Publications

A selected list of publications from the IRTG researchers.

2021

  1. Graz, I. M., & Rosset, S. (2021). Stretchable electrodes for highly flexible electronics. Organic Flexible Electronics, 479--500. https://doi.org/10.1016/b978-0-12-818890-3.00016-3
  2. Maier, B., Stach, M., & Mehl, M. (2021). Real-Time, Dynamic Simulation of Deformable Linear Objects with Friction on a 2D Surface. In J. Billingsley & P. Brett (Eds.), Mechatronics and Machine Vision in Practice 4 (pp. 217--231). Springer International Publishing. https://doi.org/10.1007/978-3-030-43703-9_18
  3. Totounferoush, A., Simonis, F., Uekermann, B., & Schulte, M. (2021). Efficient and Scalable Initialization of Partitioned Coupled Simulations with preCICE. Algorithms, 14(6), Article 6. https://doi.org/10.3390/a14060166
  4. Wnuk, M., Jaensch, F., Tomzik, D. A., Chen, Z., Terfurth, J., Kandasamy, S., Shahabi, J., Garrett, A., Mahmoudinezhad, M. H., Csiszar, A., Xu, W. L., Röhrle, O., & Verl, A. (2021). Challenges in Robotic Soft Tissue Manipulation -- Problem Identification Based on an Interdisciplinary Case Study of a Teleoperated Drawing Robot in Practice. In J. Billingsley & P. Brett (Eds.), Mechatronics and Machine Vision in Practice 4 (pp. 245--262). Springer International Publishing. https://doi.org/10.1007/978-3-030-43703-9_20
  5. Wnuk, M., Hinze, C., Zürn, M., Pan, Q., Lechler, A., & Verl, A. (2021, November). Tracking Branched Deformable Linear Objects With Structure Preserved Registration by Branch-wise Probability Modification. 2021 IEEE 27th International Conference on Machatronics and Machine Vision in Practice.
  6. Zhang, Q., Xu, P., Zhang, Z. S., Strommel, M., & Verl, A. (2021). Discussion of Soft Tissue Manipulation for the Harvesting of Ovine Offal (J. Billingsley, Ed.). Springer, Germany.
  7. Zürn, M., Wnuk, M., Hinze, C., Lechler, A., Verl, A., & Xu, W. (2021). Kinematic Trajectory Following Control For Constrained Deformable Linear Objects. 2021 IEEE 17th International Conference on Automation Science and Engineering (CASE), 1701–1707. https://doi.org/10.1109/CASE49439.2021.9551613

2020

  1. Ali, S. J. V., Cheng, L. K., & Xu, P. (2020). Soft Medical Robots-Revamping the Diagnostics and Therapeutics Technologies. Journal of Engineering and Science in Medical Diagnostics and Therapy, 3(3), Article 3. https://doi.org/10.1115/1.4047285
  2. Alla, A., Haasdonk, B., & Schmidt, A. (2020). Feedback control of parametrized PDEs via model order reduction and dynamic programming principle. Advances in Computational Mathematics, 46(1), Article 1. https://doi.org/10.1007/s10444-020-09744-8
  3. Ates, F., Brandenburg, J. E., & Kaufman, K. R. (2020). Effects of Selective Dorsal Rhizotomy on Ankle Joint Function in Patients With Cerebral Palsy. Frontiers in Pediatrics, 8(75), Article 75. https://doi.org/10.3389/fped.2020.00075
  4. Berberich, J., Köhler, J., Müller, M. A., & Allgöwer, F. (2020). Data-driven model predictive control with stability and robustness guarantees. IEEE Transactions on Automatic Control. https://doi.org/10.1109/tac.2020.3000182
  5. Berberich, J., Köhler, J., Müller, M. A., & Allgöwer, F. (2020). Data-Driven Tracking MPC for Changing Setpoints. Proc.\ 21st IFAC World Congress.
