This paper aims to study the performance of support vector machine (SVM) classification in detecting asthma attacks in a wireless\nremotemonitoring scenario.Theeffect of wireless channels on decision making of theSVMclassifier is studied in order to determine\nthe channel conditions under which transmission is not recommended from a clinical point of view. The simulation results show\nthat the performance of the SVM classification algorithm in detecting asthma attacks is highly influenced by themobility of the user\nwhere Doppler effects are manifested. The results also show that SVM classifiers outperform other methods used for classification\nof cough signals such as the hidden markov model (HMM) based classifier specially when wireless channel impairments are\nconsidered.
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