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Quantum-Enhanced Spiking Neural Networks for Closed-Loop Neuromodulation Systems: A Theoretically Advanced Framework

Quantum-Enhanced Spiking Neural Networks for Closed-Loop Neu...

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Innovative computing, Intelligent Communication and Smart electrical Systems (ICSES), international conference on

作者： Vallari Ashar Sarthak Bansal Pandiyaraju V School of Computer Science and Engineering Vellore Institute of Technology Chennai Tamilnadu India

ISBN: (数字)9798331543624

ISBN: (纸本)9798331543631

Over one billion people worldwide are affected with neurological disorders and their economic impact is approximately $800 billion annually, which constitutes major medical challenge. Using neuromodulation systems currently available suffers from sensitivity, reaction time as well as energy consumption. The proposal in this research is to address these major issues in closed loop neuromodulation by using a Quantum enhanced Spiking Neural Network (QESNN) architecture. This paper represents the interfacing of two major fields: quantum sensing and neuromorphic computing. The QESNN architecture comprises three core components: This is implemented as an array of quantum sensors, a quantum classical hybrid interface, and a spiking neural network (SNN). Taking advantage of quantum superposition and entanglement principles, the quantum sensor array noninvasively images neural activity at the level of single action potentials using NV centers. These sensors work at ambient temperatures, which is unlike superconducting devices. For processing with neuromorphic processing, quantum-classical hybrid converts quantum sensor data into classical signals with advanced signal process such as quantum state estimation and noise reduction. By modeling biological neurons with leaky integrate and fire neurons, the SNN serves as a low power, timed neural dynamics modulation component that emulates biological event driven behavior. A key innovation in our architecture is adaptive thresholding, which dynamically adjusts detection thresholds based on signal distributions, improving sensitivity and reducing false positives by 45.6%. The system also achieves 20-30% higher power efficiency through techniques like adaptive sensor frequency control and low-power processing. Simulation results that show how the QESNN performs better than classical systems with less false positives and greater energy efficiency are presented. A new platform is demonstrated that integrates quantum sensing with neurom

关键词： Neurological diseases Temperature sensors Sensitivity Quantum computing Neuromorphic engineering Spiking neural networks Computer architecture Neuromodulation Quantum sensing Sensor arrays

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A Multi-mode Low Energy Consumption System control and Reliability Evaluation Method

A Multi-mode Low Energy Consumption System Control and Relia...

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Smart electrical Grid and Renewable Energy (SEGRE), international conference on

作者： Ying Zhang Yifei Zhao Zhanggang Lv Shihui Wang Bo Yang System Engineering Research Department Beijing Institute of Aerospace Automatic Controls Beijing China Committee on Science and Technology Beijing Institute of Aerospace Automatic Controls Beijing China Beijing Institute of Precision Mechatronics and Controls Beijing China

The multi-mode low energy consumption system control and reliability evaluation method proposed in this paper has the novelty by implementing multi-mode control and operation status monitoring. Man-machine interaction mode switch, and real-time display of the controlled object, program-controlled power supply, can control the internal power supply of each part of the output state, system power consumption, system reliability, the realization of the system under the multi-mode real-time operating state monitoring. The health status of the low energy consumption system can be divided into five states: healthy state, mildly degraded state, moderately degraded state, severely degraded state, and fault state, which characterized the health status of the system operation. By quantifying the health status of low-power multi-mode systems, a fine-grained health assessment of voltage parameters between 21.50 and 23.00 volts is achieved through collecting the observable state quantity of the low energy consumption system, with wavelet packet transformation, and the HMM prediction model. The multi-mode energy consumption control method and reliability estimation strategy proposed in this paper , which has the simulation results with 22.20~22.50 V as normal status and wider 22.05~22.75 V as fault status,have important application significance for reducing system power consumption, evaluating system health status, timely carrying out health maintenance, and extending system service life.

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Analysis of Hand Shapes with Convolutional Neural Networks for Sign Language Recognition 5th

Analysis of Hand Shapes with Convolutional Neural Networks f...

