Our solution, consisting of a 3D-infrared-sensor and modular software, transforms uncertainty into clarity. Resident and patient behaviour is recorded seamlessly, providing comprehensive data for informed care decisions. The result: monitoring that creates safety and improves the quality of care.
The cogvis companion works as part of your team and adapts discreetly to any room and resident.
Mobile usability through docking station concept
Automatically adjusting sensor
Integrated night light
Presence button
Plug & play
Seamless nurse call integration
Developed in Austria
The cogvis platform transforms data into insights and enables you to provide individual care for each resident.
Individual settings per person
Create risk profiles
Set alarm periods
Overview of all active rooms
Comprehensible analyses of events
Care documentation connection via API
Premium cogvis support
The depth sensor captures spatial information only, producing a silhouette that shows posture and movement without any personal detail. This enables the system to recognise events such as getting out of bed, attempting to walk, or collapsing to floor level.
When a risky movement occurs, the sensor sends an immediate alert so staff can respond in real time. The captured movement sequence also provides insight into the lead-up to the incident, supporting both prevention and a clearer understanding of how the event unfolded.
The sensor combines several hardware elements that work together to create accurate depth information. At the top is the infrared depth emitter, which projects a pattern into the room so the device can measure distance and detect changes in posture. Beneath it sits the depth receiver, capturing these reflections and forming a precise 3D map of the space.
A dedicated processing module inside the unit analyses this data locally, reducing delay and ensuring no identifiable images are stored or transmitted. Additional environmental sensors monitor things like room layout and floor level, helping the system understand context and reducing false triggers. Together, these components create a reliable, privacy-preserving foundation for both real-time alerts and incident interpretation.
Fall detection
Fall analysis
Absence detection
Fall detection
Fall analysis
Absence detection
Fall prevention
Virtual bed beam
Virtual room beam
Integrated night light
Fall detection
Fall analysis
Absence detection
Fall prevention
Virtual bed beam
Virtual room beam
Integrated night light
Restlessness
Pressure ulcer prevention
Early detection of dementia
Care intensity indicator
