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Impedance Spectroscopy (IWIS), International Workshop on

作者： Cherif Ouni Nour Ammar Ahmed Yahia Kallel John Horstmann Nabil Derbel Ahmed Fakhfakh Olfa Kanoun Measurement and Sensor Technology Faculty of Electrical Engineering and Information Technology Chemnitz University of Technology Chemnitz Germany Laboratory of Signals Systems Artificial Intelligence and Networks Digital Research Centre of Sfax National School of Electronics and Telecommunications of Sfax Sfax Tunisia Control and Energy Management Laboratory National Engineering School of Sfax University of Sfax Sfax Tunisia Chemnitz University of Technology Chemnitz Germany Electronic Devices of Micro and Nano Technique Faculty of Electrical Engineering and Information Technology Chemnitz University of Technology Chemnitz Germany

ISBN: (数字)9798331507626

ISBN: (纸本)9798331507633

Wearable bioimpedance spectroscopy (BIS) devices are becoming increasingly popular due to their portability and low power consumption. However, improving power efficiency remains a significant challenge. One proposed solution is to reduce the number of excitation frequencies in the stimulation signal. This study investigates how reducing the number of used frequencies affects bioimpedance spectroscopy performance through simulations using synthetic data derived from a Cole-Cole model incorporating a Constant Phase Element (CPE). Simulations were conducted at various noise levels to evaluate how noise impacts the relationship between frequency and impedance. The results indicate a correlation between the number of frequencies used in BIS and the accuracy of CPE parameter extraction. This is particularly evident for $\alpha$ parameters of 0.8 and higher. Conversely, lowering the $\alpha$ value increases errors, even when a higher number of frequencies is used.

关键词： Spectroscopy Accuracy Biological system modeling Noise Bioimpedance Frequency estimation Data models Impedance Parameter extraction Synthetic data

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Electrical Impedance Tomography Image Reconstruction with apriori Knowledge for Gesture Recognition 19

Electrical Impedance Tomography Image Reconstruction with ap...

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19th IEEE International Multi-Conference on Systems, Signals and Devices, SSD 2022

作者： Alasasfeh, Hayat Hafsa, Mariem Bader, Oumaima Ibbini, Mohammed Hasan, Sameer Kanoun, Olfa Jordan University of Science and Technology Biomedical Engineering Department Irbid Jordan Université de Sousse Ecole Nationale d'Ingénieurs de Sousse LATIS- Laboratory of Advanced Technology and Intelligent Systems Sousse4023 Tunisia Measurement and Sensor Technology Technische Universität Chemnitz Chemnitz Germany

ISBN: (数字)9781665471084

ISBN: (纸本)9781665471084

Electrical impedance tomography (EIT) reconstructs the conductivity images of an object based on the voltages and the currents at the surface of the object. Among the clinical applications of EIT thorax imaging, brain function monitoring and breast cancer screening. However, EIT suffers from a poor signal-to-noise ratio and spatial resolution. To improve the quality of reconstructed images and provide clear information about the structure, the paper proposes to include prior knowledge about the structure from MRI. The proposed techniques could be very promising with more work. To illustrate this technique in this paper, eight electrodes with the adjacent current pattern were employed in this research. For each gesture, forty data points are recorded. The Gauss-Newton and Back-Projection algorithms are used for image reconstruction with prior knowledge of the human forearm from MRI images. The resultant contours of the Forearm, Ulna, and Radius have been used to build the mesh. In the Gauss-Newton algorithm, the results reveal that structural information improves image quality and conductivity distribution, particularly in the region of two bones. In addition, the reconstructed images using the Gauss-Newton algorithm performed better than images reconstructed using the back-projection algorithm. © 2022 IEEE.

关键词： Image reconstruction

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Feature Engineering for Accurate Low-Power Electrical Impedance Tomography in Hand Sign Recognition

Feature Engineering for Accurate Low-Power Electrical Impeda...

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IEEE SSD International Multi-Conference on Systems, Signals and Devices

作者： Bilel Ghoul Rim Barioul Salwa Sahnoun Ahmed Fakhfakh Olfa Kanoun Measurement and Sensor Technology Faculty of Electrical Engineering and Information Technology Chemnitz University of Technology Chemnitz Germany Laboratory of Signals Systems Artificial Intelligence and Networks Digital Research Centre of Sfax National School of Electronics and Telecommunications of Sfax Technopole of Sfax Ons City Tunisia

