Special Topics in Information Technology by Unknown

Author:Unknown
Language: eng
Format: epub
ISBN: 9783030320942
Publisher: Springer International Publishing

The second scenario we consider is the online and long-term monitoring of ECG signals using wearable devices. This is a very relevant problem as it would ease the transitioning from hospital to home/mobile health monitoring. In this case the data we analyze are the heartbeats. As shown in Fig. 5.1b, normal heartbeats feature a specific morphology, while the shape of anomalous heartbeats, that might be due to potentially dangerous arrhythmias, is characterized by a large variability. Since the morphology of normal heartbeats depends on the user and the position of the device [16], the anomaly-detection algorithm has to be configured every time the user places the device.

Monitoring this kind of datastream raises three main challenges: at first data are characterized by complex structure and high dimension and there is no analytical model able to describe them. Therefore, it is necessary to learn models directly from data. However, only normal data can be used during learning, since acquiring anomalous data can be difficult if not impossible (e.g., in case of ECG monitoring acquiring arrhythmias might be dangerous for the user). Secondly, we have to careful design indicators and rules to assess whether incoming data fit or not the learned model. Finally, we have to face the domain adaptation problem, since normal condition might changes during time and the learned model might not be able to describe incoming normal data, thus it has to be adapted accordingly. For example, in ECG monitoring the model is learned over a training set of normal heartbeats acquired at low heart rate, but the morphology of normal heartbeats changes when the heart rate increases, see Fig. 5.2b.

Fig. 5.2a Details of SEM images acquired at different scales. The content of these images is different, although they are perceptually similar. b Examples of heartbeats acquired at different heart rate. We report the name of the waveforms of the ECG [13]

Download

Copyright Disclaimer:
This site does not store any files on its server. We only index and link to content provided by other sites. Please contact the content providers to delete copyright contents if any and email us, we'll remove relevant links or contents immediately.