Avaliação do comportamento ingestivo utilizando eletromiografia de superfície do músculo masseter

Physiologists and animal scientists try to understand the relationship between ruminants and their environment. The knowledge about feeding behavior of these animals is the key to maximize the production of meat and milk and their derivatives and ensure animal welfare. Within the area called precision farming, one of the goals is to find a model that describes animal nutrition. Existing methods for determining the consumption and ingestive patterns are often time-consuming and imprecise. Therefore, an accurate and less laborious method may be relevant for feeding behaviour recognition. Surface electromyography (sEMG) is able to provide information of muscle activity. Through sEMG of the muscles of mastication, coupled with instrumentation techniques, signal processing and data classification, it is possible to extract the variables of interest that describe chewing activity. This work presents a new method for chewing pattern evaluation, feed intake prediction and for the determination of rumination, food and daily rest time through ruminant animals masseter muscle sEMG signals. Short-term evaluation results are shown and discussed, evidencing employed methods viability.

Ambiente para aquisição e processamento de sinal eletromiográfico de superfície

In this work, a platform to the conditioning, digitizing, visualization and recording of the EMG signals was developed. After the acquisition, the analysis can be done by signal processing techniques. The platform consists of two modules witch acquire electromyography (EMG) signals by surface electrodes, limit the interest frequency band, filter the power grid interference and digitalize the signals by the analogue-to- digital converter of the modules microcontroller. Thereby, the data are sent to the computer by the USB interface by the HID specification, displayed in real-time in graphical form and stored in files. As processing resources was implemented the operations of signal absolute value, the determination of effective value (RMS), Fourier analysis, digital filter (IIR) and the adaptive filter. Platform initial tests were performed with signal of lower and upper limbs with the aim to compare the EMG signal laterality. The open platform is intended to educational activities and academic research, allowing the addition of other processing methods that the researcher want to evaluate or other required analysis.