  6. Berberich, J., Köhler, J., Müller, M. A., & Allgöwer, F. (2020). Robust constraint satisfaction in data-driven MPC. https://arxiv.org/abs/2003.06808
  7. Bhattacharya, D., Ali, S. J. V., Cheng, L. K., & Xu, P. (2020). RoSE: A Robotic Soft Esophagus for Endoprosthetic Stent Testing. Soft Robotics. https://doi.org/10.1089/soro.2019.0205
  8. Brandes, J. (2020). Simulation based control of an underactuated kinematic chain.
  9. Braun, H. (2020). Model Estimation and Model Predictive Control of Flexible Loads.
  10. Buchfink, P., Haasdonk, B., & Rave, S. (2020). PSD-Greedy Basis Generation for Structure-Preserving Model Order Reduction of Hamiltonian Systems. Algoritmy 2020 Conference Proceedings, 151--160. http://www.iam.fmph.uniba.sk/amuc/ojs/index.php/algoritmy/article/view/1577
  11. Cheuk, M. L., Tang, E. J. L. P., HajiRassouliha, A., Han, J.-C., Nielsen, P. M. F., & Taberner, A. J. (2020). A Method for Markerless Tracking of the Strain Distribution of Actively Contracting Cardiac Muscle Preparations. Experimental Mechanics. https://doi.org/10.1007/s11340-020-00646-w
  12. Choisne, J., Fourrier, N., Handsfield, G., Signal, N., Taylor, D., Wilson, N., Stott, S., & Besier, T. F. (2020). An unsupervised data-driven model to classify gait patterns in children with cerebral palsy. Journal of Clinical Medicine, 9(5), Article 5. https://doi.org/10.3390/jcm9051432
  13. Debera, P. (2020). Comparison of path planning algorithms for a 7-axis lightweight robot.
  14. Dwivedi, A., Lara Aguayo, J. E., Cheng, L. K., Paskaranandavadivel, N., & Liarokapis, M. (2020). High-Density Electromyography Based Control of Robotic Devices: On the Execution of Dexterous Manipulation Tasks. Interfaces, 18, 19. https://doi.org/10.1109/icra40945.2020.9196629
  15. Echle, A.and Gong, Y., Terfurth, J., Schmid, M., & Parspour, N. (2020). FEA Based Comparison of BLDC and BLAC Modes for an Axial Flux Motor with Trapezoidal BEMF. 46th Annual Conference of the IEEE Industrial Electronics Society.
  16. Emamy, N., Litty, P., Klotz, T., Mehl, M., & Röhrle, O. (2020). POD-DEIM model order reduction for the monodomain reaction-diffusion sub-model of the neuro-muscular system. IUTAM Symposium on Model Order Reduction of Coupled Systems, Stuttgart, Germany, May 22--25, 2018, 177--190. https://doi.org/10.1007/978-3-030-21013-7_13
  17. Fernandez, J., Dickinson, A., & Hunter, P. (2020). Population based approaches to computational musculoskeletal modelling. Biomechanics and Modeling in Mechanobiology, 19(4), Article 4. https://doi.org/10.1007/s10237-020-01364-x
  18. Garrett, A. S., Loiselle, D. S., Han, J.-C., & Taberner, A. J. (2020). Compensating for changes in heart muscle resting heat production in a microcalorimeter. 2020 42nd Annual International Conference of the IEEE Engineering in Medicine & Biology Society (EMBC), 2557--2560. https://doi.org/10.1109/embc44109.2020.9175474
  19. Gerez, L., Dwivedi, A., & Liarokapis, M. (2020). A Hybrid, Soft Exoskeleton Glove Equipped with a Telescopic Extra Thumb and Abduction Capabilities. IEEE International Conference on Robotics and Automation (ICRA). https://doi.org/10.3389/fnbot.2019.00091
  20. Haasdonk, B., Wenzel, T., Santin, G., & Schmitt, S. (2020). Biomechanical surrogate modelling using stabilized vectorial greedy kernel methods. CoRR, abs/2004.12670. https://arxiv.org/abs/2004.12670
  21. Handsfield, G. le, Greiner, J., Madl, J., Rog-Zielinska, E., Holville, E., Vanwanseele, B., & Shim, V. (2020). Achilles Subtendon Structure and Behavior As Evidenced from Tendon Imaging and Computational Modeling. Frontiers in Sports and Active Living, 2, 70. https://doi.org/10.3389/fspor.2020.00070
  22. Hinze, C. (2020). Guide: Get the Franka Emika Panda running in C++. https://github.com/chhinze/panda_tutorial
  23. Hinze, C., Wnuk, M., Zürn, M., Lechler, A., & Verl, A. (2020). Daten-integrierte Simulation: Lokalisierung biegeschlaffer Bauteile durch 3D-Stereovision.
