Low-cost Hardware Platform Research Articles

Monitoring and analysis of vital signs of a patient through a multi-agent application system

In the medical environment, the clinical study of the most basic vital signs of a patient represents the simplest and most effective way to detect and monitor health problems. There are many diseases that can be diagnosed and controlled through regular monitoring of these medical data. The purpose of this study is to develop a monitoring and tracking system for the various vital signs of a patient. In particular, this work focuses on the design of a multi-agent architecture composed of virtual organizations with capabilities to integrate different medical sensors on an open, low-cost hardware platform. This system integrates hardware and software elements needed for the routine measurement of vital signs, performed by the patient or caregiver without having to go to a medical center.

Embedded Component-as-Agent Robotic Software Platform for Autonomous Robots

Robotics is a research area in which the use of software platforms became more challenging, mainly since hardware designs entered a mature phase, open source micro-controllers are accessible now more than ever, providing rich, stable and low-cost hardware platforms. The challenge in this work is to provide a software platform to manage the complexity of controlling and handling hardware components of a robotic system. Over the past decade, several robotic software platforms appeared, offering solutions to the recurrent problems. In this paper we introduce a Component-As-Agent Approach used in a Multi Agent System context, and we present a novel middle-ware system software design and implementation, using the Component-As-Agent approach.

Multi-video processing applications on FPGA

With the increasing needs of processing power in video and image processing for advanced media and communication applications, it is mandatory to go further than the software implementation to provide generic, real time, low cost and high performance hardware platforms. In this paper, we present a re-configurable, hardware platform for video and image processing. The proposed system uses the benefits of field programmable gate array FPGA to attain this objective. In this context, a prototype system is developed based on the Xilinx Virtex-5 FPGA with the integration of embedded processor, embedded memory, multi-port memory controller MPMC, standard interfaces, and different other resources. Our system includes different functional modules: video cut detection, video zoom-in and zoom-out. This provides the flexibility of using this system as a general video processing platform according to different application requirements. The final system utilises ∼16% of logic resource and 20% of on chip memory.

An easily-achieved time-domain beamformer for ultrafast ultrasound imaging based on compressive sensing.

In ultrafast ultrasound imaging technique, how to maintain the high frame rate, and at the same time to improve the image quality as far as possible, has become a significant issue. Several novel beamforming methods based on compressive sensing (CS) theory have been proposed in previous literatures, but all have their own limitations, such as the excessively large memory consumption and the errors caused by the short-time discrete Fourier transform (STDFT). In this study, a novel CS-based time-domain beamformer for plane-wave ultrasound imaging is proposed and its image quality has been verified to be better than the traditional DAS method and even the popular coherent compounding method on several simulated phantoms. Comparing to the existing CS method, the memory consumption of our method is significantly reduced since the encoding matrix can be sparse-expressed. In addition, the time-delay calculations of the echo signals are directly accomplished in time-domain with a dictionary concept, avoiding the errors induced by the short-time Fourier translation calculation in those frequency-domain methods. The proposed method can be easily implemented on some low-cost hardware platforms, and can obtain ultrasound images with both high frame rate and good image quality, which make it has a great potential for clinical application.

High-displacement flexible Shape Memory Alloy actuator for soft wearable robots

This paper describes a flexible Shape Memory Alloy (SMA) actuator designed to increase the limited displacement that these alloys can induce. The SMA actuator has been designed so that it can be bent up to about 180°, providing more freedom of movements and a better integration in wearable robots, specially in soft wearable robots, than standard rigid solutions. Although the actuator length is relatively short, this original design allows a great linear displacement, because it can have one or more loops of the same SMA wire inside the actuator. This implies that the length of the SMA wire is at least two times greater than the length of the actuator. The adopted strategy for both position and speed control that overcomes the hysteresis and prevents overheating the actuator is also described. The control algorithm has been implemented in a rapid control prototyping (RCP) system based on a low cost hardware platform. Finally, the application of this novel actuator in a wrist exoskeleton prototype is shown to demonstrate the feasibility of using the flexible SMA actuator in a real soft wearable robot.

