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17th International Workshop on Impedance Spectroscopy, IWIS 2024

作者： Ghoul, Bilel Barioul, Rim Hafsa, Mariem Sahnoun, Salwa Fakhfakh, Ahmed Kanoun, Olfa Chemnitz University of Technology Faculty of Electrical Engineering and Information Technology Measurement and Sensor Technology Chemnitz09126 Germany National School of Electronics and Telecommunications of Sfax Technopole of Sfax Laboratory of Signals Systems Artificial Intelligence and Networks Digital Research Centre of Sfax Ons City 3021 Tunisia Université de Sousse Ecole Nationale d'Ingénieurs de Sousse LATIS- Laboratory of Advanced Technology and Intelligent Systems Sousse4023 Tunisia

ISBN: (纸本)9798331507626

Electrical Impedance Tomography (EIT) is increasingly being used to recognize hand signs due to its internal sensing capabilities. EIT systems operate by injecting a lowamplitude electrical current into the forearm through a set of electrodes and recording the resulting voltages for signal processing. However, this method can result in high power consumption in wearable hand gesture recognition applications due to the current injection-based principle. To overcome this limitation, our investigation focuses on reducing the power consumption of EIT systems by minimizing the number of injected currents. In this study, we propose an injection reduction approach based on ambiguity analysis and the reduction of non-relevant voltage readings. As a result, the proposed method eliminates 3 out of 8 current injections, leading to a 37.5 % reduction in power consumption. This decreases energy usage by 22.5 mW per measurement for a current amplitude of 150 μ A over 10 trials. Further, acquisition time was reduced from 1 second to 0.6 seconds. The classification accuracy using the KNN classifier reached 99 % with full measurements and 96 % with reduced injections. Moreover, a comparative analysis of the reduced injections to forearm anatomy is performed. It demonstrates that bones and high-density muscle areas can affect the current flow and result in inaccurate measurements. These findings demonstrate the potential for reducing current injections in EIT to produce more energy-efficient wearable hand sign recognition systems. © 2024 IEEE.

关键词： Nearest neighbor search

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Insole Ballistocardiography for Unobtrusive Respiratory and Heart Rate Monitoring Using 3D-Printed Piezoelectric sensors

Insole Ballistocardiography for Unobtrusive Respiratory and ...

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IEEE International Symposium on Applications of Ferroelectrics (ISAF)

作者： Bastian Latsch Alexander A. Altmann Omar Ben Dali Romol Chadda Niklas Schäfer Kilian Schäfer Muhammad Bilal Khan Jan Helge Dörsam Felix Herbst Sven Suppelt Oliver Gutfleisch Mario Kupnik Measurement and Sensor Technology Group Technische Universität Darmstadt Germany Functional Materials Institute of Materials Science Technische Universität Darmstadt Germany

ISBN: (数字)9798350371901

ISBN: (纸本)9798350371918

There is a growing interest in monitoring vital signs outside of clinical settings for early detection of gradual health deterioration. Ballistocardiography (BCG) is a viable approach for unobtrusive everyday use without requiring direct skin contact. In this work we propose insole-based BCG using highly sensitive, 3D-printed ferroelectret sensors as a wearable system. We analyze the measurement data obtained from three participants in a standing, upright posture. A continuous wavelet transform is performed to filter the main frequency bands (6 to 8 Hz) in the time-frequency domain. Peak detection reveals the beat-to-beat heart rate, which agrees with the reference of a chest strap. Respiration is extracted from the heartbeat data through amplitude and frequency demodulation. Both characteristics can be fused for a breath-to-breath measurement, minimizing influence of body movements and non-respiratory arrhythmia. The heart rate variability of ± 4 beats per minute is consistent with values from the literature on respiratory sinus arrhythmia. In conclusion, the presented highly sensitive ferroelectret insole combined with appropriate signal processing is suitable for health monitoring, paving the way for unobtrusive sensor solutions.

