Signal Quality- From Wearables to Hospitals

Heartrate monitors are becoming ubiquitous and are being used by both athletes and the general public to keep track of their health. Heartrate monitors are just an example of the wearables currently available to the public; other examples include oxygen saturation monitors, activity monitors, and muscle activity monitors. Wearables are typically not used in a controlled environment; therefore, the quality of the collected signals might be questionable. Even in a controlled environment such as a hospital, deterioration in the quality of the collected signals can lead to false alarm and reduction in the quality of patient care. As the signals are used to inform users about their health, it is imperative that the signals are of acceptable quality. Signal Quality is the field of identifying and improving the quality of collected signals. Signal Quality can be divided into four categories: 1) detection; 2) identification; 3) quantification; and 4) mitigation. Detection is the acknowledgement of the presence of noise in the signal. Identification is the determination of the type of noise. Quantification is the estimation of the level of the noise. Mitigation is the reduction of the noise through noise removal techniques. This tutorial will provide a high-level overview of the different techniques in each of the Signal Quality categories. Did you know that the IEEE Instrumentation and Measurement Society offers a variety of e-classes? Many of our e-classes allow you to earn CEUs and PHD credits. The e-class for this video tutorial can be accessed here: https://iln.ieee.org/Public/ContentDe... The full list of available videos can be accessed here: https://loom.ly/fikwaQM Keywords: wearables, hospital, Mohamed Abdelazez, IEEE, IMS, signal quality, tutorials, education