Medical-Grade AI Algorithms
Clinically Validated Intelligent Core
Medical-Grade AI Algorithms
From Data to Insight — Turning Monitoring into Visible Health Trends
tBPC inside™ Medical-Grade AI Algorithms serve as the intelligence that transforms optical signals into clinical insight. Through deep learning and large-scale clinical data training, the AI models automatically recognise physiological changes, remove noise, correct deviations and convert raw optical signals into reliable health indicators for medical decision-making.
This technology enables wearable and long-term monitoring devices to move beyond simple “data recording”, supporting clinicians in interpretation and assisting care teams in tracking patient conditions. It extends monitoring from real-time detection to prediction and prevention, providing the foundation for continuous health management.
Why Choose tBPC inside™ Medical-Grade AI Algorithms
High-Quality Data Acquisition
Algorithm accuracy depends on diverse and high-quality physiological data. Through large-scale clinical trials across different populations, environments and conditions, tBPC inside™ has established a comprehensive and structured database that ensures robust model training.
Clinically Validated to Medical Standards
Output results must comply with regulatory standards and demonstrate interpretability and credibility.
tBPC inside™ is validated against ISO, FDA, AASM (sleep medicine) and American Heart Association guidelines, ensuring outputs are trusted and accepted by healthcare professionals.
Big-Data Iterative Optimisation
The algorithms possess self-optimising capabilities, enhancing performance through continuous data iteration and model adjustment. They automate data processing, rapid classification and anomaly exclusion — consistently increasing their clinical value.
Explainable and Trustworthy
Medical-grade algorithms must offer transparency in logic and output. tBPC inside™ adheres to professional standards of interpretability, ensuring clinicians and patients can understand and trust the resulting insights.
What Can tBPC inside™ AI Calculate?
Combining optical modelling, physiological signal analysis and clinical validation, tBPC inside™ can output a wide range of health parameters tailored to various applications.
Vital Signs
Advanced
Vital Signs
SpO₂（Oxygen Saturation）
Automatically detects desaturation events and calculates ODI (Oxygen Desaturation Index), supporting sleep and respiratory monitoring.
PR（Pulse Rate）
Calculates heart rate and variability in real time, reflecting cardiac activity and moment-to-moment physiological state.
RR（Respiratory Rate）
Identifies breathing-pattern changes from PPG waveforms, enabling respiratory-stability assessment.
SkT（Skin Temperature）
Continuously tracks skin temperature, supporting infection monitoring and metabolic evaluation.
Advanced
HRV
(Heart Rate Variability Analysi)
(Heart Rate Variability Analysi)
Automatically extracts PPI waveforms and calculates indicators such as SDNN, RMSSD and LF/HF to assess stress, recovery and autonomic nervous activity.
OSA
(Obstructive Sleep Apnoea Analysis)
(Obstructive Sleep Apnoea Analysis)
Automatically identifies desaturation events and breathing pauses based on SpO₂ and respiratory-rate variations, generating AHI/ODI reports.
Sleep Quality Assessment
Integrates pulse, activity level and respiratory trends to analyse sleep stages, deep-sleep proportion and sleep efficiency.
Extended Applications
Long-Term Care Monitoring
Analyses multi-day trends to identify fatigue, cardiopulmonary load or metabolic changes.
Clinical Decision Support
Integrates AI-derived health indicators into clinical systems to support diagnosis and treatment tracking.
Five Foundations of Trustworthy Clinical Insight
Making Health Signals More Accurate
Algorithm performance relies on effective feature extraction and model development. Through feature engineering and iterative training, tBPC inside™ isolates the most representative physiological features from complex datasets. This ensures outputs are more accurate, clinically meaningful and less susceptible to noise-induced misinterpretation.
Making Data Flow More Efficient
Healthcare data requires efficient processing. tBPC inside™ supports automated data ingestion, labelling and de-identification, reducing manual workload and minimising errors. Compliance with privacy regulations ensures data security, while streamlined model-training and validation processes speed up clinical deployment.
Ensuring Cleaner Data
Biophotonic signals often contain noise and anomalies. Intelligent auto-debugging mechanisms rapidly compare, classify and remove abnormal data. Through large-scale data comparison and self-correction, tBPC inside™ maintains data purity, providing a stable foundation for analysis and clinical use.
Making Judgements More Trustworthy
In medical applications, algorithms must be traceable. tBPC inside™ operates on a transparent logical framework, clearly explaining analytical basis and avoiding “black-box” conclusions. This builds confidence among clinicians and increases acceptance among patients and regulatory bodies.
Advancing Care One Step Ahead
The algorithms support not only real-time interpretation but also disease-risk prediction and trend analysis. By combining clinical prediction models with validation tools, tBPC inside™ enables earlier intervention — realising the value of shifting from treatment to prevention, across diagnosis, monitoring and risk management.
Patents and Technical Validation
tBPC inside™ Medical-Grade AI Algorithms have been granted multiple patents and have undergone clinical validation in compliance with international medical standards.
These achievements demonstrate strong R&D capability and provide partners with regulatory assurance and market credibility — ensuring safe deployment in healthcare and long-term care environments.
