Kaspard utilizes a non-intrusive 3D distance sensor and AI algorithms to detect falls and prolonged bed exits in real-time, alerting nursing staff immediately. This technology significantly reduces fall incidents in care facilities, enabling timely interventions and improving the overall safety and autonomy of elderly residents.
Funding
$5.8M raised to dateRaised to date based on public sources. This may differ from the amount the company actually raised and is based only on what is publicly available on the internet.
Founders
Product
Problem
Elderly residents in care facilities are at high risk of falls, which often go undetected or are discovered too late, leading to severe physical and psychological consequences. Current monitoring methods rely on scheduled rounds, which may not provide timely assistance and can contribute to a fear of falling among residents.
Solution
Kaspard offers a real-time fall detection and prevention solution designed to improve the safety and autonomy of elderly residents in care facilities. Utilizing a non-intrusive 3D distance sensor and AI algorithms, Kaspard detects falls and prolonged bed exits, alerting nursing staff immediately via DECT or smartphone. The system provides a 3D animation of the fall event and generates daily activity reports to help staff understand resident behavior and personalize care. By alerting staff to potential fall risks, Kaspard enables timely interventions and reduces the number of falls, promoting a safer environment and greater peace of mind for both residents and caregivers.
Target Audience
The primary customers are nursing homes, assisted living facilities (EHPAD), and hospitals seeking to enhance resident safety, reduce fall-related injuries, and improve staff efficiency.
Features
- Real-time fall detection using a 3D distance sensor and AI algorithms
- Alerts sent to nursing staff via DECT or smartphone for immediate response
- Bed exit detection with customizable time limits to prevent falls before they happen
- 3D animation of fall events for detailed analysis of circumstances
- Daily activity reports providing insights into resident behavior and movement patterns
- Integration with existing nurse call systems for seamless implementation
- Non-intrusive and contactless monitoring to respect resident privacy
- Low bandwidth usage by transferring resident status to a local server