A 2.2-<inline-formula> <tex-math notation="LaTeX">$\mu$ </tex-math></inline-formula>W Cognitive Always-On Wake-Up Circuit for Event-Driven Duty-Cycling of IoT Sensor Nodes

We report an always-on event-driven asynchronous wake-up circuit with trainable pattern recognition capabilities to duty-cycle power-constrained Internet-of-Things (IoT) sensor nodes. The wake-up circuit is based on a level-crossing analog-to-digital converter (LC-ADC) employed as a feature-extraction block with automatic activity-sampling rate scaling behavior. A novel asynchronous digital logic classifier for sequential pattern recognition is presented. It is driven by the LC-ADC activity and trained to minimize classification errors due to falsely detected events. As proof-of-concept, a prototype of the wake-up circuit is fabricated in 130nm CMOS technology within 0.054 mm² of active area, covering up to 2.6 kHz of input signal bandwidth. The prototype has been first validated by interfacing it with a commercial accelerometer to classify hand gestures in real-time, reaching 81% of accuracy with only 2.2 <inline-formula> <tex-math notation="LaTeX">$\mu \text{W}$ </tex-math></inline-formula> at 1-V supply. To highlight the flexibility of the design, a second application, detecting pathologic electrocardiogram beats is also discussed.