Falls represent a significant risk for elderly individuals, often resulting in severe injuries, loss of independence, and increased healthcare burdens. The project seeks to evaluate whether Fallyx’s AI-driven wearable sensor can improve fall detection accuracy, accelerate emergency response times, and ultimately reduce preventable harm in supportive living environments.
The Fallyx sensor, designed as an unobtrusive waist-worn device, continuously tracks movement patterns and location data while maintaining resident comfort and discretion. Its AI algorithms analyze motion to distinguish between normal activities and potential falls, triggering immediate alerts to staff when incidents occur. Beyond reactive monitoring, the system may also identify subtle movement irregularities that signal elevated fall risk, enabling caregivers to implement preemptive measures such as balance training or environmental adjustments.
Image Credit: Fallyx