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5th international conference on Recent Developments in control, Automation and Power engineering, RDCAPE 2023

作者： Bhatia, Sandeep Naib, Bharat Bhushan Goel, Amit Kumar Verma, Anurag Gangwar, Sachin Goel, Neha School of Computing Science and Engineering Galgotias University Uttar Pradesh Greater Noida India School of Engineering and Technology Apeejay Stya University Sohna Gurugram India Department of Electronics and Communication Engineering RKGIT Ghaziabad Uttar Pradesh Ghaziabad India Department of ECE RKGIT Ghaziabad India

ISBN: (纸本)9789819600465

According to the late theoretical physicist Stephen Hawking, having a disability need not prevent you from succeeding. People with talents should always work to make the lives of disabled people better. The deaf and dumb benefit from a variety of technological developments and studies. Numerous message boards are used by people to spread their message. Text messages can now be sent using rewritable pads, however doing so requires time and isn’t always successful. Technologies like machine learning and open CV can be employed to progress the situation. These can be created into automatic editors for anyone with limitations like as speech or hearing loss. Hand gestures can be used to convey messages. With the aid of open CV and machine learning, we can capture their hand motions and translate them into a language that we can all comprehend. This study article will look at how to implement a model that will assist the disabled with this problem and challenges associated with sign language recognition. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Motion analysis

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Simultaneous On-line Estimation of Model Parameters and the Wearer's Joint Torque of Exoskeletons

Simultaneous On-line Estimation of Model Parameters and the ...

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2021 international automatic control conference, CACS 2021

作者： Hsiao, Tesheng Tsai, ChengYu Juang, Hau-Shiue Institute of Electrical and Control Engineering National Yang Ming Chiao Tung University Hsinchu Taiwan National Chung Shan Institute of Science and Technology Taoyuan Taiwan

ISBN: (纸本)9781665444125

It is crucial for walking assistive exoskeletons to detect and comply with the motion intention of the wearers. Recently, the first author has proposed to estimate the wearer's joint torque for intention detection, and conducted assistive walking successfully. The aforementioned torque estimation algorithm was based on the model of the exoskeleton with fixed parameters. However, the model parameters depend on the weight and height of the wearer. In order to achieve more accurate torque estimation, regardless of the physique of the wearer, this paper aims to simultaneously estimate the wearer's joint torque and model parameters. Since the joint torque is periodic during walking, we on-line identify the fundamental frequency of the gait and parameterize the wearer's joint torque by its first two harmonics. Then the parameters of the joint torque and the model are estimated together by the least mean square (LMS) algorithm. Experiments are conducted to verify that the method of this paper achieves robust accuracy in torque estimation, even though additional loads are attached to the exoskeleton. The fitness of the estimated and actual torques are more than 80% in all experimental conditions. © 2021 IEEE

关键词： Torque

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A Study on the Integration of Haptic Feedback for Optimizing Telerobotic Surgery

A Study on the Integration of Haptic Feedback for Optimizing...

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Cognitive computing in engineering, Communications, sciences and Biomedical Health Informatics (IC3ECSBHI), international conference on

作者： Jayasheel Kumar Kalagatoori Archakam D Shobha Rani Ginni Nijhawan Tamam Ali Abd Ulabbas Abedi P. Subhashini Navya Gupta New Horizon College of Engineering Bangalore India Department of Electrical and Electronics Engineering Institute of Aeronautical Engineering Hyderabad Telangana Lovely Professional University Phagwara India Radiology Techniques Department College of Medical Technology The Islamic University Najaf Iraq Department of Computer Science and Engineering MLR Institute of Technology Hyderabad Telangana India Lloyd Law College Greater Noida Uttar Pradesh

ISBN: (数字)9798331518523

ISBN: (纸本)9798331518530

This paper aimed at conducting a comprehensive discussion on haptic feedback and force based teleoperation in the domain of surgical robots similar far-reaching significance of haptic feedback based operation in eradicating telerobotic surgery problems of sensory feel and motor skills for surgeons. Nonetheless, although the utilization of haptic feedback in the field of telesurgery has been demonstrated to have a plethora of benefits including enhanced realism during the interaction of tissue as well as the over-proportionate enhancement of surgical results, haptic feedback's adoption into commercial telesurgical systems remains limited. This paper categorizes the common technical barriers that have prevented broader use of haptic devices, such issues to do with fidelity, stability, and force feedback. Moreover, it also investigates strategies that are being investigated to address these problems, including the improved control algorithms, the use of machine learning techniques as well as combination of force reflection techniques. The paper also aims to review the ergonomics of haptic systems and their contribution to medical education particularly in surgery, the implications of haptic systems on patient outcomes is also considered. In concert with this, this study aims at presenting a research and development agenda for haptic integration in telesurgical operations through an elaborate review and synthesis.

