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The PhysioNet/CinC 2013 Challenge aimed to stimulate rapid development and improvement of software for estimating fetal heart rate (FHR), fetal interbeat intervals (FRR), and fetal QT intervals (FQT), from multichannel recordings made using electrodes placed on the mother's abdomen. For the challenge, jive data collections from a variety of sources were(More)
With the rapid increase in volume of time series medical data available through wearable devices, there is a need to employ automated algorithms to label data. Examples of labels include interventions, changes in activity (e.g. sleep) and changes in physiology (e.g. arrhythmias). However, automated algorithms tend to be unreliable resulting in lower quality(More)
For medical applications, the ground truth is ascertained through manual labels by clinical experts. However, significant inter-observer variability and various human biases limit accuracy. A probabilistic framework addresses these issues by comparing aggregated human and automated labels to provide a reliable ground truth, with no prior knowledge of the(More)
In foetal electrocardiographic monitoring, assessment of foetal QT (FQT) in identifying foetal hypoxia has been limited mainly due to the lack of available public databases with expert labels. Our proposed platform, CrowdLabel, a web-based open-source annotation system, was developed for crowdsourcing medical labels from multiple expert and/or non-expert(More)
Human bias and significant intra- and inter- observer variance exist in electrocardiogram QT interval evaluation. A Bayesian approach (BA) with an informative prior, that combines measures from multiple humans or algorithms as well as contextual information (such as heart rate and signal quality) was developed for inferring the true QT length. The developed(More)
This paper presents a novel motion vector (MV) steganalysis method. MV-based steganographic methods exploite the variability of MV to embed messages by modifying MV slightly. However, we have noticed that the modified MVs after steganography cannot follow the optimal matching rule which is the target of motion estimation. It means that steganographic(More)
Respiratory rate (RR) is a key vital sign that is monitored to assess the health of patients. With the increase of the availability of wearable devices, it is important that RR is extracted in a robust and noninvasive manner from the photoplethysmogram (PPG) acquired from pulse oximeters and similar devices. However, existing methods of noninvasive RR(More)