关键词： Time-frequency analysis Wavelet domain Arrhythmia Signal processing Skin sensor systems Biomedical monitoring Heart rate variability Monitoring Wearable sensors

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Vibrotactile Phantom Sensations in Haptic Wrist Rotation Guidance

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IEEE Transactions on Haptics 2025年 PP卷 PP页

作者： Schafer, Niklas Seiler, Julian Latsch, Bastian Kupnik, Mario Beckerle, Philipp Technische Universität Darmstadt Measurement and Sensor Technology Group Darmstadt64283 Germany Friedrich-Alexander-Universität Erlangen-Nürnberg Chair of Autonomous Systems and Mechatronics Erlangen91052 Germany

Haptic motion guidance has the potential to advance assistive technologies that support humans in movement tasks. This study systematically evaluates wrist rotation guidance methods in a 2×2 repeated measures design using a wearable vibrotactile feedback device. In two tasks, we investigate the benefits of encoding the current target distance in the cue strength and conveying additional information about the target location by incorporating a tactile illusion known as phantom sensation. For a directional response task, we analyze reaction times and error rates, and for an angle targeting task, we examine rise time, settling time, and maximum overshoot of the normalized step responses. These objective criteria are complemented by subjective user ratings that assess the intuitiveness and ease of interpreting the vibrotactile cues. Feedback methods incorporating an adaptive amplitude perform significantly better in the angle targeting task compared to those using a constant amplitude. Additional improvements can be achieved by combining the adaptive amplitude with phantom sensations, including an average additional 24.3% reduction in rise time. Furthermore, more than half of the participants rate this combination as their favorite method. Altogether, the results underline the potential of incorporating phantom sensations in vibrotactile wrist guidance, thereby contributing to the advancement of wearable haptics in assistive applications. © 2025 IEEE.

关键词： Assistive technology

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Photothermal monitor for black carbon mass concentration using a fiber-coupled fabry-pérot interferometer

Photothermal monitor for black carbon mass concentration usi...

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Optics and Photonics for Sensing the Environment, E2 2021 - Part of OSA Optical sensors and Sensing Congress 2021

作者： Radeschnig, Ulrich Knoll, Markus Lang, Benjamin Bergmann, Alexander Institute of Electrical Measurement and Sensor Systems Graz University of Technology Inffeldgasse 33/I Graz8010 Austria

We present a concept for a miniaturizable black carbon monitor based on a fiber-coupled Fabry-Pérot interferometer. By means of photothermal excitation, we reach a limit of detection as low as 13 μg/m3 © 20... 详细信息

ISBN: (纸本)9781557528209

关键词： Fabry-Perot interferometers

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Robust real-time model parameter extraction in inductive spectroscopy based on Artificial Neural Networks

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IFAC-PapersOnLine 2025年第1期59卷 121-126页

作者： Frank Wendler Ahmed Yahia Kallel Jeannette Boll Birgit Awiszus Till Clausmeyer Sebastian Härtel Olfa Kanoun Professorship Measurement and Sensor Technology Chemnitz University of Technology Reichenhainer Str. 70 09126 Chemnitz Germany Professorship Forming Technology Chemnitz University of Technology Reichenhainer Str. 70 09126 Chemnitz Germany Chair of Hybrid Manufacturing Brandenburg University of Technology Konrad-Wachsmann-Allee 17 03046 Cottbus Germany

Impedance spectrum modelling requires parameter extraction by solving the corresponding inverse identification problem, for which both gradient-based and stochastic methods have been proposed. Stochastic methods are more robust and have a lower risk of getting trapped in local minima but need a long calculation time. In this study, we examine the implementation of artificial neural networks (ANNs) in solving inverse identification problems in inductance spectroscopy, contrasting their performance with robust stochastic methods. In order to overcome the shortage of a representative amount of experimental data, we propose to use the analytically based model to generate accurate enough labelled data for the training process of the ANN. The artificial data have been structured in a homogeneous and tightly spaced grid in the parameter space, thus supporting the model’s generalisation and suppressing overfitting. ANNs with varied degrees of complexity have been investigated by modifying the number of neurons and evaluated by training and comparison with stochastic parameter extraction methods. The investigation concludes that, for the presented application in inductive spectroscopy, the neural networks can provide comparable parameter extraction results with a relative deviation of 0.03 % of the parameter value and a significant reduction in runtime from 60 s to 8 ms.

