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UC Santa Cruz Unveils AI Wearable That Accelerates Wound Healing in Preclinical Tests

Preclinical data show roughly 25% faster closure versus standard care.

Overview

  • The a-Heal prototype integrates a tiny onboard camera, bioelectronic actuators, and nearby AI processing to monitor wounds and adjust therapy in real time.
  • A reinforcement-learning model guided by the Deep Mapper algorithm interprets serial images, quantifies healing stage, forecasts trajectories, and personalizes decisions.
  • Therapy consists of topical fluoxetine delivered through the device or an applied electric field, with dosing and field strength set by the AI.
  • Images and healing metrics stream to a secure web interface for clinician oversight, enabling remote monitoring and potential use for patients with limited mobility.
  • Researchers are extending the platform to chronic and infected wounds, with reported support from DARPA and ARPA-H, and the current evidence comes from preclinical models.