Patient Mood and Discomfort
HDP1 · Recognizes facial expressions — happiness, sadness, anger, surprise and more
About this solution
AI model trained to recognize facial expressions associated with emotions — happiness, sadness, fear, disgust, surprise, anger, contempt and neutral. It measures in real time how customers, students and audiences react to products, service, classes, storefronts and presentations.
- 1The YuNet detector locates the faces in each frame.
- 2The HSEmotion model (trained on the AffectNet dataset) classifies 8 emotions with probabilities.
- 3Readings are smoothed over time per person to avoid fluctuations.
- 4A satisfaction (valence) index summarizes the audience's mood minute by minute.
Benefits
- Objective emotional feedback, without questionnaires.
- Identifies the moments and products that generate the most delight (or frustration).
- Complements NPS and surveys with continuous, anonymous data.
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