Facial expressions are a window into human emotions, offering valuable insights across psychology, neurology, and Human-Machine Interface (HMI) applications. From decoding micro-expressions for lie detection to monitoring emotional responses to stimuli like ads or music, facial expression analysis is a powerful tool. Facial expression analysis also plays a critical role in many clinical settings, aiding in the management of neurologic conditions like Parkinson’s disease, guiding Botox injections, and supporting rehabilitation after facial nerve palsy. In psychiatry, it provides objective measures for tracking affective states, while in HMI, it enhances neuroadaptive systems by gauging operator attention, satisfaction, or frustration. AI-driven emotional support systems can leverage facial expression analysis as a real-time feedback mechanism.
Traditional video-based facial expression analysis requires subjects to remain stationary in front of a camera and is highly sensitive to lighting conditions, making it impractical for use in dynamic environments or low-light settings. Existing electromyography (EMG) solutions rely on wired setups and bulky gel electrodes that hinder natural facial movements and limit mobility.
Enter X-trodes, a game-changer in facial EMG (fEMG) technology. X-trodes introduces thin, soft, flexible patches that collect fEMG signals non-invasively, enabling natural facial expressions and unrestricted movement. These patches are designed for real-world use, resistant to humidity, dust, and sweat, and seamlessly integrating with hats, glasses, or professional gear like helmets. With a sampling rate of up to 4KHz, X-trodes can capture even the briefest micro-expressions. The wireless design and advanced filtering make it the world’s first solution for fEMG collection on the move. In their latest work, Facial muscle mapping and expression prediction using a conformal surface-electromyography platform, Hila Man and colleagues demonstrate for the first time successful reconstruction of free facial expression from fEMG recordings and provide an anatomic framework for facial muscle activity analysis. A prior publication by Paul Funk and colleagues, Wireless high-resolution surface facial electromyography mask for discrimination of standardized facial expressions in healthy adults, demonstrated successful reconstruction of standardized expressions.
The versatility of X-trodes extends beyond fEMG. These patches can simultaneously collect EEG, EOG, ECG, and hand EMG, providing a comprehensive view of emotional and physiological states through brain activity, eye movements, blink rate, heart rate variability, and gestures. All modalities are FDA approved. This multi-modal capability makes X-trodes ideal for mental state studies.
X-trodes also supports simultaneous synchronized recordings of multiple subjects, useful in social interaction studies.
X-trodes’ wireless, high-resolution, and user-friendly design empowers researchers, clinicians, and engineers to unlock new possibilities in emotional and neurological analysis.
Here are some examples of publications utilizing this technology:
- Man, Hila, et al. “Facial muscle mapping and expression prediction using a conformal surface-electromyography platform.” npj Flexible Electronics 9.1 (2025): 71.
- Ibrahim, Rawan, et al. “Dry-printed electrodes for transcutaneous electrical stimulation of inervated muscles: Towards wearable and closed-loop stimulation.” (2025). (pre-print)
- Funk, Paul F., et al. “Wireless high-resolution surface facial electromyography mask for discrimination of standardized facial expressions in healthy adults.” Scientific Reports 14.1 (2024): 19317.
- Ibrahim, Rawan, et al. “Facial electromyography during exercise using soft electrode array: A feasibility study.” Plos one 19.2 (2024): e0298304.
- Levit, Bara, Paul F. Funk, and Yael Hanein. “Soft electrodes for simultaneous bio-potential and bio-impedance study of the face.” Biomedical Physics & Engineering Express 10.2 (2024): 025036.
- Levit, Bara, and Yael Hanein. “High-resolution bio-potential and bio-impedance investigation of the face.” (2023).
- Gat, Liraz, et al. “Similarities and disparities between visual analysis and high-resolution electromyography of facial expressions.” PLoS One 17.2 (2022): e0262286.
- Shuster, Anastasia, et al. “Lie to my face: An electromyography approach to the study of deceptive behavior.” Brain and Behavior 11.12 (2021): e2386.
- Inzelberg, Lilah, et al. “Multi-channel electromyography-based mapping of spontaneous smiles.” Journal of Neural Engineering 17.2 (2020): 026025.
- Inzelberg, Lilah, et al. “Printed facial skin electrodes as sensors of emotional affect.” Flexible and Printed Electronics 3.4 (2018): 045001.
- Inzelberg, Lilah, et al. “A wearable high-resolution facial electromyography for long term recordings in freely behaving humans.” Scientific reports 8.1 (2018): 2058.
- Inzelberg, Lilah, et al. “Wireless electronic-tattoo for long-term high fidelity facial muscle recordings.” Micro-and Nanotechnology Sensors, Systems, and Applications IX. Vol. 10194. SPIE, 2017.