Volunteers' concerns about facial neuromuscular electrical stimulation

Computer-controlled electrical stimulation of facial muscles by facial neuromuscular electrical stimulation (fNMES): Hardware and software solutions

BACKGROUND

Computer controlled electrical stimulation of facial muscles is a promising method to study facial feedback effects, though little guidance is available for new adopters.

NEW METHOD

Facial Neuromuscular Electrical Stimulation (fNMES) offers a spatially and temporally precise means of manipulating facial muscles during experiments, and can be combined with EEG to study the neurological basis of facial feedback effects. Precise delivery of stimulation requires hardware and software solutions to integrate stimulators and a stimulus-presenting computer. We provide open-source hardware schematics and relevant computer code in order to achieve this integration, so as to facilitate the use of fNMES in the laboratory.

RESULTS

Hardware schematics are provided for the building of a bespoke control module, which allows researchers to finely control stimulator output whilst participants complete computer tasks. In addition, we published code that new adopters of NMES can use within their experiments to control the module and send event triggers to another computer. These hard- and software solutions were successfully used to investigate the effects of facial muscle activation on felt and perceived emotion. We summarise these findings and discuss the integration of fNMES with EEG and peripheral physiological measures.

COMPARISON WITH EXISTING METHODS

Our inexpensive hardware solution allows fNMES parameters to be computer controlled, and thus allows to stimulate facial muscles with high precision. This opens up new possibilities to investigate, for example, facial feedback effects.

CONCLUSIONS

We provide tools and guidance to build a control module in order to precisely deliver electrical stimulation to facial muscles using a stimulus computer (while recording EEG or other peripheral physiology).

Application of facial neuromuscular electrical stimulation (fNMES) in psychophysiological research: Practical recommendations based on a systematic review of the literature

Facial neuromuscular electrical stimulation (fNMES), which allows for the non-invasive and physiologically sound activation of facial muscles, has great potential for investigating fundamental questions in psychology and neuroscience, such as the role of proprioceptive facial feedback in emotion induction and emotion recognition, and may serve for clinical applications, such as alleviating symptoms of depression. However, despite illustrious origins in the 19th-century work of Duchenne de Boulogne, the practical application of fNMES remains largely unknown to today's researchers in psychology. In addition, published studies vary dramatically in the stimulation parameters used, such as stimulation frequency, amplitude, duration, and electrode size, and in the way they reported them. Because fNMES parameters impact the comfort and safety of volunteers, as well as its physiological (and psychological) effects, it is of paramount importance to establish recommendations of good practice and to ensure studies can be better compared and integrated. Here, we provide an introduction to fNMES, systematically review the existing literature focusing on the stimulation parameters used, and offer recommendations on how to safely and reliably deliver fNMES and on how to report the fNMES parameters to allow better cross-study comparison. In addition, we provide a free webpage, to easily visualise fNMES parameters and verify their safety based on current density. As an example of a potential application, we focus on the use of fNMES for the investigation of the facial feedback hypothesis.

Zygomaticus activation through facial neuromuscular electrical stimulation (fNMES) induces happiness perception in ambiguous facial expressions and affects neural correlates of face processing

The role of facial feedback in facial emotion recognition remains controversial, partly due to limitations of the existing methods to manipulate the activation of facial muscles, such as voluntary posing of facial expressions or holding a pen in the mouth. These procedures are indeed limited in their control over which muscles are (de)activated when and to what degree. To overcome these limitations and investigate in a more controlled way if facial emotion recognition is modulated by one's facial muscle activity, we used computer-controlled facial neuromuscular electrical stimulation (fNMES). In a pre-registered EEG experiment, ambiguous facial expressions were categorised as happy or sad by 47 participants. In half of the trials, weak smiling was induced through fNMES delivered to the bilateral Zygomaticus Major muscle for 500 ms. The likelihood of categorising ambiguous facial expressions as happy was significantly increased with fNMES, as shown with frequentist and Bayesian linear mixed models. Further, fNMES resulted in a reduction of P1, N170 and LPP amplitudes. These findings suggest that fNMES-induced facial feedback can bias facial emotion recognition and modulate the neural correlates of face processing. We conclude that fNMES has potential as a tool for studying the effects of facial feedback.

Measurement of the N170 during facial neuromuscular electrical stimulation (fNMES)

BACKGROUND

Studies on facial feedback effects typically employ props or posed facial expressions, which often lack temporal precision and muscle specificity.

NEW METHOD

Facial Neuromuscular Electrical Stimulation (fNMES) allows for a controlled influence of contractions of facial muscles, and may be used to advance our understanding of facial feedback effects, especially when combined with Electroencephalography (EEG). However, electrical stimulation introduces significant interference that can mask underlying brain dynamics. Whether established signal processing methods can allow for a reduction of said interference whilst retaining effects of interest, remains unexplored.

RESULTS

We addressed these questions focusing on the classic N170 visual evoked potential, a face-sensitive brain component: 20 participants viewed images of houses, and of sad, happy, and neutral faces. On half of the trials, fNMES was delivered to bilateral lower-face muscles during the presentation of visual stimuli. A larger N170 amplitude was found for faces relative to houses. Interestingly, this was the case both without and during fNMES, regardless of whether the fNMES artefact was removed or not. Moreover, sad facial expressions elicited a larger N170 amplitude relative to neutral facial expressions, both with and without fNMES.

COMPARISON WITH EXISTING METHODS

fNMES offers a more precise way of manipulating proprioceptive feedback from facial muscles, which affords greater diversity in experimental design for studies on facial feedback effects.

CONCLUSIONS

We show that the combining of fNMES and EEG can be achieved and may serve as a powerful means of exploring the impact of controlled proprioceptive inputs on various types of cognitive processing.