P. Silva Girão

Fitting transducer characteristics to measured data

There are no rules to select the best curve-fitting method for a given set of data. This problem is of great importance in measurement applications. Optimizing analog and digital methods for a transducers characteristic interpolation or linearization is a field where constant research is being done, particularly since auto-calibration and self-test of intelligent transducers is a topic of major interest. We present an overview of classical methods for data interpolation and least mean squares regression. We make a comparative evaluation of the relative performance of polynomial and artificial neural networks approximations to measurement data with particular attention paid to the reduction of the required calibration set dimension to obtain a given accuracy.

A temperature-compensated system for magnetic field measurements based on artificial neural networks

This paper presents a personal-computer-controlled system, assembled mainly with IEEE 488 general purpose instruments and aimed at the measurement of magnetic field intensity. The main sensor element in the system is a magnetoresistive field sensor which includes four permalloy strips connected in a Wheatstone bridge configuration. The temperature dependence of this sensor can vary almost 25% in the experimental operating temperature range (20/spl deg/C-100/spl deg/C). In order to overcome this problem, a two-terminal integrated circuit temperature transducer is connected to the system, and its temperature information is used to correct the temperature drift error of the magnetic sensor. Artificial neural networks are used for data reduction and final results show an improvement in the systems accuracy from 20% to 2%.

Real-Time Sensing Channel Modelling Based on an FPGA and Real-Time Controller

This paper presents the concept of reconfigurable sensing channel characteristics inverse model in auto-calibration measurement systems, particularly for water quality measuring systems. The inverse model implementation is supported on an advanced FPGA reconfigurable embedded control and acquisition system (CompactRIO). Model blocks, such as polynomial and neuronal, are on-line updated (reconfigured) in the cRIO real time controller using calibration data while the on-line processing of the measured physical quantities (e.g. water quality quantities: conductivity) are mainly processed by the RIO FPGA core

Toward developing a smart wheelchair for user physiological stress and physical activity monitoring

The article presents a smart wheelchair characterized by embedded sensors and an acquisition, processing and communication platform based on a multifunction I/O module and an embedded PC for monitoring of physiological stress parameters and motion activity of the wheelchair user in unobtrusive way. The embedded sensors include E-textile electrodes attached to the wheelchair arms and a 3D MEMS accelerometer used to extract the motion activity information. Additional sensing channels, expressed by piezoresistive flexible force sensors are used to optimize the measurement of contact ECG and skin conductivity. A server application, developed in LabVIEW and hosted on the embedded computer, delivers information about the digital processed signals to the client application installed in mobile platforms such as tablet PC or smartphones. The mobile platform provides interface for nurses, physiotherapists or physicians as well as for the wheelchair user or informal caregivers.

Dithering performance of oversampled ADC systems affected by hysteresis

Abstract This paper addresses the problem of hysteresis in ADC systems and the improvement that can be obtained in the performance of such systems with the use of dithering and oversampling. The paper starts with an analysis of ADC hysteresis errors considering their effect on the quantization error and effective number of bits of an ADC system. It concludes with a study of the improvements obtained using dithering in over sampled ADC systems with hysteresis errors. Special attention is paid to the effect of different time sequences of a deterministic dither signal. Experimental results that validate theoretical predictions are also presented.

Static and dynamic testing of A/D converters using a VXI based system

A VXIbus based system to test analog to digital converters (ADCs) is presented. The system can perform both static and dynamic tests. In the static test the input voltage of the converter is generated by an IEEE 488 programmable dc calibrator. Dynamic test is based on the analysis of the converter output when a known sinusoidal input voltage is applied to the ADC. The differential and integral nonlinearities, gain and offset errors of the converter are obtained in both tests. Results for a 12 bit ADC are presented.<<ETX>>A VXIbus based system to test analog to digital converters (ADCs) is presented. The system can perform both static and dynamic tests. In the static test the input voltage of the converter is generated by an IEEE 488 programmable dc calibrator. Dynamic test is based on the analysis of the converter output when a known sinusoidal input voltage is applied to the ADC. The differential and integral nonlinearities, gain and offset errors of the converter are obtained in both tests. Results for a 12 bit ADC are presented. >

IEEE 1451.1 Standard and XML Web Services: a Powerful Combination to Build Distributed Measurement and Control Systems

In 2005, we presented the NCAP/XML, a prototype of NCAP (network capable application processor) that runs under the .NET framework and makes available its functionality through a set of Web services using XML (extended Markup Language). Giving continuity to this project, it is time to explain how to use the NCAP/XML to build a distributed measurement and control system (DMCS) compliant with the 1451.1 std. This paper is divided in two main parts: in the first part, we present the new software architecture of NCAP/XML (which suffered some changes since the first version), and secondly, we describe the network configuration of a Web-enabled DMCS, which includes several NCAP/XML stations, a database and a Web server

Smart Flexible Turbidity Sensing Based on Embedded Neural Network

This paper presents a flexible turbidity sensing system that implements single and multiple infrared (IR) beam architectures. The hardware includes two pairs of IR LED - IR photodiode whose relative position permits the materialization of different architectures for turbidity optical measurement. The control of the sensing architecture is performed by a microcontroller based I/O board that is wireless connected to a PC for advanced control and data processing based on neural networks. Using intelligent processing procedures, the best turbidity measurement architecture is selected in terms of measurement accuracy for a given turbidity level. Elements of neural network design, optimization and embedding as part of an advanced processing software component are presented.

Health status and air quality parameters monitoring based on mobile technology and WPAN

The paper presents a Wireless Personal Area Network (WPAN) including two Bluetooth-enabled measuring nodes that delivers information about some physiological parameters extracted from photo-plethysmographic signals and provides information of indoor air temperature and relative humidity. The data from the node of physiological and air parameters measurement are received by a smart phone device through Bluetooth communication. J2ME developed software assures Bluetooth device detection and identification, data reading, primary processing, data storage and automatic alarm generation. Critical health status associated with the assessed person leads to an automatic SMS generation. Elements related to Heart-Rate Variability (HRV) estimation are also included in the paper. This is an expanded version of a paper presented at the 3rd IEEE International Workshop on Medical Measurements and Applications, 9 10 May 2008, Ottawa, ON, Canada.

Microwave Doppler radar in unobtrusive health monitoring

This article frames the use of microwave Doppler radar in the context of ubiquitous, non-obstructive health monitoring. The use of a 24GHz CW (continuous wave) Doppler radar based on a commercial off-the-shelf transceiver for remote sensing of heart rate and respiration rate based on the acquisition and processing of the signals delivered by the radar is briefly presented.