.09.2022, Atlanta & Cambridge, USA Kurzfassung einblendenWe present a framework for IMU-based joint angle estimation during activities of daily living (ADL). Personalised musculoskeletal models were created from anthropometric data. Three sensor fusion algorithms were optimised to estimate orientation from IMU data and used as input for the simulation framework. Four ADLs, involving upper and lower limbs were simulated. Joint kinematics of IMU-based simulations were compared to optical marker-based simulations. Results for IMU-based simulations showed median RMSE of 0.8 − 15.5 ° for lower limbs and 1.5 − 33.9 ° for upper limbs. Median RMSE were 4.4 °, 5.8 °, 6.9 °, 6.5 ° for ankle plantarflexion, knee-, hip flexion, and hip rotation, respectively. For upper limbs, elbow flexion showed best median RMSE ∼ 3.7 °, whereas elevation angles (∼ 24.5 °) and shoulder rotation (∼ 12.5 °) performed worst. Increased RMSE at upper limbs was attributed to the degrees of freedom at the shoulder region compared to the hip. Overall, transversal plane movements (rotations) showed higher median RMSE compared to sagittal plane movements (flexion/extension). Optimisation of orientation estimators improved performance considerably depending on ADL (up to ∼ 20 °). Comparing sensor fusion algorithms, Madgwick and Mahony produced comparable joint kinematics, whereas the Extended Kalman Filter performance showed larger variability depending on the ADL. Our approach offers a realistic representation of joint kinematics and can be supported by optimising parameters of sensor fusion algorithms.
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2022 |
Reflecting on Approaches to Monitor User’s Dietary IntakeJ. Keppel, U. Gruenefeld, M. Strauss, L. Ignacio Lopera Gonzalez, O. Amft, S. Schneegass ACM International Conference on Mobile Human-Computer Interaction, 28.09. – 01.10.2022, Vancouver, Kanada Kurzfassung einblendenMonitoring dietary intake is essential to providing user feedback and achieving a healthier lifestyle. In the past, different approaches for monitoring dietary behavior have been proposed. In this position paper, we first present an overview of the state-of-the-art techniques grouped by image-and sensor-based approaches. After that, we introduce a case study in which we present a Wizard-of-Oz approach as an alternative and non-automatic monitoring method.
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2022 |
Comparison of Surface Models and Skeletal Models for Inertial Sensor Data SynthesisL. Uhlenberg, O. Amft IEEE-EMBS International Conference on Wearable and Implantable Body Sensor Networks, 27. – 30. September 2022, Ioannina, Griechenland Kurzfassung einblendenWe present a modelling and simulation framework to synthesise body-worn inertial sensor data based on personalised human body surface and biomechanical models. Anthropometric data and reference images were used to create personalised body surface mesh models. The mesh armature was aligned using motion capture reference pose and afterwards mesh and armature were parented. In addition, skeletal models were created using an established musculoskeletal dynamic modelling framework. Four activities of daily living (ADL), including upper and lower limbs were simulated with surface and skeletal models using motion capture data as stimuli. Acceleration and angular velocity data were simulated for 12 body areas of surface models and 8 body areas of skeletal models. We compared simulated inertial sensor data of both models against physical IMU measurements that were obtained simultaneously …
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