COVID-19: Utilizing Smart Phone Sensors and Activity Trackers for Remote Vitals Monitoring and Screening

为了方便筛查患者并改善对COVID-19或其他健康问题的风险因素的识别，我们建议使用每个智能手机以及不同活动跟踪器中的传感器，以实现对远程监控和筛查的生命体征的客观计算。 我们建议应用信号处理和机器学习技术来开发一种可靠的方法来确定呼吸率，呼吸质量，心率，心率质量和呼吸或心律异常，使用任何现代Android或iOS智能手机的可用传感器-特别是三轴加速度计和三轴陀螺仪。 然后，这些信息将与任何现有的外部健身追踪器和其他智能传感器（智能秤、心率监测器、智能手表等）提供的读数融合，以增强内部手机数据处理。 这些信息一旦与患者症状的主观信息相结合，将为护士提供更完整的信息，并将改善COVID-19的筛查、分诊和监测过程。

To facilitate the screening of patients and to improve identification of risk factors for COVID-19, or other health issues, we propose to use sensors present in every smart phone as well as from different activity trackers, to enable objective computation of vitals for remote monitoring and screening. We propose to apply signal processing and machine learning techniques to develop a reliable method to determine respiration rate, respiration quality, heart rate, heart rate quality and anomalies in respiration or heart rhythm using the available sensors of any modern Android or iOS smart phone - particularly three-axis accelerometers and three-axis gyroscopes. This information will then be fused with readings provided by any present external fitness trackers and other smart sensors (smart scales, heart rate monitors, smart watches, etc) to augment internal phone data processing. This information, once blended with subjective information on symptoms from the patient, will provide nurses with a more complete picture and will improve the screening, triaging, and monitoring process for COVID-19.