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The Science Behind Emteq Labs’ OCOsense™ Smart Glasses

How can we measure emotion in real time—without a lab or intrusive sensors? Emteq Labs’ OCOsense™ smart glasses offer a powerful solution: glasses equipped with optical sensors that detect subtle facial muscle movements, completely without skin contact.

Using a patented sensing method called Optomyography (OMG), OCOsense™ captures natural expressions like smiles and frowns in everyday environments. This means researchers can study emotional responses more naturally, accurately, and scalably than ever before.

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OCOsense™ Technology

At the core of OCOsense™ are infrared-based optical sensors that track tiny skin movements caused by underlying muscle activity. Operating at 50 Hz, they record 3D movement (X, Y, Z) with precision-no cameras or electrodes required.

Unlike traditional EMG systems that rely on sticky electrodes, OMG sensors are contact-free, functioning effectively from 4 to 30 mm away [1]. That means greater comfort, hygiene, and long-term wearability for participants in natural settings.

And with Bluetooth Low Energy (BLE) and onboard buffering, OCOsense™ is truly wireless [1].

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Sensor Placement & Muscle Targeting

The glasses are embedded with OCO™ sensors, each strategically positioned to capture key muscle groups involved in facial expressions. Here's how they’re laid out:

● Forehead (left & right): Over the frontalis muscle, detecting eyebrow raises

● Cheeks (left & right): Over the zygomaticus major, capturing smiles

● Glabella (center brow): Targets the corrugator/procerus to distinguish between frowns and brow raises

● Temples (left & right): Serve as reference points to help eliminate head motion artifacts

A 9-axis IMU and altimeter sit in the right temple, enabling the glasses to distinguish facial expressions from general head movement, and also to estimate head posture and orientation [1, 4].

Table 1. Comparative Analysis of Biometric Sensing Technologies & Performance Benchmark

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Figure 1. OCOSense™  glasses and corresponding sensor placement

Expression Recognition — Backed by Science

Sensor placement has been rigorously validated [3]:

● Cheek sensors picked up cheek raises, smiles and eye-squeezes

● Brow sensors tracked frowns and eyebrow raises

● Temple sensors and the IMU filtered out head motion

● A trained machine learning model classified expressions with 93% accuracy (F1-score: 0.90) [3].

This means OCOsense™ doesn’t just track movement—it understands what those movements mean.

Illustration 1. The relationship between the facial muscles and that indicate positive (zygomaticus major) and negative (corrugator supercilii) valence.

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Real-World Applications

Mental Health & Rehab

Track subtle facial changes in people recovering from stroke, facial palsy, or experiencing depression—outside the clinic, passively [2].

Behavioral Science & Neuroscience

Collect high-quality expression data in everyday environments. Study natural emotional reactions, not just lab-based responses.

Emotion-Aware Tech & XR

Add emotional intelligence to training, virtual reality, and assistive technologies—no cameras required.

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Conclusion

Emteq Labs’ OCOsense™ smart glasses are reshaping how we measure facial expressions and emotion—non-invasively, accurately, and in the real world. With validated sensing technology and smart design, it’s a platform ready for clinical, research, and technology innovation.

Whether you're studying behavior, building emotion-aware tools, or supporting recovery—OCOsense™ helps you go deeper into what the face reveals.

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References

[1] Archer, J. A., Mavridou, I., Stankoski, S., Broulidakis, M. J., Cleal, A., Walas, P., Fatoorechi, M., Gjoreski, H., & Nduka, C. (2023). OCOsense™ smart glasses for analyzing facial expressions using optomyographic sensors. IEEE Pervasive Computing, 22(3), 53–61. https://doi.org/10.1109/MPRV.2023.3276471

[2] Broulidakis, M. J., Kiprijanovska, I., Stankoski, S., Archer, J. A., Cleal, A., Fatoorechi, M., Walas, P., Gjoreski, H., & Nduka, C. (2023). Optomyography-based sensing of facial expression derived arousal and valence in adults with depression. Frontiers in Psychiatry, 14, 1232433. https://doi.org/10.3389/fpsyt.2023.1232433

[3] Kiprijanovska, I., Stankoski, S., Broulidakis, M. J., Archer, J. A., Fatoorechi, M., Gjoreski, M., Nduka, C., & Gjoreski, H. (2023). Towards smart glasses for facial expression recognition using OMG and machine learning. Scientific Reports, 13, Article 43135. https://doi.org/10.1038/s41598-023-43135-5

[4] Stankoski, S., Sazdov, B., Broulidakis, J., Kiprijanovska, I., Sofronievski, B., Cox, S., Gjoreski, M., Archer, J., Nduka, C., & Gjoreski, H. (2023). Recognizing activities of daily living using multi-sensor smart glasses. In 2023 46th International Convention on Information, Communication and Electronic Technology (MIPRO) (pp. 360–365). IEEE. https://doi.org/10.23919/mipro57284.2023.10159701

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