  24. Hinze, C., Zürn, M., Wnuk, M., Lechler, A., & Verl, A. (2020). Nonlinear Trajectory Control for Deformable Linear Objects based on Physics Simulation. IECON 2020 The 46th Annual Conference of the IEEE Industrial Electronics Society, 310–316. https://doi.org/10.1109/IECON43393.2020.9254923
  25. Hussan, J. R., & Hunter, P. J. (2020). Comfort Simulator: A Software Tool to Model Thermoregulation and Perception of Comfort. Journal of Open Research Software, 8. https://doi.org/10.5334/jors.288
  26. Illenberger, P. K., Rosset, S., Madawala, U. K., & Anderson, I. A. (2020). The integrated self priming circuit: an autonomous electrostatic energy harvester with voltage boosting. IEEE Transactions on Industrial Electronics, 1--1. https://doi.org/10.1109/tie.2020.3003591
  27. Jaung, R., Varghese, C., Lin, A. Y., Paskaranandavadivel, N., Du, P., Rowbotham, D., Dinning, P., O’Grady, G., & Bissett, I. (2020). High-Resolution Colonic Manometry Pressure Profiles Are Similar in Asymptomatic Diverticulosis and Controls. Digestive Diseases and Sciences. https://doi.org/10.1007/s10620-020-06320-4
  28. Jayaneththi, V., Aw, K., & McDaid, A. (2020). Wireless manipulation using magnetic polymer composites. Smart Materials and Structures, 29(3), Article 3. https://doi.org/10.1088/1361-665x/ab6691
  29. Kamat, A. A., Paskaranandavadivel, N., Alighaleh, S., Cheng, L. K., & Angeli, T. R. (2020). Effects of Electrode Diameter and Contact Material on Signal Morphology of Gastric Bioelectrical Slow Wave Recordings. Annals of Biomedical Engineering, 1--12. https://doi.org/10.1007/s10439-020-02457-5
  30. Killen, B. A., da Luz, S. B., Lloyd, D. G., Carleton, A. D., Zhang, J., Besier, T. F., & Saxby, D. J. (2020). Automated creation and tuning of personalised muscle paths for OpenSim musculoskeletal models of the knee joint. Biomechanics and Modeling in Mechanobiology. https://doi.org/10.1007/s10237-020-01398-1
  31. Köhler, J., Kötting, P., Soloperto, R., Allgöwer, F., & Müller, M. A. (2020). A robust adaptive model predictive control framework for nonlinear uncertain systems. Int. J. Robust and Nonlinear Control, 1–25.
  32. Köhler, J., Müller, M. A., & Allgöwer, F. (2020). A nonlinear model predictive control framework using reference generic terminal ingredients. IEEE Trans. Automat. Control, 65(8), Article 8.
  33. Köhler, J., Müller, M. A., & Allgöwer, F. (2020). A nonlinear tracking model predictive control scheme for unreachable dynamic target signals. Automatica, 118, 109030.
  34. Köhler, J., Müller, M. A., & Allgöwer, F. (2020). Periodic optimal control of nonlinear constrained systems using economic model predictive control. J. Proc. Contr., 92, 185–201.
  35. Köhler, J., Schwenkel, L., Koch, A., Berberich, J., Pauli, P., & Allgöwer, F. (2020). Robust and optimal predictive control of the COVID-19 outbreak. Annual Reviews in Control.
  36. Köhler, J., Soloperto, R., Müller, M. A., & Allgöwer, F. (2020). A computationally efficient robust model predictive control framework for uncertain nonlinear systems. IEEE Trans. Automat. Control.
  37. Köhler, J., Kötting, P., Soloperto, R., Allgöwer, F., & Müller, M. A. (2020). A robust adaptive model predictive control framework for nonlinear uncertain systems. International Journal of Robust and Nonlinear Control. https://doi.org/10.1002/rnc.5147
  38. Köhler, J., Müller, M. A., & Allgöwer, F. (2020). Implicit solutions to constrained nonlinear output regulation using MPC. Proc.\ 59th IEEE Conf.\ Decision and Control (CDC), 4604–4609.
