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Research

Our research teams investigate the safety, inner workings, and advances in health monitoring—so that new technologies have a positive impact as they become increasingly capable.

Research teams:
Interpretability Alignment Health Monitoring Clinical Research

Interpretability

Understanding how AI models and biosensing systems work internally, as a foundation for safety and trustworthy outcomes.

Alignment

Ensuring that AI systems remain helpful, honest, and aligned with human values as they become more capable.

Health Monitoring

Developing and validating continuous biosensing technologies for real-time health tracking and disease management.

Clinical Research

Conducting rigorous, peer-reviewed research into mast cell activation and neuroinflammation with clinical partners.

MastCell Tracker Research
Health Monitoring · August 26, 2026

Continuous mast cell activation signatures during heat exposure

A continuous-biosensing study of how heat exposure drives mast cell activation in MCAS, revealing distinct physiological signatures that precede reported symptoms.
Interpretability · August 21, 2026

Explainable models for flare prediction in mast cell activation syndrome

Interpretable machine-learning models forecast MCAS flares from continuous biosignals while making their reasoning transparent to patients and clinicians.
Clinical · August 15, 2026

Validating wearable biosignals against clinical reference measures

A validation study comparing continuous MCT-1 biosignals against established clinical reference measures across activity, sleep, and flare conditions.
Safety · August 11, 2026

On-device processing for privacy-preserving biosignal analysis

A privacy-first architecture that performs sensitive biosignal analysis directly on the device, minimizing exposure of personal health data.
Health Monitoring · August 6, 2026

Sensor fusion for multi-parametric mast cell monitoring

Combining multiple biosignal streams through sensor fusion to detect mast cell activation more reliably than any single measurement alone.
Clinical · August 1, 2026

Longitudinal biomarker and symptom correlation in MCAS cohorts

A longitudinal analysis linking continuously measured biomarkers with patient-reported symptoms across MCAS cohorts over multiple months.

Publications

Date Category Title
Jul 15, 2026 Machine Learning From signal to insight: the MCT - 1 analytics pipeline
Jul 8, 2026 Methods Personalizing baselines: individual variability in activation
Jun 27, 2026 Clinical Research Correlating inflammatory markers with patient-reported symptoms
Jun 20, 2026 Privacy & Ethics Privacy-preserving models for continuous health monitoring
Jun 13, 2026 Biomarkers Skin temperature dynamics during flares
Jun 6, 2026 Health Monitoring Heart rate variability as a marker of mast cell activation
May 30, 2026 Machine Learning Machine learning for trigger identification in mast cell disorders
May 23, 2026 Biomarkers Signatures of histamine release in continuous physiological data
May 16, 2026 Methods Continuous vs. episodic measurement in MCAS
May 9, 2026 Health Monitoring Detecting mast cell activation from wearable biosignals
May 8, 2026 Health Monitoring Real-time biomarker detection in mast cell activation syndrome
May 7, 2026 Interpretability Understanding neural patterns in health prediction
May 2, 2026 Interpretability Machine learning model interpretability in biosensing data analysis
Apr 30, 2026 Clinical Neuroinflammation markers in related conditions
Apr 25, 2026 Health Monitoring Patient empowerment through real-time health data access
Apr 22, 2026 Safety Privacy-first architecture for wearable health data
Apr 18, 2026 Clinical Multi-omics integration for personalized medicine
Apr 15, 2026 Alignment Ethical frameworks for AI-assisted medical diagnosis
Apr 10, 2026 Policy Regulatory considerations for AI medical devices
Apr 8, 2026 Health Monitoring Continuous biosensing validation in patient cohorts
Apr 3, 2026 Health Monitoring Longitudinal biomarker tracking in chronic conditions
Mar 27, 2026 Safety Federated learning for distributed health data analysis
Mar 20, 2026 Health Monitoring Wearable sensor calibration and validation methods
Mar 13, 2026 Interpretability Deep learning for time series anomaly detection
Mar 6, 2026 Clinical Cross-platform data integration and harmonization
Feb 27, 2026 Health Monitoring Behavioral interventions driven by biosensing insights
Feb 20, 2026 Policy Real-world evidence generation from continuous monitoring
Feb 13, 2026 Clinical Patient stratification for precision treatment selection
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