ベッドサイドSaMD&重症生体信号推論のための決定論的エッジコンピューティング

SaMDComputeは、ベッドサイドや診察現場で複雑な生体生理学的推論を直接実行し、重篤な不整脈や呼吸不全の判断においてクラウド依存とレイテンシの揺らぎを完全に排除します。

SaMDCompute Bedside Edge Architecture

Deterministic Processing Enclave and Biosignal Accelerator

Central System: Clinical Edge Inference Engine - Deterministic RTOS Core

Clinical IoMT Nodes

  • Quantized Neural Engine
  • RTOS Memory Enclave
  • Bedside Telemetry Ingress
  • Hazard Supervisor
  • EHR Export Bridge

Architectural Layers & Regulatory Standards

  • Deterministic Microkernel Layer (seL4 Microkernel / FreeRTOS MPU Medical Profile): Formally verified microkernel enforcing priority preemption and bounded interrupt latency.
  • Memory Protection & Isolation Enclave (ARM TrustZone-M / RISC-V PMP (Physical Memory Protection)): Hardware-enforced MPU boundaries preventing non-critical logging tasks from corrupting vital algorithms.
  • Hardware-Accelerated Neural Inference (CMSIS-NN Vector Kernels / INT8 Quantized Tensor Arrays): Low-power vector NPU executing quantized 1D/2D CNNs for real-time electrophysiological wave analysis.
  • Clinical Decision & Dispatch Interface (IEC 60601-1-8 Audio/Visual Hazard Controller): Synchronous dispatch of high-priority alarms to bedside displays and central nurse consoles.

Key Metrics: < 100 µs (Worst-Case Interrupt Latency) | 100% (Formal Memory Safety Guarantee) | INT8 (Quantized Waveform Inference) | Class C (IEC 62304 Software Architecture)

秒が命を救う場所での予測可能な低遅延コンピューティング

Cloud-based medical algorithms are vulnerable to internet outages and packet jitter. SaMDCompute standardizes edge acceleration platforms that guarantee worst-case execution times for real-time hemodynamic alerting and automated drug delivery.

Core Engineering Areas

Technical Articles

Related Cluster Architecture Specifications