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In this paper, we present a non-invasive, low-cost, wire-free video processing-based approach to neonatal apnoea detection. Our method consists in evaluating the presence or absence of apnoea events through an innovative analysis of a motion signal extracted from a video live capturing or recording of a patient. In particular, we pre-process the video by a recently proposed selective magnification...
In this paper we consider the use of a well-known statistical method, namely Maximum-Likelihood Detection (MLD), to early diagnose, through a wire-free low-cost video processing-based approach, the presence of neonatal clonic seizures. Since clonic seizures are characterized by periodic movements of parts of the body (e.g., hands, legs), by evaluating the periodicity of the extracted signals it is...
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