As the population ages, the demand for nursing services continues to grow, which places unprecedented high demands on the design and functionality of nursing clothing. However, traditional nursing clothing has obvious limitations in terms of comfort, functionality and intelligence, and it is difficult to fully meet the needs of modern nursing services. In response to this situation, an innovative nursing clothing system based on artificial intelligence technology comes into being and quickly becomes a research hotspot. The system integrates advanced sensors, efficient data analysis algorithms and intelligent feedback mechanisms to achieve multifunctional needs such as health monitoring, behavior recognition and nursing assistance for the care recipients. Experimental results show that the system can accurately monitor the vital signs and behavioral status of the care recipients, with an accuracy of up to 99%, which can provide accurate auxiliary information for caregivers, thereby improving the efficiency and quality of care services.

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The Innovation System of Nursing Clothing Based on Artificial Intelligence Technology

  • Dan Yu,
  • Yushan Liu,
  • Peipei Zhao

摘要

As the population ages, the demand for nursing services continues to grow, which places unprecedented high demands on the design and functionality of nursing clothing. However, traditional nursing clothing has obvious limitations in terms of comfort, functionality and intelligence, and it is difficult to fully meet the needs of modern nursing services. In response to this situation, an innovative nursing clothing system based on artificial intelligence technology comes into being and quickly becomes a research hotspot. The system integrates advanced sensors, efficient data analysis algorithms and intelligent feedback mechanisms to achieve multifunctional needs such as health monitoring, behavior recognition and nursing assistance for the care recipients. Experimental results show that the system can accurately monitor the vital signs and behavioral status of the care recipients, with an accuracy of up to 99%, which can provide accurate auxiliary information for caregivers, thereby improving the efficiency and quality of care services.