面向床旁 SaMD 与重症生命体征实时推理的确定性边缘计算系统

SaMDCompute 直接在床旁就地即时检验 (Point of Care) 边缘终端执行高度复杂的生理病理 AI 推理计算,彻底消除对公有云网络的依赖与网络抖动延迟,为恶性心律失常与急性呼吸衰竭等生死抉择争分夺秒。

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)

在分秒决定生死之处提供可预测的低延迟计算

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