0000000000682765
AUTHOR
Fabrizio Argenti
Adaptive quadratic regularization for baseline wandering removal in wearable ECG devices
The electrocardiogram (ECG) is one of the most important physiological signals to monitor the health status of a patient. Technological advances allow the size and weight of ECG acquisition devices to be strongly reduced so that wearable systems are now available, even though the computational power and memory capacity is generally limited. An ECG signal is affected by several artifacts, among which the baseline wandering (BW), i.e., a slowly varying variation of its trend, represents a major disturbance. Several algorithms for BW removal have been proposed in the literature. In this paper, we propose new methods to face the problem that require low computational and memory resources and th…
Regularized LMS methods for baseline wandering removal in wearable ECG devices
The acquisition of electrocardiogram (ECG) signals by means of light and reduced size devices can be usefully exploited in several health-care applications, e.g., in remote monitoring of patients. ECG signals, however, are affected by several artifacts due to noise and other disturbances. One of the major ECG degradation is represented by the baseline wandering (BW), a slowly varying change of the signal trend. Several BW removal algorithms have been proposed into the literature, even though their complexity often hinders their implementation into wearable devices characterized by limited computational and memory resources. In this study, we formalize the BW removal problem as a mean-square…
3D Map Computation from Historical Stereo Photographs of Florence
The analysis of early photographic sources is fundamental for documenting and understanding the evolution of a city so rich in history and art as Florence. Indeed, by the 1860s several photographers used to work in town, and their images (often obtained through stereoscopic set-ups) can help us to reconstruct Florence in 3D as it was by the time of the Italian unification. The first and most delicate part of such reconstruction process is the computation of disparity maps from the historical stereo pairs. This is a very challenging task for fully-automatic computer vision algorithms, since XIX century photographs are affected by several problems—ranging from superficial damages to asynchron…