Research of System Design and Automatic Detection Method for Excretion Nursing Equipment

Area of Science:

• Geriatric Nursing
• Biomedical Engineering
• Artificial Intelligence in Healthcare

Background:

• Increasing attention on elderly care, particularly for urination and defecation needs.
• Existing challenges in accurately identifying and managing elderly excretions.

Purpose of the Study:

• To design innovative excretion nursing equipment for precise urine and stool identification and management.
• To develop a reliable system for improving the quality of care for elderly individuals.

Main Methods:

• Utilized a split mechanical design and modular control approach for equipment development.
• Implemented Dempster-Shafer (D-S) evidence theory for accurate urine and stool identification.
• Analyzed requirements for effective excretion nursing equipment.

Main Results:

• The designed excretion nursing equipment demonstrated effective functionality in tests.
• The D-S evidence theory-based identification method achieved a 90% success rate.
• This represents a 20% improvement in accuracy compared to traditional identification methods.

Conclusions:

• The D-S evidence theory-based algorithm enhances recognition accuracy for excretion detection.
• The developed equipment successfully provides essential excretion care for patients.
• This innovation contributes to improved elderly care standards and patient outcomes.