2014/04/30 by Hoda Daou, Daou, Hoda, Fabrice Labeau +1
Engineering · Medicine · Neuroscience · #Analog and Mixed-Signal Circuit Design #ECG Monitoring and Analysis #EEG and Brain-Computer Interfaces #FOS: Computer and information sciences #Information Theory (cs.IT)
paper · pdf · doi:10.48550/arxiv.1405.0086
openalex publication_date 2014/04/30 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28
Biomedical signals aid in the diagnosis of different disorders and\nabnormalities. When targeting lossy compression of such signals, the medically\nrelevant information that lies within the data should maintain its accuracy and\nthus its reliability. In fact, signal models that are inspired by the\nbio-physical properties of the signals at hand allow for a compression that\npreserves more naturally the clinically significant features of these signals.\nIn this paper, we illustrate this through the example of EEG signals; more\nspecifically, we analyze three specific lossy EEG compression schemes. These\nschemes are based on signal models that have different degrees of reliance on\nsignal production and physiological characteristics of EEG. The resilience of\nthese schemes is illustrated through the performance of seizure detection post\ncompression.\n