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Publicações

Publicações por José Machado da Silva

2003

Computing ADC harmonic content from a reduced number of values

Autores
Mendonca, HS; da Silva, JM; Matos, JS;

Publicação
IMTC/O3: PROCEEDINGS OF THE 20TH IEEE INSTRUMENTATION AND MEASUREMENT TECHNOLOGY CONFERENCE, VOLS 1 AND 2

Abstract
The estimation of the harmonic content of an ADC output is fundamental to evaluate its suitability to perform according the requirements specified for an application. The use of the traditional frequency analysis leads to a large hardware overhead due to the amount of on-chip processing being involved, or to a large quantity of data to be transferred in case the processing is performed in a tester. This paper presents an algorithm capable of estimating the harmonics with similar accuracy but with the advantage of being more suitable for a BIST implementation, since it requires a reduced number of on-chip operations, and that only a small set of values has to be supplied outside the chip for further processing. It relies, on the fact that harmonics generated by an ADC are mathematical related with the polynomial coefficients of its transfer function. ADC offset and gain errors can also be measured.

2005

A processor for testing mixed-signal cores in System-on-Chip

Autores
Duarte, F; da Silva, JM; Alves, JC; Pinho, GA; Matos, JS;

Publicação
DSD 2005: 8th Euromicro Conference on Digital System Design, Proceedings

Abstract
This paper describes the design of a processor specific for testing cores embedded in system-on-chip. This processor which can be implemented within a system's reconfigurable area, shall be responsible for scheduling and control test operations and perform preliminary data processing, as well as to provide the interface with an external tester Building these test operations on-chip allows for simplifying external tester interface and to reduce testing time. The testing procedure and the infrastructure required to test an AID converter is described as an example.

2008

Estimation of analogue-to-digital converter's signal-to-noise plus distortion ratio using the code histogram method

Autores
Mendonca, HS; da Silva, JM; Matos, JS;

Publicação
IET SCIENCE MEASUREMENT & TECHNOLOGY

Abstract
A procedure is proposed to estimate an analogue-to-digital converter's signal-to-noise plus distortion ratio using the histogram method. The procedure provides results that are in close agreement with the ones obtained with the spectral analysis and sinewave fitting methods. It is shown that the errors obtained by using former implementations of the histogram method are due to not considering the input stimulus probability density function, and it is shown how these errors can be rectified.

2016

Fault Diagnosis in Highly Dependable Medical Wearable Systems

Autores
Oliveira, CC; da Silva, JM;

Publicação
JOURNAL OF ELECTRONIC TESTING-THEORY AND APPLICATIONS

Abstract
High levels of dependability are required to promote the adherence by public and medical communities to wearable medical devices. The study presented herein addresses fault detection and diagnosis in these systems. The main objective resides on correctly classifying the captured physiological signals, in order to distinguish whether the actual cause of a detected anomaly is a wearer health condition or a system functional flaw. Data fusion techniques, namely fuzzy logic, artificial neural networks, decision trees and naive Bayes classifiers are employed to process the captured data to increase the trust levels with which diagnostics are made. Concerning the wearer condition, additional information is provided after classifying the set of signals into normal or abnormal (e.g., arrhythmia, tachycardia and bradycardia). As for the monitoring system, once an abnormal situation is detected in its operation or in the sensors, a set of tests is run to check if actually the wearer shows a degradation of his health condition or if the system is reporting erroneous values. Selected features from the vital signals and from quantities that characterize the system performance serve as inputs to the data fusion algorithms for Patient and System Status diagnosis purposes. The algorithms performance was evaluated based on their sensitivity, specificity and accuracy. Based on these criteria the naive Bayes classifier presented the best performance.

2019

Literature on Wearable Technology for Connected Health: scoping review on research trends, advances and barriers (Preprint)

Autores
Loncar-Turukalo, T; Zdravevski, E; Machado Da Silva, J; Chouvarda, I; Trajkovik, V;

Publicação

Abstract
BACKGROUND

In the last decade the advances in wearable technology have driven and transformed performance monitoring in fitness and wellness applications, surveillance in extreme (working) conditions, and management of chronic diseases. These innovations have opened a whole new perspective on health and social care, challenged by vast expenditures in ageing societies.

OBJECTIVE

The aim of this study is to scope the scientific literature in the field of pervasive wearable health monitoring in the time interval 2010-2019, identify chronological research trends and milestones, enabling technology innovations, and spot the gaps and barriers from technology and user perspectives.

METHODS

This study follows the scoping review methodology and PRISMA guidelines to identify and process the available literature. As the scope surpasses the possibilities of manual search, we rely on Natural Language Processing (NLP) to ensure efficient and exhaustive search of the literature corpus in three large digital libraries: IEEE, PubMed and Springer. The search is based on keywords and properties to be found in the articles using the search engines of the digital libraries.

RESULTS

The chronological analysis highlights the increasing numbers of publications that address health-related wearable technologies resulting from collaborative work on a global scale. The identified articles indicate the research focus on technology, delivery of prescriptive information, and user (data) safety and security. The literature corpus evidences major research progress in sensor technology (with regard to miniaturization and placement), communication protocols, data analytics, and evolution of cloud and edge computing powered architectures. The most addressed user related concerns are (technology)acceptance and privacy. The research lag in battery technology puts energy-efficiency as relevant consideration both in the design of sensor and network architectures with computational offloading. User-related gaps indicate more efforts should be invested into formalizing clear use-cases with timely and valuable feedback and prescriptive recommendations.

CONCLUSIONS

There is no doubt that wearable technology is a key enabler of a new model of healthcare delivery. While technology is driving the transformation, there is ongoing research resolving the user concerns related to reliability, privacy, comfort, and delivered feedback. The current research focus is on sustainable delivery of valuable recommendations, the enforcement of privacy by design, and technological solutions for energy-efficient pervasive sensing, seamless monitoring, and low-latency 5G communications.

2023

An Introduction to the Evaluation of Perception Algorithms and LiDAR Point Clouds Using a Copula-Based Outlier Detector

Autores
Reis, N; da Silva, JM; Correia, MV;

Publicação
REMOTE SENSING

Abstract
The increased demand for and use of autonomous driving and advanced driver assistance systems has highlighted the issue of abnormalities occurring within the perception layers, some of which may result in accidents. Recent publications have noted the lack of standardized independent testing formats and insufficient methods with which to analyze, verify, and qualify LiDAR (Light Detection and Ranging)-acquired data and their subsequent labeling. While camera-based approaches benefit from a significant amount of long-term research, images captured through the visible spectrum can be unreliable in situations with impaired visibility, such as dim lighting, fog, and heavy rain. A redoubled focus upon LiDAR usage would combat these shortcomings; however, research involving the detection of anomalies and the validation of gathered data is few and far between when compared to its counterparts. This paper aims to contribute to expand the knowledge on how to evaluate LiDAR data by introducing a novel method with the ability to detect these patterns and complement other performance evaluators while using a statistical approach. Although it is preliminary, the proposed methodology shows promising results in the evaluation of an algorithm's confidence score, the impact that weather and road conditions may have on data, and fringe cases in which the data may be insufficient or otherwise unusable.

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