  39. Köhler, J., Müller, M. A., & Allgöwer, F. (2020). Constrained nonlinear output regulation using model predictive control. IEEE Transactions on Automatic Control. https://arxiv.org/pdf/2005.12413.pdf
  40. Köhler, J., Müller, M. A., & Allgöwer, F. (2020). A nonlinear model predictive control framework using reference generic terminal ingredients. IEEE Transactions on Automatic Control. https://doi.org/10.1109/tac.2019.2949350
  41. Köhler, J., Müller, M. A., & Allgöwer, F. (2020). Implicit solutions to constrained nonlinear output regulation using MPC. Proc. 59th Annual Conference on Decision and Control (CDC).
  42. Köhler, J., Müller, M. A., & Allgöwer, F. (2020). A nonlinear tracking model predictive control scheme for dynamic target signals. Automatica, 118, 109030. https://doi.org/10.1016/j.automatica.2020.109030
  43. Köhler, J., Schwenkel, L., Koch, A., Berberich, J., Pauli, P., & Allgöwer, F. (2020). Robust and optimal predictive control of the COVID-19 outbreak. https://arxiv.org/abs/2005.03580
  44. Köhler, J., Soloperto, R., Müller, M. A., & Allgöwer, F. (2020). A computationally efficient robust model predictive control framework for uncertain nonlinear systems. IEEE Transactions on Automatic Control. https://doi.org/10.1109/TAC.2020.2982585
  45. Lara Aguayo, J. E., Paskaranandavadivel, N., & Cheng, L. K. (2020). HD-EMG Electrode Count and Feature Selection Influence on Pattern-Based Movement Classification Accuracy. 2020 42nd Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC), 4787--4790. https://doi.org/10.1109/embc44109.2020.9175210
  46. Lindner, F., Totounferoush, A., Mehl, M., Uekermann, B., Pour, N. E., Krupp, V., Roller, S., Reimann, T., C. Sternel, D., Egawa, R., Takizawa, H., & Simonis, F. (2020). ExaFSA: Parallel Fluid-Structure-Acoustic Simulation. Software for Exascale Computing - SPPEXA 2016-2019, 271--300. https://doi.org/10.1007/978-3-030-47956-5
  47. Lotz, J. (2020). Design of a flexible real-time control method for a lightweight robot based on PREEMPT\_RT-Linux.
  48. Mahmoudinezhad, M., Anderson, I. A., & Rosset, S. (2020). Interdigitated sensor based on a silicone foam for subtle robotic manipulation. Submitted to Macromolecular Rapid Communications.
  49. Mahmoudinezhad, M. H., Anderson, I., & Rosset, S. (2020). Compressible dielectric elastomer sensor for robotic application. In Second International Congress on Progress in Tissue Engineering and Regenerative medicine (Vol. 11375, p. 1137527). International Society for Optics and Photonics. https://doi.org/10.1117/12.2558386
  50. Mahmoudinezhad, M. H., Rosset, S., & Anderson, I. (2020). Interdigitated soft capacitive compression sensor for robotic Application. Soft Robotics Journal.
  51. Meinel, J., Vorobyov, V., Yavkin, B., Dasari, D., Sumiya, H., Onoda, S., Isoya, J., & Wrachtrup, J. (2020). Heterodyne Sensing of Microwaves with a Quantum Sensor. ArXiv Preprint ArXiv:2008.10068. https://arxiv.org/pdf/2008.09716.pdf
  52. Mesmer, P., Neubauer, M., Lechler, A., & Verl, A. (2020). Drive-Based Vibration Damping Control for Robot Machining. IEEE Robotics and Automation Letters, 5(2), Article 2. https://doi.org/10.1109/lra.2019.2960723
  53. Mordhorst, M. (2020). Towards a fast and stable dynamic skeletal muscle model.
  54. Moretti, G., Rosset, S., Vertechy, R., Anderson, I., & Fontana, M. (2020). A Review of Dielectric Elastomer Generator Systems. Advanced Intelligent Systems, 2(10), Article 10. https://doi.org/10.1002/aisy.202000125
  55. Mostashiri, N. (2020). An In-Vitro Study of the Temporomandibular Reaction Forces through Motion-Capturing and Robotics.
