**1. Introduction**

The development and widespread use of electrically powered technology has grown exponentially since the 1960s. Modern homes and offices routinely have flat-screen TVs, microwave ovens, WIFI, and air conditioning systems. Technology requires power in either Alternating Current (AC) or Direct Current (DC) form. Cellular, WIFI, satellite, and other Radio Frequency (RF) devices provide communication between technologies. The widespread use of wired and wireless technologies has led to increased Electromagnetic Interference (EMI) due to Electromagnetic Fields (EMF) in its many forms. Electromagnetic Fields (EMF) are generated by both the source of power, and the technology device that is powered. Electromagnetic

Interference (EMI), or "electrical noise" is the unwanted disturbance in a circuit caused by EMF [1].

EMI creates problems for the electrophysiologist attempting to extract bioelectric signals from the body, especially when those signals are in the microvolt (μV) range such as Surface Electromyography (SEMG), ECG and EEG [2]. Wireless devices have been quickly replacing wired devices in every area of technology. Smart meters are replacing water, gas and power meters in both residential and commercial applications. WIFI routers and microwave based WIFI blanket many towns and cities. Cellular towers, cellular phones and Bluetooth devices all contribute to EMI. In addition to wireless signals, the impact of the electric vehicle has led to an increase in the transmission of high levels of AC power with powerlines the area we live and work. Wireless devices along with EMF generated by power sources contribute to EMI or EMF, potentially damaging the integrity of bioelectric signals as measured at the human body.

In the past decade, there has been a disturbing trend toward clinicians relying upon computer-analyzed ECG/ECG bioelectric data and making clinical decisions based on erroneous results [3]. Unfortunately, many clinicians no longer understand ECG graphs or understand the subtle meaning of the graphed analog signal. This lack of knowledge means there is a higher probability that they will not be aware of the impact of EMI on electrophysiologic evaluations, and the importance of obtaining a clean signal before being processed by the computer.

There are many methods of filtering out EMI, from hardware-based filtering to software algorithms. The best method of preserving the integrity of a bioelectric signal is to reduce the impact of EMI at the source of the biological signal.

Surface Electromyography (SEMG) is a measurement of muscle activity. A pubmed.gov search of the term yields over 13,500 peer-reviewed studies, including the evaluation for presence or absence of back pain and soft tissue injury [4] and workplace ergonomics evaluations. Since this technology measures muscle activity in the microvolt range, it is extremely susceptible to EMI and is a good tool to use when evaluating a location for EMF/EMI. The device utilizes high gain differential amplifiers, and sensors comprised of a metallic electrode with conductive medium which is placed on the skin above the muscles of greatest interest. When performed with the proper equipment and controlling for EMI, the device can extract a microvolt level signal produced by motor units beneath the skin [5].

EMI can make SEMG extremely difficult to measure, making it a perfect tool for evaluating methods of eliminating EMI. The microphone is another device that allows you to"hear" the presence of EMI (constant "hum" in the speakers), and quickly determine when EMI has been removed. Troubleshooting EMI with a commercially available microphone requires the same troubleshooting steps that apply to eliminating EMI's impact on bioelectric signals.