关键词： Frequency domain identification measurement instrumentation Data-fusion Process observation parameter estimation Induction spectroscopy Machine learning Neural networks

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A New Method to Determine the Shear Wave Speed and Attenuation Coefficient in Phantoms for Ultrasound Shear Wave Elastography

A New Method to Determine the Shear Wave Speed and Attenuati...

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IEEE Instrumentation and measurement technology Conference

作者： Zuyuan Wang Christian Kargel School of Mechanical and Electrical Engineering University of Electronic Science and Technology of China Sichuan Chengdu China Division of Sensor Technology and Measurement Systems Institute for Measurement and Automation Bundeswehr University Munich Neubiberg Germany

Ultrasound shear wave elastography is an effective imaging method for diagnosing abnormal tissues. It can provide spatially resolved tissue information like the shear wave speed $c$ s and the attenuation coefficient a, which depend on the (health) condition of the examined tissue. In this study we investigate a new method to determine c s and $a$ by using a homogenous tissue-mimicking agar phantom and taking into account the inevitable reflection at the phantom-air boundary. The experimental data are fitted in the least-squares sense to a model that is theoretically derived and accounts for a single reflected wave. The obtained $c$ s and $a$ are then used to calculate in a rheological model-independent fashion the shear storage modulus G’ and the shear loss modulus G“, which are often used in material testing, and together fully describe the behavior of a viscoelastic material. The G’ and G“ results are compared with those obtained using a standard rotational rheometer.

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Torque Sensing with Tunable Millimeter Wave Metamaterial and a FMCW Chip 16

Torque Sensing with Tunable Millimeter Wave Metamaterial and...

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16th International Congress on Artificial Materials for Novel Wave Phenomena, Metamaterials 2022

作者： Schossmann, A. Michenthaler, C. Hammerschmidt, D. Bergmann, A. Graz University of Technology Institute of Electrical Measurement and Sensor Systems Inffeldgasse 33/I Graz8010 Austria Infineon Technologies Austria AG Siemensstraße 2 Villach9500 Austria

ISBN: (数字)9781665465847

ISBN: (纸本)9781665465847

Real-time torque sensing in power trains and robotics is still a major challenge for state of the art sensor technology. We present a new torque sensor concept based on tunable millimeter wave metamaterials. The concept is to mechanically translate torque signals into a shift of the metamaterial resonance frequency which in turn leads to a tuning of its reflection spectra. This tuning is detected using a frequency modulated continuous wave (FMCW) chip. We show the feasibility of the sensor concept by means of numerical simulations and provide the proof of concept by means of a demonstrator. It gives a measurement range from 0 N m to 7.58 N m with an accuracy ≤ 2.37 % full scale. We believe that our concept is potentially the basis for a new torque sensor technology. © 2022 IEEE.

关键词： Metamaterials

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Study of Adverse Effects on Fiber Bragg Grating sensors in Lithium-Ion Pouch Cells 27

Study of Adverse Effects on Fiber Bragg Grating Sensors in L...

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27th International Conference on Optical Fiber sensors, OFS 2022

作者： Unterkofler, Johanna Glanz, Gregor Koller, Markus Klambauer, Reinhard Bergmann, Alexander Institute of Electrical Measurement and Sensor Systems Graz University of Technology Inffeldgasse 33/I Graz8010 Austria Center for Low-Emission Transport AIT Austrian Institute of Technology GmbH Giefinggasse 2 Vienna1210 Austria

We study a fiber Bragg grating (FBG) sensor array inside lithium-ion pouch cells to measure the temperature. A comparison of the sensor response before and after embedding in a cell is performed. Several adverse effec... 详细信息

ISBN: (纸本)9781957171142

关键词： Fiber Bragg gratings

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PORTABLE ELECTROCHEMICAL sensor BASED ON MOLECULARLY IMPRINTED POLYMER FOR OXYTETRACYCLINE DETECTION 10

PORTABLE ELECTROCHEMICAL SENSOR BASED ON MOLECULARLY IMPRINT...