Performance Comparison of Low-cost Hardware Platforms Targeting Physiological Computing Applications

Abstract Although the Arduino is currently the most popular low-cost hardware platform within the Do-it-Yourself (DiY) community, it is not designed taking into account the specific requirements of physiological computing. As a result of previous work by our group, a novel hardware framework for physiological computing, entitled BITalino, was proposed, to allow anyone to create their own projects and applications with biosignal sensors. In this work, we benchmark the Arduino and BITalino platforms, targeting the evaluation of their performance for the purpose of biosignals acquisition. We also describe a few physiological computing applications built with the BITalino, that show the potential of this platform within the engineering community.

Smooth feedrate planning for continuous short line tool path with contour error constraint

In the machining program for free form surfaces, the tool path is usually represented as continuous short lines. For the computer numerical control, the feedrate profile for short line tool path should be smooth and optimized in order to achieve high machining quality and high speed. In high speed machining, the feedrate profile also has a strong influence on contour accuracy. This paper presents a new real-time smooth feedrate planning algorithm for short line tool path, in which the contour error constraint is included. To realize contour error control, the feedrate is adaptively adjusted based on the curvature radius of the tool path, which is directly estimated from the short lines. The 7-phase jerk-limited look-ahead planning is employed to generate a smooth feedrate profile. The target feedrate filter (TFF) and planning units merging techniques are developed to improve the smoothness of the feedrate profile and reduce the overhead on look-ahead. The advantage of the proposed algorithm is that it is not only convenient to achieve the balance among accuracy, smoothness and productivity by adjusting parameters, but also efficient in design, which makes it possible to be implemented on low cost hardware platforms. Experiment results demonstrate the feasibility of the proposed algorithm on smooth feedrate planning and contour error control for continuous short line tool path.

Design and Implementation of the Control System for Two-Wheeled Self-Balancing Vehicles

A control-system design for a two-wheeled self-balancing vehicle is discussed in this paper. We have developed a low-cost hardware platform based on AVR MCU, accelerometer sensor and gyroscope sensor, for which the critical circuits, such as sensors and motor driver, are introduced. The control strategy operates by two steps: a) securing the real-time vehicle posture by integrating the data from accelerometer and gyroscope sensors; b) using a closed-loop PID controller to keep the vehicle balanced. This control system is applied to a prototype two-wheeled self-balancing vehicle, whose performance has turned out to be a satisfaction.

A Complex Space Vector Approach to Rotor Temperature Estimation for Line-Connected Induction Machines With Impaired Cooling

Thermal models used in overload protection relays often fail to predict the rotor temperature for motors with impaired cooling conditions. In this case, the temperature estimated from the rotor resistance can be used as an indicator of the motor's cooling capability. However, this estimated rotor temperature is often corrupted by estimation error due to the asymmetry in the power supply. A detailed analysis of the trajectories of the complex current and voltage space vectors in a synchronous reference frame is presented in this paper, and the negative sequence fundamental frequency components are identified as the major cause of the estimation error. Based on this analysis, a fast and efficient algorithm is proposed to calculate the rotor temperature for line-connected induction machines. By applying the Goertzel algorithm to the complex current and voltage space vectors, constructed directly from the motor terminal measurements, the positive sequence fundamental frequency components are extracted, and the rotor temperature is then estimated with significantly reduced estimation error. Compared to the conventional scheme based on the fast Fourier transform, the proposed algorithm is faster and more efficient, and is therefore more suitable for implementation on a low-cost hardware platform.

Education, Outreach, and Training for High-Performance Computing

Most current models for delivering HPC education, outreach, and training lack support for the next generation of HPC users. The authors present lessons learned in developing and disseminating HPC-enabled tools and curriculum, including their efforts at developing low-cost hardware, software, and curricular platforms for easy classroom and workshop deployment.

High performance I/O architectures and systems

I/O- and data-intensive workloads, as represented by the Grand Challenge problems, multimedia applications, cosmology simulations, climate modeling, and large collaborative visualizations, to name a few, entail innovative approaches to alleviate the I/O (both bandwidth and data access) performance bottlenecks. The advent of low-cost hardware platforms, such as the Beowulf clusters, has opened up numerous possibilities in mass data storage, scalable architectures, and large-scale simulations. The objective of this Special Issue is to discuss problems and solutions, to identify new issues, and to help shape future research and development directions in these areas. From these perspectives, the Special Issue addresses the problems encountered at the hardware, middleware, and application levels, providing conceptual as well as empirical treatments.