关键词： Medical robotics Reviews Force Surgery Robot sensing systems Stability analysis Reflection Haptic interfaces Telerobotics Research and development

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SpiCS-Net: Circuit Switched Network on Chip for Area-Efficient Spiking Recurrent Neural Networks

SpiCS-Net: Circuit Switched Network on Chip for Area-Efficie...

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international conference on VLSI Design

作者： Manu Rathore Garrett S. Rose Department of Electrical Engineering and Computer Science The University of Tennessee Knoxville TN USA

Spiking Recurrent Neural Networks (SRNNs) present an alternative computing paradigm to traditional von Neumann computing in the post-Moore’s law era because they omit the memory-processor bottleneck and enable low-power resource-efficient computations. When utilized as a reservoir in a Reservoir computing (RC) system, SRNNs enable applications in temporal signal processing involving complex data patterns, e.g., chaotic time-series prediction and control in non-linear dynamical systems. Implementing the RC system based on SRNNs on hardware would enable low-power and area-efficient computing, suitable for various applications in resource-constrained systems like battery-powered edge devices. However, one of the significant challenges in achieving this on hardware relates to the Network-on-Chip (NoC) implementation for the SRNN. This NoC implementation challenge stems from the requirement to support reconfigurable connectivity across the chip to enable connections between any arbitrary pair of neurons within the network. Traditional NoC approaches are packet-based spike routing networks that require extra packet-handling circuits and are targeted for large-scale SRNNs. In this work, we propose SpiCS-Net, pronounced spikes-net, a Spike-routing Clos Circuit-Switched Network-on-Chip architecture. SpiCS-Net is a switch-based communication scheme that avoids the conversion of spikes into data packets. Thus, SpiCS-Net is highly efficient when compared to packet-based networks. SpiCS-Net is evaluated and compared with state-of-the-art for several key network design metrics, including throughput, area, and power consumption. Compared to packet-based approaches in the literature, SpiCS-Net offers up to 9% higher throughput and nearly $13\times$ savings in area.

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The Role of Medical Informatics in Facilitating Evidence-Based Healthcare Practices

The Role of Medical Informatics in Facilitating Evidence-Bas...

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Intelligent control, computing and Communications (IC3), international conference on

作者： Manish Gupta Ali Saeed K. Srinija Amit Kumar Muthuswamy Jayanthi Yaragudipati Sri Lalitha Lovely Professional University Phagwara India Radiology Techniques Department College of Medical Technology The Islamic University Najaf Iraq Department of Computer Science and Engineering MLR Institute of Technology Hyderabad Telangana India Department of Electrical Electronics & Communication Engineering Galgotias university Gerater Noida Uttar Pradesh Department of Electronics and Communication Engineering New Horizon College of Engineering Bangalore India Department of Information Technology GRIET Bachupally Hyderabad Telangana India

ISBN: (数字)9798331527495

ISBN: (纸本)9798331527501

Medical knowledge, technology, and data have changed healthcare. A new method, OptimizedClinicalDecide (OCD), is transforming evidence-based health care and achieving this critical goal. To treat OCD, it is critical to use medical data as well as cutting-edge algorithms and learning systems that evolve over time. This strategy effectively addresses the long-standing issue of incompatible healthcare data sets, making it perfect for data integration. OCD's dynamic learning engine is continually adding new patient data to the knowledge base, guaranteeing that health care practitioners have the most up-to-date patient health information. Modern healthcare relies on decision-making aid, and flexible decision optimization techniques enhance it by providing patient-specific guidance. OCD's ability to use cutting-edge medical knowledge and promote lifelong learning are its assets. Advanced analytics and personalized patient outcome prediction methodologies increase forecasting and prognosis. The proposed strategy makes use of mobile health resources and is appropriate for the present era of patient-centered treatment. MEPCC promotes patients to work together on health-care decisions. Traditional approaches suffer with adaptability, data integration, and decision support. OptimizedClinicalDecide addresses these challenges and increases patient involvement. According to evidence, OCD has the ability to transform health care. This enhances our mission of providing educated, specialized, and collaborative patient care.

关键词： Heuristic algorithms Precision medicine Data integration Medical services Transforms Prediction algorithms Informatics Prognostics and health management Optimization Standards

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A New Rotor Position Observer of Brushless Doubly-Fed Induction Generators Based on control-Winding High-Frequency Signal Injection 4

A New Rotor Position Observer of Brushless Doubly-Fed Induct...

