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Medical & Care Perception Systems

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This solution is built on TOF (Time-of-Flight) 3D depth sensing technology, combined with embedded algorithms and human behavior understanding models. It is designed for medical care, assisted living, elderly care, and rehabilitation monitoring, providing non-contact, privacy-friendly, and 24/7 reliable spatial perception and behavior recognition capabilities.

The system relies solely on depth information and does not capture RGB images, ensuring both privacy protection and long-term operational stability.
TOF Fall Detection & Behavior Recognition Demo
Fall Detection & Risk Alerting: By analyzing 3D human silhouettes and motion trajectories, the system detects falls from multiple directions and postures, enabling real-time alerts. Suitable for nursing homes, rehabilitation centers, hospitals, and independent living environments.
Prolonged Sitting / Lying Detection: Continuous monitoring of human posture changes in 3D space allows identification of abnormal prolonged sitting or lying behavior, providing decision support for caregivers and medical staff.
Privacy-Preserving, Non-Contact Sensing: The system outputs only depth data and behavior results. No color images are captured or stored, making it suitable for privacy-sensitive medical and care environments.
24/7 Stable Operation: Independent of ambient lighting conditions, the system operates reliably in darkness or low-light environments and is suitable for continuous, around-the-clock operation.
Embedded, Local Algorithm Deployment: All algorithms can run entirely on local embedded platforms without reliance on cloud services, ensuring real-time response, flexible deployment, and easy integration into existing medical systems.
CONTACT US

Tel: +86 186 6808 7462

Email: contact@3dsensing.cn

East China: 6102, Building B2, Dongfang Chuangzhi Park, Jinfang Road, Suzhou Industrial Park, Jiangsu Province, China

South China: Room 105, 1st Floor, Lingyun Building, Honglang North Second Road, Bao'an District, Shenzhen City, Guangdong Province

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