scholarly journals Multichannel Biphasic Muscle Stimulation System for Post Stroke Rehabilitation

Electronics ◽  
2020 ◽  
Vol 9 (7) ◽  
pp. 1156
Author(s):  
Tyler Ward ◽  
Neil Grabham ◽  
Chris Freeman ◽  
Yang Wei ◽  
Ann-Marie Hughes ◽  
...  
Keyword(s):  
Integrated Circuits ◽  
Upper Limb Function ◽  
Stimulation Parameters ◽  
Average Accuracy ◽  
Pulse Timing ◽  
Field Programmable ◽  
Stimulation System ◽  
Electrical Stimulator ◽  
Mechanical Movement ◽  
Better Than

We present biphasic stimulator electronics developed for a wearable functional electrical stimulation system. The reported stimulator electronics consist of a twenty four channel biphasic stimulator. The stimulator circuitry is physically smaller per channel and offers a greater degree of control over stimulation parameters than existing functional electrical stimulator systems. The design achieves this by using, off the shelf multichannel high voltage switch integrated circuits combined with discrete current limiting and dc blocking circuitry for the frontend, and field programmable gate array based logic to manage pulse timing. The system has been tested on both healthy adults and those with reduced upper limb function following a stroke. Initial testing on healthy users has shown the stimulator can reliably generate specific target gestures such as palm opening or pointing with an average accuracy of better than 4 degrees across all gestures. Tests on stroke survivors produced some movement but this was limited by the mechanical movement available in those users’ hands.

scholarly journals A Gastrointestinal Electrical Stimulation System Based on Transcutaneous Power Transmission Technology

2014 ◽  
Vol 2014 ◽  
pp. 1-9 ◽  
Author(s):  
Bingquan Zhu ◽  
Yongbing Wang ◽  
Guozheng Yan ◽  
Pingping Jiang ◽  
Zhiqiang Liu
Keyword(s):  
Electrical Stimulation ◽  
Power Transmission ◽  
Functional Gastrointestinal Disorders ◽  
Gastrointestinal Disorders ◽  
Stimulation Protocol ◽  
Stimulation Parameters ◽  
Parametric Studies ◽  
Stimulation System ◽  
Electrical Stimulator ◽  
Extended Power

Electrical stimulation has been suggested as a possible treatment for various functional gastrointestinal disorders (FGID). This paper presents a transcutaneous power supplied implantable electrical stimulation system. This technology solves the problem of supplying extended power to an implanted electrical stimulator. After implantation, the stimulation parameters can be reprogrammed by the external controller and then transmitted to the implanted stimulator. This would enable parametric studies to investigate the efficacy of various stimulation parameters in promoting gastrointestinal contractions. A pressure detector in the internal stimulator can provide real-time feedback about variations in the gastrointestinal tract. An optimal stimulation protocol leading to cecal contractions has been proposed: stimulation bursts of 3 ms pulse width, 10 V amplitude, 40 Hz frequency, and 20 s duration. The animal experiment demonstrated the functionality of the system and validated the effects of different stimulation parameters on cecal contractions.

DCNN-based Ship Classification using Enhanced Edge Information and Inception Module

2021 ◽  
Author(s):  
Bo Wang ◽  
Xiaoting Yu ◽  
Chengeng Huang ◽  
Qinghong Sheng ◽  
Yuanyuan Wang ◽  
...  
Keyword(s):  
Neural Networks ◽  
Classification Performance ◽  
Image Features ◽  
Deep Convolutional Neural Networks ◽  
Edge Information ◽  
Average Accuracy ◽  
Ship Classification ◽  
Edge Features ◽  
High Level ◽  
Better Than

The excellent feature extraction ability of deep convolutional neural networks (DCNNs) has been demonstrated in many image processing tasks, by which image classification can achieve high accuracy with only raw input images. However, the specific image features that influence the classification results are not readily determinable and what lies behind the predictions is unclear. This study proposes a method combining the Sobel and Canny operators and an Inception module for ship classification. The Sobel and Canny operators obtain enhanced edge features from the input images. A convolutional layer is replaced with the Inception module, which can automatically select the proper convolution kernel for ship objects in different image regions. The principle is that the high-level features abstracted by the DCNN, and the features obtained by multi-convolution concatenation of the Inception module must ultimately derive from the edge information of the preprocessing input images. This indicates that the classification results are based on the input edge features, which indirectly interpret the classification results to some extent. Experimental results show that the combination of the edge features and the Inception module improves DCNN ship classification performance. The original model with the raw dataset has an average accuracy of 88.72%, while when using enhanced edge features as input, it achieves the best performance of 90.54% among all models. The model that replaces the fifth convolutional layer with the Inception module has the best performance of 89.50%. It performs close to VGG-16 on the raw dataset and is significantly better than other deep neural networks. The results validate the functionality and feasibility of the idea posited.