  56. Mostashiri, N., Dhupia, J. S., Verl, A. W., & Xu, P. (2020). Disturbance Observer-Based Controller for Mimicking Mandibular Motion and Studying Temporomandibular Joint Reaction Forces by a Chewing Robot. 2020 IEEE/ASME International Conference on Advanced Intelligent Mechatronics (AIM), 1042--1047. https://doi.org/10.1109/aim43001.2020.9158891
  57. Nejati, M., Penhall, N., Williams, H., Bell, J., Lim, J., Ahn, H. S., & MacDonald, B. (2020). Kiwifruit detection in challenging conditions. https://arxiv.org/pdf/2006.11729.pdf
  58. Nickerson, D. P., Lundeng\aard, K., Watts, J., Porter, S., Yu, T., Nielsen, P., & Hunter, P. (2020). Physiome: Encouraging Reproducible and FAIR Computational Modelling. The FASEB Journal, 34(S1), Article S1. https://doi.org/10.1096/fasebj.2020.34.s1.04897
  59. Noble, D., & Hunter, P. (2020). How to link genomics to physiology through epigenomics. Epigenomics, 12(4), Article 4. https://doi.org/10.2217/epi-2020-0012
  60. Nubert, J., Köhler, J., Berenz, V., Allgöwer, F., & Trimpe, S. (2020). Safe and Fast Tracking on a Robot Manipulator: Robust MPC and Neural Network Control. IEEE Robotics and Automation Letters, 5(2), Article 2.
  61. Nurbert, J., Köhler, J., Berenz, V., Allgöwer, F., & Trimpe, S. (2020). Safe and Fast Tracking on a Robot Manipulator: Robust MPC and Neural Network Control. IEEE Robotics and Automation Letters. https://doi.org/10.1109/lra.2020.2975727
  62. Pace, F. D., Gorjup, G., Bai, H., Sanna, A., Liarokapis, M., & Billinghurst, M. (2020, November). Assessing the Suitability and Effectiveness of Mixed Reality Interfaces for Accurate Robot Teleoperation. 26th ACM Symposium on Virtual Reality Software and Technology. https://doi.org/10.1145/3385956.3422092
  63. Pan, Q. (2020). Method for localization and state estimation of branched deformable linear objects in real time (working title).
  64. Paskaranandavadivel, N., Avci, R., Nagahawatte, N., Farajidavar, A., & Cheng, L. K. (2020). Electroceutical approaches for Gastroparesis in ‘Obesity and Diabetes: New Surgical and Nonsurgical Approaches.’
  65. Quigan, S. (2020). Real-time capable method for estimating the state of linear deformable objects from point cloud data.
  66. Rosenfelder, M., Köhler, J., & Allgöwer, F. (2020). Stability and performance in transient average constrained economic MPC without terminal constraints. Proc.\ 21st IFAC World Congress.
  67. Rosenfelder, M., Köhler, J., & Allgöwer, F. (2020). Stability and performance in transient average constrained economic MPC without terminal constraints. Proc.\ 21st IFAC World Congress.
  68. Saini, H., Ackland, D. C., Gong, L., Cheng, L. K., & Röhrle, O. (2020). Occlusal load modelling significantly impacts the predicted tooth stress response during biting: a simulation study. Computer Methods in Biomechanics and Biomedical Engineering, 1--10. https://doi.org/10.1080/10255842.2020.1711886
  69. Santin, G., & Haasdonk, B. (2020). Kernel Methods for Surrogate Modelling. Model Order Reduction, 1.
  70. Sawodny, J. (2020). Identification of dynamics parameters of deformable linear objects for simulation driven robotic manipulation.
