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Sensors and Devices Guided by Artificial Intelligence for Personalized Pain Medicine.

Yantao XingKaiyuan YangAlbert LuKen MackieFeng Guo
Published in: Cyborg and bionic systems (Washington, D.C.) (2024)
Personalized pain medicine aims to tailor pain treatment strategies for the specific needs and characteristics of an individual patient, holding the potential for improving treatment outcomes, reducing side effects, and enhancing patient satisfaction. Despite existing pain markers and treatments, challenges remain in understanding, detecting, and treating complex pain conditions. Here, we review recent engineering efforts in developing various sensors and devices for addressing challenges in the personalized treatment of pain. We summarize the basics of pain pathology and introduce various sensors and devices for pain monitoring, assessment, and relief. We also discuss advancements taking advantage of rapidly developing medical artificial intelligence (AI), such as AI-based analgesia devices, wearable sensors, and healthcare systems. We believe that these innovative technologies may lead to more precise and responsive personalized medicine, greatly improved patient quality of life, increased efficiency of medical systems, and reducing the incidence of addiction and substance use disorders.
Keyphrases
  • artificial intelligence
  • chronic pain
  • pain management
  • neuropathic pain
  • healthcare
  • machine learning
  • big data
  • spinal cord
  • case report
  • risk factors
  • risk assessment
  • low cost
  • quality improvement