Handheld Robotic Medical Device for Semi-automated Nerve Block Administration in Austere Environments

Acute combat pain (ACP) from battlefield injuries has adverse effects, including (1) diminished operational effectiveness, (2) consumption of limited medical resources, and (3) heightened PTSD risk. Current Tactical Combat Casualty Care (TCCC) pain management guidelines include the use of opioids, such as oral transmucosal fentanyl citrate or parenteral morphine, and ketamine. Opioids are effective but increase the risk of respiratory depression, drowsiness, confusion, impaired mobility, gastrointestinal side effects, and addiction. Ketamine is increasingly preferred owing to its strong analgesic effect, rapid onset of action, and lower respiratory depression risk. However, ketamine has a short duration of action and an increased risk of dissociation, hallucinations, anxiety, cardiovascular effects, and addiction.  Peripheral nerve blocks (PNB) offer a superior alternative to opioids or ketamine for managing ACP. They provide localized and effective pain relief without the systemic side effects, rendering them particularly suitable for use in field settings where maintaining cognitive and physical capacities is crucial. The adoption of PNBs also aligns with the strategic goals of military medicine by preserving medical resources and improving the relative operational readiness of personnel. Unfortunately, the use of PNBs in austere environments is limited by the high level of technical skill required for their administration, which is outside of the training of almost all medics and many other military healthcare providers. Given the modest cost and size of ultrasound, this limitation is primarily due to the challenges of ultrasound image interpretation and coordinated needle guidance; skills that require significant training to master and are typically in the purview of subspecialist anesthesiologists. To help personnel rapidly overcome this skills gap, AutonomUS’s Artificial Intelligence-Guided Ultrasound Intervention Device (AI-GUIDE) integrates ultrasound, machine learning, and hand-held robotics. The on-device machine learning algorithms interpret the ultrasound imagery in real time and guide the user where to place the device via a simple targeting display. The robotics perform the needle insertion and anesthetic delivery. By enabling medics with fundamental medical training to safely and effectively perform PNB, AI-GUIDE extends the accessibility of advanced pain management techniques to austere environments. The result would be a fighting force with increased operational effectiveness, reduced PTSD, and better preparedness for prolonged field care.