OSA patient monitoring system based on the Internet of Things framework

Abstract

According to the American Academy of Sleep Medicine (AASM), patients with apnea of 10 seconds or more , and more than 5 times per hour can be diagnosed with sleep disorders. The current gold standard for detecting this type of people with sleep disorder is Polysomnography (PSG). But more than 80% Obstructive Sleep Apnea(OSA) patients of the Sleep Disorder(SD) have not been detected. The reason is that the current configuration of PSG is insufficient in more than 2,500 sleep labs in the United States , and that the lack of manpower of sleep professional technicians who analyze PSG signal has caused many OSA patients to be diagnosed in a timely and effective manner. It is no effective measures to reduce the risk even after OSA patients have been diagnosed. Current medical treatments are either surgical or a lifelong Continuous positive dual channel air pressure ventilator(CPAP). Domestic research shows that OSA patients have poor sleep at night and sleepiness during the day. It often results in inefficient work and causes many traffic accidents. Therefore, how to take effective monitoring measures for these already diagnosed OSA patients has become an urgent problem to be solved.This paper extracts an interactive monitoring system for patients with OSA based on the Internet of Things(IoT) framework. It can reduce the timely rescue of OSA patients when they are in danger in field operations. At the same time, through the interactive function of this indicator mark, the anxiety during the waiting process can be reduced. It is also convenient for the peers to report the progress of the patient in time. The specific method is to use the existing IoT framework. The IoT data acquisition layer uses wearable sensors to collect vital signs of patients, with emphasis on ECG and SpO2 signals. The network layer transmits the collected physiological signals to the Beidou indicator using the Bluetooth Low Energy (BLE) protocol. The platform layer adopts the mature rescue interaction platform of Beidou&GPS. The previous GPS indicator has no short message function, and the patient can only passively wait for rescue. Positional standard is improved through Beidou model, and the short message interaction function has been added. Then the patient can report the progress of the disease in time while waiting for the rescue. After our simulation test, the effectiveness of the OSA patient rescue monitoring system based on the IoT framework has been greatly improved, especially in outdoor work, where the mobile phone signal coverage is relatively weak. The short message function added by the Beidou indicator can be used to provide timely progress of the patient's condition, and provide the medical rescue team with the data support to offer a more accurate rescue plan. After a comparative trial, the rescue rate of the OSA patients with the detection device of this article increased by 10 percentage points compared with the rescue rate with only GPS satellite phones.