Privacy-Preserving Emotion Recognition
On-device biosignal analysis using wrist-based PPG sensors
Synheart Emotion
A privacy-preserving on-device emotion recognition system using wrist-based PPG biosignals and machine learning models optimized with ONNX.
About
Synheart Emotion is a privacy-preserving on-device emotion recognition system that utilizes wrist-based photoplethysmography (PPG) biosignals. The system processes Heart Rate Variability (HRV) features to classify emotions while ensuring user data remains on the device, addressing critical privacy concerns in emotion detection applications.
Human–computer interaction increasingly demands systems that recognize not only explicit user inputs but also implicit emotional states. While substantial progress has been made in affective computing, most emotion recognition systems rely on cloud- based inference, introducing privacy vulnerabilities and latency constraints unsuitable for real-time applications.
"By optimizing machine learning models with ONNX and deploying them on-device, we ensure that sensitive biosignal data never leaves the user's wearable device, providing a privacy-first approach to emotion recognition that achieves state-of-the-art performance."
What We Built
The Synheart Emotion system addresses fundamental challenges in emotion recognition from biosignals:
- Privacy concerns with cloud-based emotion recognition systems that transmit sensitive biosignal data.
- Limited computational resources on wearable devices requiring efficient model optimization.
- Need for real-time emotion classification without network latency or connectivity requirements.
- Balancing model performance with memory footprint and inference speed on edge devices.
Our Vision
We envision a future where emotion-aware wearable technology respects user privacy while delivering accurate insights:
- Users can benefit from emotion recognition without compromising their sensitive biosignal data.
- Wearable devices become more intelligent and responsive to emotional states in real-time.
- Healthcare providers gain valuable tools for mental health monitoring with patient consent.
- Developers can build privacy-preserving emotion-aware applications using standardized on-device models.
Who Can Use Synheart Emotion?
- Healthcare Professionals → Monitor patients' emotional states for mental health assessment and treatment.
- Researchers → Study emotion patterns and develop new affective computing applications.
- Wearable Manufacturers → Integrate privacy-preserving emotion recognition into their devices.
- App Developers → Build emotion-aware applications that respect user privacy and work offline.