scholarly journals iHandU: A Novel Quantitative Wrist Rigidity Evaluation Device for Deep Brain Stimulation Surgery

Sensors ◽  
2020 ◽  
Vol 20 (2) ◽  
pp. 331 ◽  
Author(s):  
Elodie Múrias Lopes ◽  
Maria do Carmo Vilas-Boas ◽  
Duarte Dias ◽  
Maria José Rosas ◽  
Rui Vaz ◽  
...  
Keyword(s):  
Deep Brain Stimulation ◽  
Brain Stimulation ◽  
Lessons Learned ◽  
Wrist Flexion ◽  
Stimulation Parameters ◽  
Average Accuracy ◽  
Gyroscope Sensor ◽  
Work Done ◽  
Deep Brain Stimulation Surgery ◽  
Deep Brain

Deep brain stimulation (DBS) surgery is the gold standard therapeutic intervention in Parkinson’s disease (PD) with motor complications, notwithstanding drug therapy. In the intraoperative evaluation of DBS’s efficacy, neurologists impose a passive wrist flexion movement and qualitatively describe the perceived decrease in rigidity under different stimulation parameters and electrode positions. To tackle this subjectivity, we designed a wearable device to quantitatively evaluate the wrist rigidity changes during the neurosurgery procedure, supporting physicians in decision-making when setting the stimulation parameters and reducing surgery time. This system comprises a gyroscope sensor embedded in a textile band for patient’s hand, communicating to a smartphone via Bluetooth and has been evaluated on three datasets, showing an average accuracy of 80%. In this work, we present a system that has seen four iterations since 2015, improving on accuracy, usability and reliability. We aim to review the work done so far, outlining the iHandU system evolution, as well as the main challenges, lessons learned, and future steps to improve it. We also introduce the last version (iHandU 4.0), currently used in DBS surgeries at São João Hospital in Portugal.

scholarly journals FPGAs in Client Compute Hardware

2021 ◽  
Author(s):  
Michael Mattioli
Keyword(s):  
Integrated Circuits ◽  
Field Programmable Gate Arrays ◽  
Gate Arrays ◽  
Application Specific Integrated Circuits ◽  
Field Programmable ◽  
Programmable Gate Arrays ◽  
And Performance ◽  
Application Specific

<div>Field-programmable gate arrays (FPGAs) are remarkably versatile. FPGAs are used in a wide variety of applications and industries where use of application-specific integrated circuits (ASICs) is less economically feasible. Despite the area, cost, and power challenges designers face when integrating FPGAs into devices, they provide significant security and performance benefits. Many of these benefits can be realized in client compute hardware such as laptops, tablets, and smartphones.</div>

Dynamically Reconfigurable Embedded Architectures for Safe Transportation Systems

2014 ◽  
pp. 347-371 ◽  
Author(s):  
Naim Harb ◽  
Smail Niar ◽  
Mazen A. R. Saghir
Keyword(s):  
Integrated Circuits ◽  
Embedded System ◽  
Transportation Systems ◽  
Base System ◽  
Dynamic Partial Reconfiguration ◽  
Dynamically Reconfigurable ◽  
Gate Arrays ◽  
Field Programmable ◽  
Programmable Gate Arrays ◽  
Mtt Algorithm

Embedded system designers are increasingly relying on Field Programmable Gate Arrays (FPGAs) as target design platforms. Today's FPGAs provide high levels of logic density and rich sets of embedded hardware components. They are also inherently flexible and can be easily and quickly modified to meet changing applications or system requirements. On the other hand, FPGAs are generally slower and consume more power than Application-Specific Integrated Circuits (ASICs). However, advances in FPGA architectures, such as Dynamic Partial Reconfiguration (DPR), are helping bridge this gap. DPR enables a portion of an FPGA device to be reconfigured while the device is still operating. This chapter explores the advantage of using the DPR feature in an automotive system. The authors implement a Driver Assistant System (DAS) based on a Multiple Target Tracking (MTT) algorithm as the automotive base system. They show how the DAS architecture can be adjusted dynamically to different scenario situations to provide interesting functionalities to the driver.

