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In this paper, the architecture of a modular, service-oriented, Sensor Middleware for data acquisition and processing is presented. The described solution was developed with the purpose of solving two increasingly relevant problems in the context of modern pHealth systems: i) to aggregate a number of heterogeneous, off-the-shelf, devices from which clinical(More)
This paper proposes a methodology for ECG (electrocardiograms) data compression based on R-R segmentation. An ECG can be seen as a quasi-periodic signal, where it is possible to find many similarities between heart beats. These similarities are explored by the proposed compression scheme through the use of a segment dictionary combined with an efficient(More)
It has been 20 years since the concept of the Autonomous Ocean Sampling Network (AOSN) was first introduced. This vision has been brought closer to reality with the introduction of underwater gliders. While in terms of functionality the underwater glider has shown to be capable of meeting the AOSN vision, in terms of reliability there is no communitywide(More)
This paper proposes a new methodology to identify and correlate patterns on nearly periodic signal, based on signal simplification and clustering approaches. Using cubic Bezier curves some significant signal samples (control points), enabling to segment adequately the original signal, are extracted in a first step. Next, given the correlation among(More)
This work describes a lossy Electrocardiogram (ECG) compression algorithm based on R-R segmentation and segment matching. An ECG can be thought of as a quasi-periodic signal, with many similarities existing between heartbeats acquired from the same source. Through the use of an adaptive dictionary, it is possible to explore the similarities between new and(More)
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