Development of Wearable Pulse Oximeter Based on Internet of Things and Signal Processing Techniques

Abstract

Blood oxygen saturation is an important physiological parameter involved in respiration and circulation, which is also a critical indicator in the area of medical and health monitoring. Wearable non-invasive blood oxygen saturation monitoring approaches overcomes the shortcomings of the traditional approaches, and reflects the tendency to change of breathing function in real time, which has great advantages for monitoring at home. Thanks to the Internet of Things and advanced signal processing algorithms, we have developed wearable pulse oximeters. These devices are able to detect users' physiological data such as blood oxygen saturation (SpO <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sub> ), pulse rate (PR), and perfusion index (PI). These data can then be transmitted to an APP for intelligent mobile devices. Then, the data could be uploaded to a server to generate a report. Accordingly medical personnel will know patients' medical condition. Finally, the accuracy of the device has been verified by the experiment conducted on the simulator.