scholarly journals Establishment of a Numerical Model to Design an Electro-Stimulating System for a Porcine Mandibular Critical Size Defect

2019 ◽  
Vol 9 (10) ◽  
pp. 2160 ◽  
Author(s):  
Hendrikje Raben ◽  
Peer W. Kämmerer ◽  
Rainer Bader ◽  
Ursula van Rienen
Keyword(s):  
Numerical Model ◽  
Critical Size ◽  
Healing Process ◽  
Low Frequency ◽  
Implant Design ◽  
Tissue Properties ◽  
Stimulation Parameters ◽  
Promising Therapeutic Approach ◽  
Stimulation System

Electrical stimulation is a promising therapeutic approach for the regeneration of large bone defects. Innovative electrically stimulating implants for critical size defects in the lower jaw are under development and need to be optimized in silico and tested in vivo prior to application. In this context, numerical modelling and simulation are useful tools in the design process. In this study, a numerical model of an electrically stimulated minipig mandible was established to find optimal stimulation parameters that allow for a maximum area of beneficially stimulated tissue. Finite-element simulations were performed to determine the stimulation impact of the proposed implant design and to optimize the electric field distribution resulting from sinusoidal low-frequency ( f = 20 Hz ) electric stimulation. Optimal stimulation parameters of the electrode length h el = 25 m m and the stimulation potential φ stim = 0.5 V were determined. These parameter sets shall be applied in future in vivo validation studies. Furthermore, our results suggest that changing tissue properties during the course of the healing process might make a feedback-controlled stimulation system necessary.

EVOLVING DECISION TREES IN HARDWARE

2009 ◽  
Vol 18 (06) ◽  
pp. 1033-1060 ◽  
Author(s):  
RASTISLAV J. R. STRUHARIK ◽  
LADISLAV A. NOVAK
Keyword(s):  
Integrated Circuits ◽  
Decision Tree ◽  
Decision Trees ◽  
Adaptive Learning ◽  
Software Evolution ◽  
Fpga Implementation ◽  
Software Implementation ◽  
Navigation Systems ◽  
Field Programmable ◽  
Tree Inference

This paper, according to the best of our knowledge, provides the very first solution to the hardware implementation of the complete decision tree inference algorithm. Evolving decision trees in hardware is motivated by a significant improvement in the evolution time compared to the time needed for software evolution and efficient use of decision trees in various embedded applications (robotic navigation systems, image processing systems, etc.), where run-time adaptive learning is of particular interest. Several architectures for the hardware evolution of single oblique or nonlinear decision trees and ensembles comprised from oblique or nonlinear decision trees are presented. Proposed architectures are suitable for the implementation using both Field Programmable Gate Arrays (FPGA) and Application Specific Integrated Circuits (ASIC). Results of experiments obtained using 29 datasets from the standard UCI Machine Learning Repository database suggest that the FPGA implementations offer significant improvement in inference time when compared with the traditional software implementations. In the case of single decision tree evolution, FPGA implementation of H_DTS2 architecture has on average 26 times shorter inference time when compared to the software implementation, whereas FPGA implementation of H_DTE2 architecture has on average 693 times shorter inference time than the software implementation.

A Prototyping Environment for Hardware/Software Codesign of OFDM Systems

2013 ◽  
Vol 380-384 ◽  
pp. 2803-2806
Author(s):  
Xu Ming Lu ◽  
Wei Jie Wen ◽  
Hong Zhou Tan
Keyword(s):  
Integrated Circuits ◽  
Data Transmission ◽  
Hardware Implementation ◽  
Ofdm Systems ◽  
Ofdm System ◽  
Field Programmable ◽  
Software And Hardware ◽  
Front End Module ◽  
Application Specific ◽  
Insight Into

To make rapid implementation and verification for the systems becomes important in frontend Application Specific Integrated Circuits. Therefore, a field programmable gate array based hardware/software codesign prototyping environment is proposed to simulate the software implementation and verify the hardware implementation of a baseband OFDM system. The system is implemented by software and hardware partitions, respectively. The analog radio frequency front-end module helps take a full insight into the actual baseband system performance. User datagram protocol is used for data transmission between these two partitions, and hence makes a complete baseband system. With the proposed codesign environment, the software simulation is running over real wireless channels, and the hardware implemental results can be flexibly processed in real time and enhances the design efficiency.

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