Clinical Biomedical Engineering Research Group

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EPSRC Network: Advanced Microtechnologies for Microsurgery

Evaluation of Changing State in Body Functions

The principal objective of the research is to derive and evaluate an automated identification method that can be applied generically to detect and evaluate the state of body functions using coupled Electromyographic (EMG) signals in the time-space domain.

The research is based on the hypothesis that the body system presents highly non-linear complexity and that the body functions are coupled with each other. From the non-linear coupling dynamics between processes and tissues of the body, system parameters can be derived to detect and predict the onset of fatigue during lengthy microsurgical procedures.

Surface electrode EMG data is captured from muscles of interest and analyzed for any defining patterns. Muscle fatigue is generally determined by examining differences in an EMG signal’s Power Spectral Density (PSD). Fatigue is demonstrated by a shift in the mean frequency value as well as a decrease in power. These lower frequencies present themselves because of physiological tremors in the muscles and the lower energy associated with the slowing muscle activation.

Fatigue can also be determined by examining at the complexity of a signal. This method consists of embedding the EMG time series from a single muscle and characterizing the complexity of the signal. This is computed from the system’s singular values and entropy. The patterns associated with an increase in entropy reveal a development towards fatigued muscles.

Fine finger precision also deteriorates over time with the development of fatigue. The associated tremors can adversely affect a micro-surgeon’s performance. Detection of these tremors is therefore relatively important. They can be detected using accelerometers positioned on the surgical tool, or directly on the surgeon. They can also be detected through EMG measurement. Therefore coupling the collected EMG data with that of the accelerometer should provide an alternative method for determining the onset of fatigue and tremor.

Thus far in the project, a preliminary fatigue analysis has been performed using both conventional mean frequency and complexity methods. In addition, a demonstrator system has been manufactured to assist with consistent EMG measurement and motion capturing.