Fellowship Square Mesa reduces resident falls 90% with AI radar monitoring system Paul

Fellowship Square Mesa's assisted living community averaged 20 falls per month despite consistent preventive efforts including routine safety checks, resident education, and wearable alert devices. The care team recognized they needed a proactive approach rather than a reactive one, as existing interventions were not reducing fall rates meaningfully.

In July 2024, the community deployed Paul, a radar-based AI device from Helpany that continuously monitors residents' living spaces without cameras, microphones, or wearables. Paul tracks subtle changes in movement patterns, gait strength, and sleep quality to identify residents at increased fall risk, sending real-time alerts to staff smartphones and generating weekly resident reports to inform care planning.

Falls dropped from 20 per month to just 2 by December 2024 and January 2025—a 90% reduction. From August through December 2024, the community recorded zero overnight falls. The success has prompted exploration of expanding Paul's use across the broader campus.

• Radar-based monitoring that requires no wearables or cameras can overcome resident resistance and privacy concerns, enabling broad adoption in senior living.
• Stakeholder trust-building through resident and family focus groups was critical to successful rollout.
• Shifting from reactive incident response to proactive early-warning intervention dramatically outperforms traditional fall prevention protocols.