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4th IEEE China international electrical and Energy conference, CIEEC 2021

作者： Hussien, Mohamed G. Liu, Yi Xu, Wei Wuhan China Electrical Power and Machines Engineering Department Faculty of Engineering Tanta University Tanta Egypt High-efficiency and Energy-saving Electrical Machine RandD Center of Hust Zibo High-tech Development Zone China

ISBN: (纸本)9781728171494

In this paper, the main target is to propose a novel detection methodology for sensorless position observer with the injection approach of high-frequency signal (HFS) for voltage regulation of the brushless doubly-fed induction generators (BDFIGs). The new suggested observer relies on the injection of HFS into the control winding (CW) side, (CW-HFS), while the resulted induced signal detected from the power winding (PW) side can be processed for observing the position signal of generator. The proposed new sensorless control method neither need any saliencies in the rotor side nor require any process for computing the flux, which can assure the superiority of the new algorithm. Comprehensive analysis is realized with a BDFIG of wound-rotor type. The effective observation of the novel algorithm for detecting the mechanical position of BDFIGs has been confirmed through the obtained results with a better dynamic performance under various states of operation. © 2021 IEEE.

关键词： Asynchronous generators

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Data-Driven Coordinated control of AVR and PSS in Power Systems: A Deep Reinforcement Learning Method 21

Data-Driven Coordinated Control of AVR and PSS in Power Syst...

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21st IEEE international conference on Environment and electrical engineering / 5th IEEE Industrial and Commercial Power Systems Europe (EEEIC/I and CPS Europe)

作者： Oshnoei, Arman Sadeghian, Omid Mohammadi-Ivatloo, Behnam Blaabjerg, Frede Anvari-Moghaddam, Amjad Aalborg Univ Dept Energy Aalborg Denmark Univ Tabriz Fac Elect & Comp Engn Tabriz Iran

ISBN: (纸本)9781665436137

Y In this paper, a strategy based on deep reinforcement learning (DRL) as an intelligent coordinator for power system stabilizer (PSS) and automatic voltage regulator (AVR) in a two-are power grid is proposed. The proposed coordinator is developed to provide accurate online modification of the gains appearing in the structure of PSS and AVR which avoids unfavorable interactions between PSS and AVR under significant changes in the working point and thereby guaranteeing the stability of the power grid. A Markov decision manner is used to formulate the DRL problem and it is solved through a deep deterministic policy gradient approach with an actor-critic framework. Since the intelligent coordinator relies on the expert's science, some scaling coefficients are added to the coordinator body to achieve optimal performance. To confirm the effectiveness of the presented DRL approach, the design is conducted on Kundur's power grid. Simulations illustrate that the proposed DRL-based control can confirm the stability of the system and attain desired dynamic responses.

关键词： power system stability deep reinforcement learning coordinated control interconnected power system

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Research on Mechanical Arm Grinding Method Based on Improved CascadePSP Net 7

Research on Mechanical Arm Grinding Method Based on Improved...

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7th international conference on Communication, Image and Signal Processing, CCISP 2022

作者： Peng, Jishen Han, Jiaxin Yang, Yiling College of Electrical and Control Engineering Liaoning Technical University Huludao China Xi'An Fude Automatic Control Technology Co. LTD Xi'an China

ISBN: (数字)9781665459594

ISBN: (纸本)9781665459594

Aiming at the problems of manual processing and grinding workpieces, such as time-consuming and low accuracy, an intelligent method for grinding workpieces was proposed. The dataset is preprocessed using image graying and guided filtering. The mechanical arm is used for machining and grinding, Adding semantic segmentation technology to realize accurate identification and location of machining trajectory, An improved CascadePSP Net is proposed to realize faster recognition while ensuring accuracy. By comparing the improved CascadePSP Net with the original network, the segmentation accuracy and training speed are improved. Use the Sober operator to extract the contour of the workpiece to be machined to determine the final machining path. The trajectory planning of the three-degree-of-freedom Dobot Magician manipulator is carried out by the fifth-order polynomial interpolation method and the Cartesian coordinate system method. Build an experimental platform for an image recognition robotic arm, and the comparison of the trajectory recognition method and the test experiment of the mechanical arm grinding system were carried out respectively. It verifies the feasibility of the proposed grinding method. The experimental results show that the method reduces the network training time, realizes high-efficiency and high-precision segmentation processing, thus improves the workpiece grinding efficiency and realizes the intelligent processing of workpiece batches. © 2022 IEEE.

关键词： Trajectories

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