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10th International Symposium on Test Automation and Instrumentation, ISTAI 2024

作者： Tang, Yuxin Hu, Jingfang Wang, Linzhe Wei, Wensong Song, Yu Li, Yansheng Gao, Guowei Beijing key Laboratory of sensor Beijing Information Science & Technology University Beijing100101 China Key Laboratory of Agricultural Product Processing Ministry of Agriculture Institute of Food Science and Technology Chinese Academy of Agricultural Sciences Beijing100193 China Key Laboratory of Modern Measurement and Control Technology Ministry of Education Beijing Information Science & Technology Unive rsity Beijing100192 China Zibo Institute for Digital Agriculture and Rural Research Zibo255051 China

ISBN: (纸本)9781837242672

Reduced graphene oxide (rGO) plays a critical role in enhancing the performance of electrochemical sensors through its excellent electrical conductivity, large surface area, ease of functionalization, chemical stability, and synergy with other nanomaterials. In this paper, A novel electrochemical sensor was developed based on rGO and molecularly imprinted polymer (MIP) for detection of trace oxytetracycline (OTC) in water. The MIP/rGO composites are synthesized by in-situ electrochemical modification on a disposable screen-printed electrode (SPE). Due to the large surface area and good electron transport rate of rGO, as well as the specific recognition for TC of MIP, the sensitive determination of trace TC at MIP/rGO/SPE was realized. Linear sweep voltammetry (LSV) was performed on the sensor for the electrochemical analysis of OTC. Under optimized conditions, the peak current of MIP/rGO/SPE exhibited a good linear correlation with OTC concentration in a wide linear range (1-25 (j,mol/L), possessed a detection limit of 0.34 (j,mol/L. Spiked detection of OTC was applied for the sensor in actual water samples, with relative standard deviations (RSDs) of 93.2%-108.7%. These results indicate that the proposed MIP/rGO/SPE sensor has the ability to accurately, rapidly and selectively detect OTC in water samples. © The Institution of Engineering & technology 2024.

关键词： Reduced Graphene Oxide

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A Polynomial Curve Fitting of Bioimpedance Data for Parameter Estimation of the Cole-Impedance Model 17

A Polynomial Curve Fitting of Bioimpedance Data for Paramete...

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17th International Workshop on Impedance Spectroscopy, IWIS 2024

作者： Simic, Mitar Freeborn, Todd J. Seoane, Fernando Kanoun, Olfa University of Novi Sad Faculty of Technical Sciences Novi Sad21000 Serbia University of Alabama Department of Electrical and Computer Engineering TuscaloosaAL35401 United States Karolinska University Hospital Department of Clinical Physiology Stockholm17176 Sweden Karolinska University Hospital Department of Medical Technology Stockholm17176 Sweden University of Borås Department of Textile Technology Borås50190 Sweden Chemnitz University of Technology Measurement and Sensor Technology Chemnitz09126 Germany

ISBN: (纸本)9798331507626

The rapid advancements in technology have led to a significant increase in the number of portable and wearable devices, driving the demand for efficient and reliable methods for bioimpedance analysis suitable for compact embedded-hardware platforms. In this paper, a method for complex bioimpedance curve fitting with the second order polynomial is derived and validated with synthetic datasets as well as experimentally obtained bioimpedance. The main advantages are independence of the frequency data (which results in reduction of the dataset by 1/3), and the elimination of dependence on characteristic frequency estimation. More importantly, it is possible to estimate parameters of the Cole-impedance model (R∞, R1 and a) from obtained polynomial coefficients in a very efficient micro controller-based realization. Raspberry Pi Pico-based execution time was around 9 ms for 256 datapoints, which is more than 1000 times shorter when compared to the relevant references. Moreover, here presented method required 22.05% less flash memory and 43.64% less SRAM. Experimental bioimpedance of human volunteer was obtained using the ImpediMed SFB7 device. Relative deviations of the estimated values of the Cole-impedance model with the proposed method and BioImp software were around 5%. The proposed method's suitability for applications involving portable and cost-effective bioimpedance measurement and processing units was demonstrated by achieving a mean relative deviation of less than 2% between the fitted and measured bioimpedance of pear slices over a three-hour period. © 2024 IEEE.

关键词： Frequency estimation

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