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As wireless devices proliferate, the ability to obtain a clean, analog, bioelectric signal becomes challenging. Digital filtering algorithms have become extremely sophisticated, yet there is the possibility that much of the unique characteristics of the original signal may be significantly altered by these algorithms. Many clinicians and researchers have developed complete trust in these computer algorithms, losing their ability to discriminate between quality data and that contaminated by Electromagnetic Interference (EMI).  The result?  Clinical decisions may be compromised due to the lack of quality data. Understanding the principles of analog electronics for reduction of EMI teaches the clinician and researcher how to evaluate for contaminated data and how to obtain a cleaner signal prior to digital processing.  Presented is a pragmatic process for eliminating or attenuating EMI at the sensor interface with the body using real-life scenarios. Perhaps one of the best use-case scenarios for evaluating EMI is by testing the principles of EMI reduction with Surface Electromyography (SEMG).  SEMG measures a summation of depolarizations beneath the skin at the location of electrode contact.  With signals in the microvolt (µV) range, eliminating EMI is crucial in obtaining clinically relevant data. This chapter will discuss sources of EMI and various means of mitigating their impact on bioelectric signal quality utilizing Surface EMG, EKG and the microphone as practical use-case scenarios.

Protecting Bioelectric Signals from Electromagnetic Interference in a Wireless World