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 analogto-digital converter (LC-ADC) employed as 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 130 nm CMOS technology within 0.054 mm 2 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 μW at 1 V supply. To highlight the flexibility of the design, a second application, detecting pathologic ECG beats is also discussed.