Facial electromyography for characterization of emotions using LabVIEW
Dhanshree Thulkar, Tushar Bhaskarwar, Satish Tukaram Hamde · 2015
Knowledge of muscle activity during movements is essential for understanding control strategies of human neuromuscular system. Human face is considered as source of information for revealing a person's affective state. This paper presents a method of recognizing two facial emotions from zygomaticus and corrugator muscles using two channel data acquisition system. Zygomaticus muscles aid in articulation of mouth, nose and cheeks whereas corrugator muscles draws the eyebrows downward producing vertical wrinkles on forehead. The bioelectric signals are recorded using bipolar surface electrode. This raw signal is filtered and windowed. The time domain features like root mean square value (RMS), median value and mean absolute value are extracted. Depending on features extracted thresholding is done and LabVIEW is used in messaging the status of nerve conduction. Thus in this paper we have proposed an optimize technique to record facial muscle potential and transmit the related information of the signal using LabVIEW and GSM (Global system for mobile communication) module using SMS (Short Messaging Service) to infer subject's mood state.