  71. Scheufele, K., Subramanian, S., Mang, A., Biros, G., & Mehl, M. (2020). Image-driven biophysical tumor growth model calibration. SIAM Journal on Scientific Computing, 42(3), Article 3. https://doi.org/10.1137/19m1275280
  72. Schlatter, S., Grasso, G., Rosset, S., & Shea, H. (2020). Inkjet Printing of Complex Soft Machines with Densely Integrated Electrostatic Actuators. Advanced Intelligent Systems, 2000136. https://doi.org/10.1002/aisy.202000136
  73. Schlüter, H., & Allgöwer, F. (2020). A Constraint-Tightening Approach to Nonlinear Stochastic Model Predictive Control under General Bounded Disturbances. Proc. 21th IFAC World Congress, 53(2), Article 2. https://doi.org/10.1016/j.ifacol.2020.12.518
  74. Schlüter, H., & Allgöwer, F. (2020). A Constraint-Tightening Approach to Nonlinear Stochastic Model Predictive Control for Systems under General Disturbances. In Proc. 21st IFAC World Congress. IFAC. https://arxiv.org/abs/1912.01946
  75. Soloperto, R., Köhler, J., & Allgöwer, F. (2020). Augmenting MPC schemes with active learning: Intuitive tuning and guaranteed performance. IEEE Control Systems Letters, 4(3), Article 3. https://doi.org/10.1109/lcsys.2020.2983384
  76. Terfurth, J., Schmid, M., & Parspour, N. (2020). Planar Aligned Transverse Flux Machine with Integrated Reduction Gear. In 2020 IEEE International Conference on Electrical Machines (ICEM).
  77. Tomalka, A., Weidner, S., Hahn, D., Seiberl, W., & Siebert, T. (2020). Cross-Bridges and Sarcomeric Non-cross-bridge Structures Contribute to Increased Work in Stretch-Shortening Cycles. Frontiers in Physiology, 11, 921. https://doi.org/10.3389/fphys.2020.00921
  78. Venkatasubramanian, J., Köhler, J., Berberich, J., & Allgöwer, F. (2020). Robust Dual Control based on Gain Scheduling. Proc. 59th Annual Conference on Decision and Control (CDC).
  79. Vorobyov, V., Zaiser, S., Abt, N., Meinel, J., Dasari, D., Neumann, P., & Wrachtrup, J. (2020). Quantum Fourier transform for quantum sensing. https://arxiv.org/abs/2008.09716
  80. Walter, J., Günther, M., Haeufle, D. F. B., & Schmitt, S. (2020). Synthesising biological movement of muscle-driven systems: a geometry- and actuator-based control architecture. Biological Cybernetics, (Submitted).
  81. Walter, J. R., Saini, H., Maier, B., Mostashiri, N., Aguayo, J. L., Zarshenas, H., Hinze, C., Shuva, S., Köhler, J., Sahrmann, A. S., Chang, C., Csiszar, A., Galliani, S., Cheng, L. K., & Röhrle, O. (2020). Comparative Study of a Biomechanical Model-based and Black-box Approach for Subject-Specific Movement Prediction.
  82. Wang, L., Malik, A., Roop, P. S., Cheng, L. K., Paskaranandavadivel, N., & Ai, W. (2020). A novel approach for model-based design of gastric pacemakers. Computers in Biology and Medicine, 116, 103576. https://doi.org/10.1016/j.compbiomed.2019.103576
  83. Wirzberger, M., Borst, J. P., Krems, J. F., & Rey, G. D. (2020). Memory-related cognitive load effects in an interrupted learning task: A model-based explanation. Trends in Neuroscience and Education. https://doi.org/10.1016/j.tine.2020.100139
  84. Wnuk, M. (2020). Roboterprogrammierung für weiche Bauteile. https://www.konstruktion-entwicklung.de/roboterprogrammierung-fuer-weiche-bauteile
  85. Wnuk, M. (2020). grk2198 Soft Tissue Robotics: Introduction to Dynamics Animation and Robotics Toolbox (DART). https://github.com/markuswnuk91/tutorial_on_DART
  86. Wnuk, M., Hinze, C., Lechler, A., & Verl, A. (2020). Kinematic Multibody Model Generation of Deformable Linear Objects from Point Clouds. In 2020 International Conference on Intelligent Robots and Systems (IROS).