ISBN: (数字)9798331542726

ISBN: (纸本)9798331542733

Achieving high classification accuracy from raw measurements in Electrical Impedance Tomography (EIT) for hand sign recognition is a significant challenge due to the inherent ill-posed nature of the corresponding inverse problem to solve. Energy consumption is an issue, especially for wearable devices, so there is a growing preference to measure EIT with fewer electrodes or fewer current injections. In a previous study, we demonstrated that an 8-electrode hand gesture recognition system could achieve high accuracy with only 5 current injections instead of 8, resulting in significant power savings. In this study, we investigate feature extraction and selection techniques to improve the classification accuracy in the low-power EIT system based on less measurements. We evaluate the performance of 12 statistical features by analyzing the Feature Importance (FI) and identify 8 features with non-zero values: WL, MAV, Kurtosis, VORDER, DASDV, RMS, P2P and VAR. Using K-Nearest Neighbour (KNN), a comparative classification is performed using subsets of the best ranked features ranging from 2 to 8. Compared to the 96% accuracy achieved with raw data, our solution achieves 99.8% accuracy with the 8 extracted features. The results show that feature engineering significantly improves classification accuracy compared to the use of raw data.

关键词： Hands Performance evaluation Electrical impedance tomography Reactive power Accuracy Current measurement Nearest neighbor methods Feature extraction Kurtosis Wearable devices

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Comparative Study of Excitation Signals for Microcontroller-based EIS measurement on Li-Ion Batteries

Comparative Study of Excitation Signals for Microcontroller-...

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Impedance Spectroscopy (IWIS), International Workshop on

作者： Amin Fischer Ahmed Yahia Kallel Olfa Kanoun Chair of Measurement and Sensor Technology Technical University of Chemnitz Chemnitz Germany

Electrochemical impedance spectroscopy (EIS) is a well-known tool for battery cell analysis. Conventionally, a frequency-swept sine signal is used to perform impedance spectroscopy on the battery. However, such an excitation signal can be very time-consuming, leading to higher memory storage demand or extra hardware equipment for impedance determination. In the state-of-the-art, broadband signals were studied and proven to be an adequate alternative for fast and reliable impedance spectroscopy. However, most of these studies use industrial computers (PXI), FPGAs, and other systems which are off-limits for end customers. We propose to evaluate the performance of a cost-effective STM32 microcontroller as an alternative to lab equipment for impedance spectroscopy of Lithium-Ion cells. In this paper, we focus only on the evaluation of its practical capability to generate an excitation signal waveform. Hereby the generated Signal is measured by an external data acquisition device (DAQ). The proposed work can be applied to a complementary part utilizing IS in battery management systems.

关键词： Lithium-ion batteries Spectroscopy Impedance measurement Microcontrollers Chirp Data acquisition Energy efficiency

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A review on intelligent IoT systems design methodologies

A review on intelligent IoT systems design methodologies

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作者： Fredj, Nissaf Hadj Kacem, Yessine Khriji, Sabrine Kanoun, Olfa Abid, Mohamed Measurement and Sensor Technology Chemnitz University of Technology Germany CES Laboratory ENIS University of Sfax Tunisia CES Laboratory ENIS University of Sfax Tunisia

The design of distributed real-time systems including In- ternet of Things (IoT) systems is complex due to open-ended architectures requirements. An emergent solution to deal with this complexity and to manage system constraints is the integration of adaptation strategies in distributed devices behavior. The developement of such systems denotes a signifi-cant challenge on providing autonomous and intelligent ability to verify distributed devices behaviors and constraints such as battery storage of sensors. Existing AI-based approaches for dynamic IoT systems proposed solutions relative to the target system for resolving specific problems without consid-ering interoperability and reusability. Using MDE approach and UML/MARTE profile for high-level abstraction becomes a promising solution to ease the design of intelligent IoT systems. This paper recalls and classifies the existing AI and MDE-based works for the design of dynamic distributed systems especialy IoT applications. We concentrate on a set of criteria to highlight the shortages of existing approaches on the design of distributed devices interaction, adaptation and system constraints. Finally, we introduce our future directions to cope with the limits of existing solutions while taking into account the observed criteria. © 2021

关键词： Interoperability

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sensor Design Based on MSL Coupled with HCSRR-Loaded Ground Plane for Material Characterization

Sensor Design Based on MSL Coupled with HCSRR-Loaded Ground ...

