Optimal processing of surface facial EMG to identify emotional expressions: A data-driven approach.

Surface facial electromyography (EMG) is commonly used to detect emotions from subtle facial expressions. Although there are established procedures for collecting EMG data and some aspects of their processing, there is little agreement among researchers about the optimal way to process the EMG signal, so that the study-unrelated variability (noise) is removed, and the emotion-related variability is best detected. The aim of the current paper was to establish an optimal processing pipeline for EMG data for identifying emotional expressions in facial muscles. We identified the most common processing steps from existing literature and created 72 processing pipelines that represented all the different processing choices. We applied these pipelines to a previously published dataset from a facial mimicry experiment, where 100 adult participants observed happy and sad facial expressions, whilst the activity of their facial muscles, zygomaticus major and corrugator supercilii, was recorded with EMG. We used a resampling approach and subsets of the original data to investigate the effect and robustness of different processing choices on the performance of a logistic regression model that predicted the mimicked emotion (happy/sad) from the EMG signal. In addition, we used a random forest model to identify the most important processing steps for the sensitivity of the logistic regression model. Three processing steps were found to be most impactful: baseline correction, standardisation within muscles, and standardisation within subjects. The chosen feature of interest and the signal averaging had little influence on the sensitivity to the effect. We recommend an optimal processing pipeline, share our code and data, and provide a step-by-step walkthrough for researchers.

Measuring mimicry: general corticospinal facilitation during observation of naturalistic behaviour.

Mimicry of others' postures and behaviours forms an implicit yet indispensable component of social interactions. However, whereas numerous behavioural studies have investigated the occurrence of mimicry and its social sensitivity, the underlying neurocognitive mechanisms remain elusive. In this study, single-pulse transcranial magnetic stimulation was used to measure corticospinal facilitation during a naturalistic behaviour observation task adapted from the behavioural mimicry literature. Motor evoked potentials (MEPs) in participants' right hands were measured as they observed stimulus videos of a confederate describing photographs. MEPs were recorded while confederates were and were not carrying out hand and leg behaviours that also differed in spatial extent (i.e. large behaviours: face rubbing and leg crossing; small behaviours: finger tapping and foot bouncing). Importantly, the cover task instructions did not refer to the behaviours but instead required participants to focus on the confederates' photograph descriptions in order to later perform a recognition test. A general arousal effect was found, with higher MEPs during stimulus video observation than during a fixation-cross baseline, regardless of whether or not the confederate was carrying out a behaviour at the time of the pulse. When controlling for this general arousal effect, results showed that MEPs during observation of the larger two behaviours were significantly higher than the smaller two behaviours, irrespective of effector. Thus, using a controlled yet naturalistic paradigm, this study suggests that general sensorimotor arousal during social interactions could play a role in implicit behavioural mimicry.