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A novel video processing-based method for remote estimation of the respiratory rate (RR) is proposed. Relying on the fact that breathing involves quasi-periodic movements, this technique employs a generalized model of pixel-wise periodicity and applies a maximum likelihood (ML) criterion. The system first selects suitable regions of interest (ROI) mainly affected by respiratory movements. The obtained...
In this paper, we present Smartphone-based Contactless Epilepsy Detector (SmartCED): an Android monitoring application able to diagnose neonatal clonic seizures and warn about their possible occurrences in realtime. SmartCED has, however, wider applicability so that it could also be used on adult patients. The main goal is to implement a wire-free and low-cost epilepsy diagnostic system, executing...
This paper presents a video simulator of apnoea episodes. A simple Continuous-Time Markov Chain (CTMC) model, describing the apnoea statistical behaviour, is combined with a properly designed video processing tool to insert apnoea episodes in the video recording of a normally breathing patient. In particular, the simulator has been applied to videos of newborns in order to simulate respiratory arrests...
In this paper, we present a wire-free, low-cost video processing-based technique for respiratory rate (RR) estimation. The proposed method blends together two recently presented techniques, with the purpose of emphasizing small movements, such as respiratory movements possibly present in a video stream, in order to detect them. Initially, the system performs a spatial decomposition of the video frames...
In this paper, we consider a novel low-complexity real-time image-processing-based approach to the detection of neonatal clonic seizures. Our approach is based on the extraction, from a video of a newborn, of an average luminance signal representative of the body movements. Since clonic seizures are characterized by periodic movements of parts of the body (e.g., the limbs), by evaluating the periodicity...
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