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AI-Assisted Ultrasound-Guided Galvanic Therapy (AAUGGT) – An Innovative Approach to Pain Management – Fundamental Mechanisms, Biomedical and Technical Development

Author

Listed:
  • Kaneez Abbas

    (Athreya Med Tech)

  • Behrooz Khajehee

    (University of Milano-Bicocca)

  • Mahdi Khanbabazadeh

    (Chiro Care Clinic)

  • Majd Oteibi

    (Validus Institute Inc)

  • Hadi Khazaei

    (Athreya Med Tech)

  • Bala Balaguru

    (Athreya Med Tech)

Abstract

AI-Assisted Ultrasound-Guided Galvanic Therapy (AAUGGT) is an emerging, minimally invasive approach to managing post-inflammatory musculoskeletal pain. This technique combines direct current (galvanic) stimulation with ultrasound imaging for the precise targeting of pathological tissues, further enhanced by artificial intelligence for real-time decision support and treatment optimization. AAUGGT is designed to improve precision, safety, and personalization in conditions such as chronic tendinopathy, myofascial pain, and post-surgical adhesions. The system’s architecture combines a handheld probe integrating ultrasound and galvanic electrodes, tissue impedance sensors, and adaptive AI algorithms for image segmentation and dose adjustment. Despite promising early evidence and technical innovation, widespread adoption of AAUGGT faces challenges, including the need for large-scale clinical trials, standardized devices, and regulatory approval. Continued development and multidisciplinary collaboration may establish AAUGGT as a next-generation therapeutic platform in musculoskeletal medicine, with potential for expanded clinical applications and home-based solutions.

Suggested Citation

  • Kaneez Abbas & Behrooz Khajehee & Mahdi Khanbabazadeh & Majd Oteibi & Hadi Khazaei & Bala Balaguru, 2025. "AI-Assisted Ultrasound-Guided Galvanic Therapy (AAUGGT) – An Innovative Approach to Pain Management – Fundamental Mechanisms, Biomedical and Technical Development," International Journal of Research and Innovation in Applied Science, International Journal of Research and Innovation in Applied Science (IJRIAS), vol. 10(7), pages 1280-1291, July.
  • Handle: RePEc:bjf:journl:v:10:y:2025:i:7:p:1280-1291
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