  87. Wnuk, M., Hinze, C., Zürn, M., Lechler, A., & Verl, A. (2020). Demonstrator zur Handhabung biegeschlaffer Objekte.
  88. Yeung, S., Fernandez, J., Handsfield, G., Walker, C., Besier, T., & Zhang, J. (2020). Rapid muscle volume prediction using anthropometric measurements and population-derived statistical models. Biomechanics and Modeling in Mechanobiology, 19(4), Article 4. https://doi.org/10.1007/s10237-019-01243-0
  89. Zarshenas, H., Ruddy, B., Kempa-Liehr, A., & Besier, T. (2020). Ankle torque forecasting using time-delayed neural networks. 43rd Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC). https://doi.org/10.1109/embc44109.2020.9175376

2019

  1. Aghababaie, Z., Chan, C. A., Paskaranandavadivel, N., Beyder, A., Farrugia, G., Asirvatham, S., O’Grady, G., Cheng, L. K., & Angeli, T. R. (2019). Feasibility of High-Resolution Electrical Mapping for Characterizing Conduction Blocks Created by Gastric Ablation. Conf Proc IEEE Eng Med Biol Soc, 2019, 170–173. https://doi.org/10.1109/EMBC.2019.8856406
  2. Alighaleh, S., Cheng, L. K., Angeli, T. R., Amiri, M., Sathar, S., O’Grady, G., & Paskaranandavadivel, N. (2019). A Novel Gastric Pacing Device to Modulate Slow Waves and Assessment by High-Resolution Mapping. IEEE Trans Biomed Eng, 66(10), Article 10. https://doi.org/10.1109/TBME.2019.2896624
  3. Avci, R., Paskaranandavadivel, N., Calder, S., Du, P., Bradshaw, L. A., & Cheng, L. K. (2019). Source localization for gastric electrical activity using simulated magnetogastrographic data. Conf Proc IEEE Eng Med Biol Soc, 2019, 2336–2339. https://doi.org/10.1109/EMBC.2019.8857384
  4. Bannwarth, J. X., Jeremy Chen, Z., Stol, K. A., MacDonald, B. A., & Richards, P. J. (2019). Aerodynamic Force Modeling of Multirotor Unmanned Aerial Vehicles. AIAA Journal, 57(3), Article 3. https://doi.org/10.2514/1.j057165
  5. Brunner, F. D., Heemels, W. P. M. H., & Allgöwer, F. (2019). Event-triggered and self-triggered control for linear systems based on reachable sets. Automatica, 101, 15--26. https://doi.org/10.1016/j.automatica.2018.11.035
  6. Buchfink, P., Bhatt, A., & Haasdonk, B. (2019). Symplectic Model Order Reduction with Non-Orthonormal Bases. Mathematical and Computational Applications, 24(2), Article 2. https://doi.org/10.3390/mca24020043
  7. Chan, C. A., Aghababaie, Z., Paskaranandavadivel, N., Cheng, L. K., & Angeli, T. R. (2019). Methods for Visualization of Gastric Endoscopic Mapping Data From Three-Dimensional, Non-Uniform Electrode Arrays. Conf Proc IEEE Eng Med Biol Soc, 2019, 2222–2225. https://doi.org/10.1109/EMBC.2019.8857158
  8. Chang, C. M., Gerez, L., Elangovan, N., Zisimatos, A., & Liarokapis, M. (2019). On Alternative Uses of Structural Compliance for the Development of Adaptive Robot Grippers and Hands. Frontiers in Neurorobotics, 13, 91. https://doi.org/10.3389/fnbot.2019.00091
  9. Chang, C.-M., Gerez, L., Elangovan, N., Zisimatos, A., & Liarokapis, M. (2019). Unconventional Uses of Structural Compliance in Adaptive Hands. 2019 28th IEEE International Conference on Robot and Human Interactive Communication (RO-MAN), 1--7. https://doi.org/10.1109/ro-man46459.2019.8956340
  10. Cherian Abraham, A., Cheng, L. K., Angeli, T. R., Alighaleh, S., & Paskaranandavadivel, N. (2019). Dynamic slow-wave interactions in the rabbit small intestine defined using high-resolution mapping. Neurogastroenterol Motil, 31(9), Article 9. https://doi.org/10.1111/nmo.13670
  11. Chigateri, N. G., Kerse, N., & MacDonald, B. (2019, June). Novel Algorithm for Identification and Differentiation of Shuffling from Walking. 2019 IEEE International Conference on Healthcare Informatics (ICHI). https://doi.org/10.1109/ichi.2019.8904831
  12. Csiszar, A. (2019). AI for Control Technology. In AI Forum Stuttgart.
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