Pulse Oximetry : Signal Processing in real time on Raspberry Pi

Detta är en Master-uppsats från KTH/Skolan för teknik och hälsa (STH)

Författare: Malin Thunholm; [2017]

Nyckelord: Pulse Oximetry; Raspberry Pi; Signal processing; Filtering; RespiHeart; Healthcare; Python; FIR; IIR; Filter; IMSE RToS; Matlab; Electronic Health Record; Real Time; Pulsoximetri; Raspberry Pi; Signalbehandling; Filtrering; RespiHeart; Sjukvård; Python; FIR; IIR; Filter; IMSE RToS; Matlab; Elektronisk Patient Journal; Realtid;

Sammanfattning: This thesis introduces the reader into RespiHeart, which is a product under development. RespiHeart is an complement/alternative to the regular Pulse Oximeter and is intended to be used within the health care sector for combined measurements and communication on open inexpensive platforms. This thesis evaluates interaction between RespiHeart and a Raspberry Pi 3 Model B to evaluate if the computer is capable of handling the data from RespiHeart and make signal processing. Python is used throughout the whole project and is a suitable language for interaction and signal processing in real time.

  HÄR KAN DU HÄMTA UPPSATSEN I FULLTEXT. (följ länken till nästa sida)