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IEEE SSD International Multi-Conference on Systems, Signals and Devices

作者： Swaranpreet Kaur Surinder Singh Murari Mohan Sinha Dhivakar Rajendran Adiraju Anurag Olfa Kanoun Department of Physics Sant Longowal Institute of Engg. & Tech. Longowal Sangrur India Department of ECE Sant Longowal Institute of Engg. & Tech. Longowal Sangrur India Measurement and Sensor Technology Chemnitz University of Technology Chemnitz Germany

ISBN: (数字)9798331542726

ISBN: (纸本)9798331542733

Material characterization utilizing electromagnetic planar sensors is a promising area within modern sensing technology. This work introduces a novel sensor design based on a microstrip line (MSL) structure coupled with three hexagonal-shaped complementary split-ring resonators (HCSRR) etched onto the ground plane. The primary purpose of the proposed sensor is to measure the dielectric constant of the material under test (MUT). The MSL-HCSRR sensor is specifically engineered to operate within the Industrial, Scientific, and Medical (ISM) frequency band centered at 2.4 GHz. The total dimensions of the sensor structure are optimized to 0.35 λ 0 × 0.16 λ 0 × 0.01 λ 0 . The interaction of electromagnetic waves with the MUT induces a shift in resonant frequencies, utilized for material characterization. The proposed MSL-HCSRR configuration exhibits an E-field distribution of about 1.15 x 10 4 V/m and hence, enhances the sensitivity of the sensor by inducing a resonance response that is influenced by the changing dielectric properties of the MUT. This approach enables precise and reliable characterization of materials, particularly those with varying dielectric constants.

关键词： Sensitivity Dielectric constant Soil measurements Soil moisture Resonant frequency Materials reliability sensor phenomena and characterization Solids Dielectric measurement Microstrip

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Exploring the Real-Time Capability of Electrical Impedance Tomography for Hand Sign Recognition in Robotic Hand Control

Exploring the Real-Time Capability of Electrical Impedance T...

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International Workshop on Robot Sensing (ROSE)

作者： Bilel Ghoul Bilel Ben Atitallah Rim Barioul Ahmed Fakhfakh Olfa Kanoun Measurement and Sensor Technology Faculty of Electrical Engineering and Information Technology Chemnitz University of Technology Chemnitz Germany Laboratory of Signals Systems Artificial Intelligence and Networks Digital Research Centre of Sfax National School of Electronics and Telecommunications of Sfax Technopole of Sfax Ons City Tunisia

ISBN: (数字)9798350362367

ISBN: (纸本)9798350362374

Electrical impedance tomography (EIT) can monitor the influence of the muscle activity on the conductivity distribution across the forearm and is therefore suitable for Hand Sign Recognition (HSR). However, the method is relatively complex, so realizing real-time classification based on EIT measurements is still considered a major challenge. In addition, the accuracy of EIT for HSR is highly dependent on the injection configuration parameters applied. In this study, we investigate the influence of the injection configuration on the achieved accuracy of the hand robot control and the feasibility of a real-time classification based on EIT measurements. To assess real-time feasibility, experimental data have been collected for a sign set of 36 American Sign Language (ASL) performed by one healthy subject. Moreover, a comparative study of the adjacent, opposite, and cross injection configurations has been conducted on 10 subjects performing the ASL set. An ambiguity study based on the measured signals was performed to assess the discrimination potential between the hand signs. The adjacent EIT configuration exhibited higher sensitivity in discriminating hand signs. For a real-time classification, we propose the use of a Support Vector Machine (SVM) model realizing an overall accuracy of 71.38%. To validate the system's real-time behavior, the classification result is visualized by a robotic hand reproducing 6 different hand signs from the 36 ASL set reaching an accuracy of 80%. The results demonstrate the potential of EIT to facilitate real-time Hand Sign Recognition for robot control applications.

关键词： Support vector machines Electrical impedance tomography Surface impedance Accuracy Robot control Muscles Robot sensing systems

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Comparative Study of Data Reduction Methods in Electrical Impedance Tomography For Hand Sign Recognition

Comparative Study of Data Reduction Methods in Electrical Im...

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International Conference on Advanced Technologies for Signal and Image Processing (ATSIP)

作者： Bilel Ghoul Bilel Ben Atitallah Salwa Sahnoun Ahmed Fakhfakh Olfa Kanoun Measurement and Sensor Technology Faculty of Electrical Engineering and Information Technology Chemnitz University of Technology Chemnitz Germany Digital Research Centre of Sfax National School of Electronics and Telecommunications of Sfax Technopole of Sfax Laboratory of Signals Systems Artificial Intelligence and Networks Ons City Tunisia

ISBN: (数字)9798350351484

ISBN: (纸本)9798350351491

Several studies have shown that electrical impedance tomography (EIT) on the human forearm can be used to classify hand signs without the need for cameras or gloves. However, the amount of measured data is in relatively high, leading to long execution times and high processing complexity. In this study, we investigate the influence of reducing the number of EIT measurements on the classification accuracy. Four different algorithms were used to halve the number of measurements, namely Principal Component Analysis (PCA), Chi-square tests, Minimum Redundancy Maximum Relevance (MRMR) and Laplacian scores. These algorithms were applied to a dataset of forearm EIT measurements corresponding to the practice of American Sign Language (ASL) in a healthy subject. The results show a slight drop in accuracy when using the quadratic support vector machine (SVM) classifier, with accuracy dropping from 95.3% to 93.4% in the best cases. A method based on a genetic algorithm (GA) was also used. This approach exploits the strengths of genetic algorithms in exploring a large solution space and converging on the near-optimal combination. This approach resulted in an increase in accuracy to 96.7%. The study demonstrated that the number of EIT measurements can be reduced without compromising overall accuracy.

