THE IMPACT OF ELECTROMAGNETIC KINEMATIC TRACKING SYSTEM INTERFERENCE ON EMG DATA USED TO DETERMINE MUSCLE ONSETS

Abstract

PURPOSE: Electromagnetic (EM) kinematic tracking systems have gained popularity in recent years due to their ability to quickly capture 6 degree-of-freedom position data. EM systems work by sequentially creating orthogonally oriented magnetic fields in which the receivers locate themselves. The purpose of this investigation was to determine the impact of the EM signal on surface EMG data and to provide suggested methods for reducing any detrimental effects. EQUIPMENT / METHODS: EM signals are produced by EM kinematic tracking systems. The EM field-strength varies as a function of the distance from the transmitter. The frequency varies as a function of the selected kinematic sampling rate. These combine to produce a non-stationary signal that can contaminate EMG data. Raw EMG data was collected from the quadriceps and hamstring muscles on subjects performing a squatting task and a jumping task in the presence of an EM transmitter. Both tasks were performed with and without the transmitter on. Data were collected at 1000 Hz. ANALYSIS Data from all trials were qualitatively assessed for the appearance of EM contamination. These data were then processed to evaluate the impact of the EM signal on muscle timing analyses. Power spectrums of the data were computed using a Fast Fourier Transform (FFT) algorithm. This spectral information was used to create digital filters to remove the EM signal from the raw data. RESULTS The EM signal was present in the EMG data for all trials performed in the presence of an active EM transmitter. In many cases, this signal was strong enough to completely mask the EMG signal. The muscle timing analysis of contaminated data were unable to accurately quantify onsets. Digital filtering successfully removed the EM noise and provided muscle latencies that were comparable to those found from the analysis of the uncontaminated data. CONCLUSIONS Digital filtering is an effective way of removing EM contamination from EMG data. When using this method, care should be taken to collect raw EMG data at a sampling rate that is consistent with the digital filtering requirements. RELEVANCE Extraneous EM signals have historically been part of EMG data collection. Many commercial systems have built-in notch filters to contend with 60Hz interference. The advent of EM tracking systems produces a need to re-evaluate processing techniques for EMG data collected in these environments.