Biodétection Clinique Continue avec Silicium Très Basse Consommation et Circuits Flexibles

WearableIoMT assure un suivi électrophysiologique de qualité clinique hors de l'hôpital, combinant rejet des artéfacts de mouvement et TinyML sur puce pour détecter les arythmies paroxystiques en temps réel.

WearableIoMT Body Area Network Topology

Sub-Microwatt Sensor Fusion and Cryptographic Uplink

Central System: BAN Sensor Hub - Ultra-Low Power SoC

Clinical IoMT Nodes

AFE Photoplethysmography
Multi-Lead Bio-Potential
BLE 5.3 Coded PHY
Secure Element PUF
Local Edge TinyML

Architectural Layers & Regulatory Standards

Analog Front-End (AFE) Sensing (24-bit Delta-Sigma ADC / CMRR > 115 dB): High-impedance bio-potential instrumentation amplifiers with active electrode motion cancelation.
Micro-Power Signal Preprocessing (ARM Cortex-M33 / CMSIS-DSP Vector Kernels): Wavelet filtering and R-peak detection executed on dedicated ultra-low-power DSP co-processors.
Body Area Network Transport (IEEE 802.15.6 / Bluetooth 5.3 Coded PHY): Short-range wireless propagation conforming to medical Body Area Network standards.
Encrypted Telemetry Dispatch (NIST SP 800-38C AES-CCM / ECDH P-256): AES-CCM authenticated encryption pairing sensor patches with patient smartphone gateways.

Key Metrics: < 15 µW (Active Sensor Power Consumption) | 250 Hz (Multi-Lead ECG Sampling Frequency) | AES-CCM (Over-the-Air Encryption Standard) | 14 Days (Continuous Patch Battery Autonomy)

Électrophysiologie clinique sur bioadhésifs flexibles

Hospital Holter monitors are bulky and discourage patient compliance. WearableIoMT introduces miniature biocompatible adhesive patches that monitor multi-channel ECG, respiration, temperature, and pulse oximetry for up to two weeks on a single zinc-air battery.

Core Engineering Areas

Sub-Microwatt Analog Front-End Design — Minimizing thermal noise and baseline wander in continuous clinical ambulatory ECG recording.
BLE Coded PHY for Body Area Networks — Overcoming human body tissue attenuation and multipath fading with LE Coded PHY.
TinyML On-Device Arrhythmia Classification — Running convolutional inference directly on wearable microcontrollers to trigger clinical alarms.

Technical Articles

Related Cluster Architecture Specifications

HealthVigilance — Zero-Trust IoMT Architecture, SaMD Risk Engineering & Autonomous Clinical Post-Market Vigilance
AgenticSaMD — Autonomous Agentic Software as a Medical Device, Multi-Agent Clinical Decision Support & FDA GMLP Guardrails
AITelemonitoring — Autonomous AI Telemonitoring, Virtual Nursing Assistants & Predictive Clinical Deterioration Scoring
BCI2IoMT — Brain-Computer Interface IoMT Gateways, Neural Decoding & Electrophysiological Streaming