关键词： Support vector machines Electrical impedance tomography Sign language Accuracy Image recognition Laplace equations Assistive technologies

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Multicore fiber with thermally expanded cores for increased collection efficiency in endoscopic imaging

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Light(Advanced Manufacturing) 2024年第4期5卷 102-109页

作者： Kinga Zolnacz Ronja Stephan Jakob Dremel Katharina Hausmann Matthias Lieβmann Michael Steinke Juergen Czarske Robert Kuschmierz Chair of Measurement and Sensor System Technique TU Dresden01069 DresdenGermany Department of Optics and Photonics Wroclaw University of Science and Technology50370 WroclawPoland Institute of Quantum Optics Leibniz University Hannover30167 HannoverGermany Competence Center for Biomedical Computational Laser Systems(BIOLAS) TU Dresden01069 DresdenGermany Else Kroner Fresenius Center for Digital Health(EKFZ) TU Dresden01307 DresdenGermany Cluster of Excellence PhoenixD Leibniz University Hannover30167 HannoverGermany

Fiber-based endoscopes are promising for minimally invasive in vivo biomedical *** fibers offer high resolution ***,to avoid image deterioration induced by inter-core coupling,significant spacing between cores is required,which limits the active image guiding area of the ***,they suffer from low light collection efficiency and decreased signal-to-noise *** this paper,we present a method to increase the collection efficiency by thermally expanding the cores at the facet of a multicore *** expansion is based on the diffusion of doping material of the cores,thus the fiber’s original outer diameter is *** enlarging the core diameter by a factor of 2.8,we increase the intensity of the transmitted light by a factor of up to *** results in a signal-to-noise ratio increase by a factor of up to 4.6 and significant improvement in the image *** improvement increases with increasing working distance but is already prominent for as small working distance as 0.5 *** feasibility of the method is proved experimentally by lensless single-shot imaging of a test chart and incoherent light reflected from clusters of *** demonstrated approach is an important tool especially in imaging of biological specimens,for which phototoxicity must be avoided,and therefore,high collection efficiency is required.

关键词： Thermally expanded cores fiber Multicore fiber Lensless imaging

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Biomimetic Robotic Hand with Highly Sensitive Integrated Nanocomposite Force sensors for Adaptive Grasping

Biomimetic Robotic Hand with Highly Sensitive Integrated Nan...

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International Workshop on Robot Sensing (ROSE)

作者： Ahmed Attaoui Achraf Djemal Bilel Ben Atitallah Asma El Jaoui Olfa Kanoun Professorship Measurement and Sensor Technology Chemnitz University of Technology Chemnitz Germany Laboratory of Mechanics of Sousse National Engineering School of Sousse University of Sousse Sousse Tunisia Laboratory of Signals Systems Artificial Intelligence and Networks National School of Electronics and Telecommunications of Sfax Sfax Tunisia

ISBN: (数字)9798350362367

ISBN: (纸本)9798350362374

Robotic hands have immense potential for a wide range of applications, but the key challenge is still to achieve human-like dexterity. This requires overcoming several challenges, such as high system complexity, slow response time, and difficulties in integrating effective sensors. In this study, we present a novel robotic hand with 17 degrees-of-freedom equipped with nanocomposite based pressure and strain sensors. Inspired by the human hand's capabilities, the hand's design strives to mimic its dexterity and shape. The implemented nanocomposite sensors have exceptional electrical, mechanical, and electrochemical capabilities, making them ideal for integration into our robotic hand system design. The pressure sensor has a rapid response time, high pressure sensitivity of 4.4 kΩ /kPa, and remains stable over more than 5,000 cycles, demonstrating a high reliability. The strain sensor also maintains good linearity of 0.98 when subjected to strains from 0% to 24.49%. To address the challenge of balancing secure grasping and delicate touch, a finite state machine (FSM) control method is proposed enabling the hand to dynamically adjust its grasping pressure based on the real-time sensor feedback, allowing for precise manipulation of fragile objects. Experiments demonstrate the effectiveness of the proposed approach, paving the way for the development of intelligent robotic systems with enhanced dexterity and adaptability for real-world applications.

关键词： Automata Tactile sensors Grasping Robot sensing systems Capacitive sensors sensor systems sensors

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