External marker-based automatic congruencing: a new method of 3D reconstruction from serial sections.

Computer-based three-dimensional (3D) visualizations reconstructed from sectional images represent a valuable tool in biomedical research and medical diagnosis. Particularly with those imaging techniques that provide virtual sections, such as CT, MRI, and CLSM, 3D reconstructions have become routine. Reconstructions from physical sections, such as those used in histological preparations, have not experienced an equivalent breakthrough, due to inherent shortcomings in sectional preparation that impede automated image-processing and reconstruction. The increased use of molecular techniques in morphological research, however, generates an overwhelming amount of 3D molecular information, stored within series of physical sections. This valuable information can be fully appreciated and interpreted only through an adequate method of 3D visualization. In this paper we present a new method for a reliable and largely automated 3D reconstruction from physically sectioned material. The 'EMAC' concept (External Marker-based Automatic Congruencing) successfully approaches the three major obstacles to automated 3D reconstruction from serial physical sections: misalignment, distortion, and staining variation. It utilizes the objectivity of external markers for realignment of the sectional images and for geometric correction of distortion. A self-adapting dynamic thresholding technique compensates for artifactual staining variation and automatically selects the desired object contours. Implemented on a low-cost hardware platform, EMAC provides a fast and efficient tool that largely facilitates the use of computer-based 3D visualization for the analysis of complex structural, molecular, and genetic information in morphological research. Due to its conceptual versatility, EMAC can be easily adapted for a broad range of tasks, including all modern molecular-staining techniques, such as immunohistochemistry and in situ hybridization.

External marker‐based automatic congruencing: A new method of 3D reconstruction from serial sections

Background Computer-based three-dimensional (3D) visualizations reconstructed from sectional images represent a valuable tool in biomedical research and medical diagnosis. Particularly with those imaging techniques that provide virtual sections, such as CT, MRI, and CLSM, 3D reconstructions have become routine. Reconstructions from physical sections, such as those used in histological preparations, have not experienced an equivalent breakthrough, due to inherent shortcomings in sectional preparation that impede automated image-processing and reconstruction. The increased use of molecular techniques in morphological research, however, generates an overwhelming amount of 3D molecular information, stored within series of physical sections. This valuable information can be fully appreciated and interpreted only through an adequate method of 3D visualization. Methods and results:In this paper we present a new method for a reliable and largely automated 3D reconstruction from physically sectioned material. The ‘EMAC‘ concept (External Marker-based Automatic Congruencing) successfully approaches the three major obstacles to automated 3D reconstruction from serial physical sections: misalignment, distortion, and staining variation. It utilizes the objectivity of external markers for realignment of the sectional images and for geometric correction of distortion. A self-adapting dynamic thresholding technique compensates for artifactual staining variation and automatically selects the desired object contours. Conclusions Implemented on a low-cost hardware platform, EMAC provides a fast and efficient tool that largely facilitates the use of computer-based 3D visualization for the analysis of complex structural, molecular, and genetic information in morphological research. Due to its conceptual versatility, EMAC can be easily adapted for a broad range of tasks, including all modern molecular-staining techniques, such as immunohistochemistry and in situ hybridization. Anat. Rec. 248:583-602, 1997. © 1997 Wiley-Liss, Inc.

Low-cost hardware platform for developing realtime 3D graphics

BRAD3D, a low-cost hardware platform for the development of a realtime 3D graphics software is presented. The BRAD3D configuration is derived from a generalization of 3D image synthesis. Three basic processes have been identified: the geometric process, dealing with the measurements of the scene; the topologic process, extracting visible information from the polygonal structure; and the scan-conversion process, producing pixel values on a frame buffer. BRAD3D is implemented as a three-stage pipeline and accommodates depth-list and scan-line hidden-surface-removal algorithms. Each stage of the pipeline can be implemented using different hardware solutions. A microprocessor-based solution is presented as a general prototyping approach.