Introduction
Emotion is a critical element among human beings. Individuals experience various feelings in their day to day interactions. In this respect, there is a need to detect the various emotions that humans experience. There are various techniques that have been established to assist in the detection of emotions. The different techniques have been established to measure the voice and facial expressions. Some of the techniques used in the measurement of emotions include the Electroencephalographic (EEG), Facial Electromyography (EMG) and Galvanic Skin Response (GSR). These are some of the techniques that are used in the determination of the physiological process of a smile. This paper shall compare the facial EMG, with EEG and GSR with the aim of establishing a system that can be used to identify evoked smiles. This will include evoked smiles even from paralyzed patients and other patients that do not have any facial movements.
The Facial Electromyography (EMG)
The facial Electromyography (EMG) can be defined as a technique used in taking measurement of muscular activities. The EMG detects and amplifies the minute electrical impulses released by the muscular fibers upon contraction (Broek, Schut, Westerink, Herk and Tuinenbreijer, 2006; Dimberg, 1990). Essentially, this technique focuses on facial muscles that are related to smiling and frowning. These muscles include the zygomaticus major muscle and the corrugator supercilli muscle respectively. Studies indicate that the corrugator supercilli muscle, which is associated with frowning, often lowers the eyebrow. On the other hand, the zygomaticus major muscle has been identified with smiling (Larsen, Norris and Cacioppo, 2003). In this respect, the muscle is associated with positive emotions. Notably, the facial EMG can be used in detection of both positive and negative emotions. This technique has proved efficient in the investigation of emotions among patients suffering from autism (Wolf, et al., 2005; Sato, Fujimura and Suzuki, 2008).
Electroencephalographic (EEG)
The brain is regarded as the central nervous system of the human body. In this respect, the brain has numerous neurons that have electric charges (Eysenck, 1967). The Electroencephalographic (EEG) is a method used in measuring the electrical action on the scalp (Gale, 1983). This technique is used to measure the variations in voltage that emanate from the brain activity. Therefore, EEG is an approach that is used in determining the electrical activity in the brain (Achaibou, Pourtois, Schwartz and Vuillemier, 2008). This is done by placing numerous electrodes on the scalp. The electric charges produced by a single neuron cannot be detected by the EEG. In this respect, the EEG can only detect the activity from numerous neurons with the same spatial alignment (Mulholland, 1973). When there is a lack of spatial alignment, the ions cannot be aligned and thus cannot be detected by the EEG. The EEG can be used in the determination of a smile (McFarland, Sarnacki and Wolpaw, 2010; Gale and Edwards, 1986). The smile is regarded as a process that begins in the brain. A smile, like many other facial expressions, is known to depend on a distinct neural circuit. Therefore, the Electroencephalographic can be used in the study of facial expressions such as the smile (Ohme, Reykowska, Wiener and Choromanska, 2009).
The Galvanic Skin Response (GSR)
The Galvanic Skin Response (GSR) can be described as a technique used in measuring skin conductivity. This instrument is noted to be highly reactive to emotions among some individuals. The GSR has been used electrical conductance levels on the human body. This is an aspect that varies depending on the moisture level on the skin. Notably, the control of the sweat glands is initiated by a certain nervous system within the human body. This is the sympathetic nervous system. Therefore, the conductivity of the skin can be used to determine any psychological and physiological processes within the body (Conesa, 1995).
Various studies have been conducted regarding the electro-dermal activity. A significant number of these studies have focused on the impulsive variations or responses to stimuli (Ohme, Reykowska, Wiener and Choromanska, 2009). In one of the studies, Frodi and Lamb (1980) set out to establish how a child abuser responded to infant smiles and cries. In this study, it was established that when the child cried, there was an increased skin conductance among the subjects of the study. On the other hand, when the child smiled, there were variations on how the subjects responded. The child abusers reacted in the same way as to when the child cried. On the contrary, the control group had no changes in their physiological processes, and in some instances, a reduction in the physiological activity was noted. These results were determined using the Galvanic Skin Response (GSR) (Frodi and Lamb, 1980).
The Galvanic Skin Response (GSR) is used in measuring the activity of the sweat glands. Also, it can be used in measuring the variations within the sympathetic nervous system. There is an association between the sympathetic nervous system and emotive stimulation. Nonetheless, it is not easy to recognize the special emotion caused. This is because there are numerous emotions that can elicit same GSR responses. For instance, fear, anger, and sexual feelings are known to exhibit similar the galvanic skin responses. However, since smiling is one of the emotional responses, GSR can be used to detect this feeling in some instances (Gomez, Zimmerman, Guttormsen and Danuser, 2009).
A system that can recognize evoked smiles
From the discussion, it has been established that the Electroencephalographic (EEG), Facial Electromyography (EMG) and Galvanic Skin Response (GSR) are some of the instruments used to capture facial emotions. These three techniques are critical in measuring emotions. This is with special regard to the smile. In this case, the Electroencephalographic (EEG) is the best instrument that can capture a smile in an individual. This is because of the ability of the instrument to capture the muscle movement that elicits a smile. Also, Facial Electromyography (EMG) is essential in capturing a smile among individuals given that it can detect the electrical activity in the brain associated with smile. The Galvanic Skin Response (GSR) is the least effective method of detecting and measuring a smile. This is because the responses captured by this instrument cannot be attributed to a certain stimulus. Therefore, the reaction of the sweat gland due to a smile can be shared among other stimuli. Thus, it can be proposed that the Electroencephalographic (EEG) and Facial Electromyography (EMG) should be used in recognition of evoked smiles even from paralyzed patients and other patients that do not have any facial movements.
Conclusion
Facial expressions form part of the emotional responses. It can be noted that individuals can pose a certain emotive response in a voluntary manner. This means that such individuals exhibit emotional expression without having been enticed. In this case, it can be appreciated that certain emotional responses cannot be determined expressly. In this respect, various techniques have been developed to ensure that all emotions are captured. However, the Electroencephalographic (EEG) and Facial Electromyography (EMG) can be argued to be among the best instruments for measuring a smile.
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