Artificial Intelligence in Falls Management for Older Adult Care

Abstract

Older adults face significant public health difficulties from falls that lead to serious injuries alongside loss of independence and greater healthcare spending. The study examines how Artificial Intelligence (AI) can revolutionize fall risk management in geriatric care settings. The combination of machine learning algorithms with data from wearable sensors, along with electronic health records and environmental monitoring systems, enables AI to deliver proactive and personalized risk assessments as well as early fall detection with real-time intervention strategies. Caregivers gain continuous, personalized care capabilities through the integration of AI technology, which includes ambient intelligence and remote patient monitoring systems that help reduce the impact of falls. The study examines existing AI technologies used for fall prevention, evaluating their medical implications and suggesting future advancements to enhance the safety and well-being of the elderly.