The article reviews recent advancements in sensors and devices guided by artificial intelligence (AI) for personalized pain medicine. Personalized pain medicine aims to tailor pain treatment strategies to individual patient needs, improving outcomes and reducing side effects. The introduction highlights the prevalence and impact of pain, emphasizing the need for more precise and responsive treatments. The article discusses the challenges in understanding, detecting, and treating complex pain conditions, and reviews various sensors and devices for pain monitoring, assessment, and relief. Key advancements include AI-based analgesia devices, wearable sensors, and healthcare systems. AI can process extensive patient data, identify pain patterns, and predict treatment outcomes, enhancing treatment efficiency and reducing drug dependency. Wearable sensors monitor physiological and biochemical indicators, providing real-time data for personalized pain management. Smart devices enhance interactivity and personalization, facilitating cognitive behavioral therapy and remote consultations. The article also explores imaging devices, such as fMRI, PET, CT, and ultrasound, which provide detailed insights into pain assessment. Intelligent communication devices, leveraging AI and large language models (LLMs), offer psychological support and facilitate dialogue, addressing the psychological aspects of chronic pain. Biomarkers play a crucial role in pain assessment, integrating multiple biomarkers with clinical tools to enhance precision. Devices for pain relief, including implantable drug pumps, spinal cord stimulators, deep brain stimulators, and noninvasive methods like TENS, TMS, TCS, and ultrasonic technology, are discussed, highlighting their effectiveness and limitations. AI's integration in personalized pain medicine offers transformative benefits, but challenges remain, including data accuracy, device reliability, privacy, security, and cost. Future developments focus on AI-based analgesia devices, continuous monitoring, virtual reality and augmented reality treatments, and patient education and support. Global cooperation and resource optimization are essential for advancing personalized pain medicine.The article reviews recent advancements in sensors and devices guided by artificial intelligence (AI) for personalized pain medicine. Personalized pain medicine aims to tailor pain treatment strategies to individual patient needs, improving outcomes and reducing side effects. The introduction highlights the prevalence and impact of pain, emphasizing the need for more precise and responsive treatments. The article discusses the challenges in understanding, detecting, and treating complex pain conditions, and reviews various sensors and devices for pain monitoring, assessment, and relief. Key advancements include AI-based analgesia devices, wearable sensors, and healthcare systems. AI can process extensive patient data, identify pain patterns, and predict treatment outcomes, enhancing treatment efficiency and reducing drug dependency. Wearable sensors monitor physiological and biochemical indicators, providing real-time data for personalized pain management. Smart devices enhance interactivity and personalization, facilitating cognitive behavioral therapy and remote consultations. The article also explores imaging devices, such as fMRI, PET, CT, and ultrasound, which provide detailed insights into pain assessment. Intelligent communication devices, leveraging AI and large language models (LLMs), offer psychological support and facilitate dialogue, addressing the psychological aspects of chronic pain. Biomarkers play a crucial role in pain assessment, integrating multiple biomarkers with clinical tools to enhance precision. Devices for pain relief, including implantable drug pumps, spinal cord stimulators, deep brain stimulators, and noninvasive methods like TENS, TMS, TCS, and ultrasonic technology, are discussed, highlighting their effectiveness and limitations. AI's integration in personalized pain medicine offers transformative benefits, but challenges remain, including data accuracy, device reliability, privacy, security, and cost. Future developments focus on AI-based analgesia devices, continuous monitoring, virtual reality and augmented reality treatments, and patient education and support. Global cooperation and resource optimization are essential for advancing personalized pain medicine.