A4 Vertaisarvioitu artikkeli konferenssijulkaisussa
Biosignal Feature Extraction Techniques for IoT Healthcare Platform
Tekijät: Amleset, Kelati; Ethiopia, Nigussie; Juha, Plosila; Hannu, Tenhunen
Konferenssin vakiintunut nimi: IEEE Conference on Design and Architectures for Signal and Image Processing, DASIP2016
Kustannuspaikka: France
Julkaisuvuosi: 2016
Sarjan nimi: DASIP 2016, ECSI Resource Center
Verkko-osoite: https://ecsi.org/dasip/program
In IoT healthcare platform, a variety of biosignals are acquired from its sensors and appropriate feature extraction techniques are crucial in order to make use of the acquired biosignal data and help the healthcare scientist or bio-engineer to reach at optimal decisions. This work reviews the existing biosignal feature extraction and classification methods for different healthcare applications. Due the enormous amount of different biosignals and since most healthcare applications uses electrocardiogram (ECG), electroencephalogram (EEG), electromyogram (EMG), Electrogastrogram (EGG), we focus the review on feature extractions and classification method for these biosignals. The review also includes a summary of Blood Oxygen Saturation determined by Pulse Oximetry (SpO2), Electrooculography and eye movement (EOG), and Respiration (RSP) signals. Its discussion and analysis focuses on advantages, performance and drawbacks of the techniques.
Ladattava julkaisu This is an electronic reprint of the original article. |  |
