AI Solutions
Patient Monitoring
- Patient monitoring
Nurse shortage and challenging demographics calls for intelligent solutions that can support general ward in hospitals and in primary care to free up personnel time and support patient safety. We enable this via sensor, camera and AI technology across patient monitoring.
Kepler Night Nurse enables virtual supervision and detects incidents via images from an installed camera in healthcare facilities and hospitals worldwide. The software notices when clients fall and when people with dementia wander from their location. In addition, the system recognizes when a situation occurs where the client is prone to fall.
The Night Nurse system captures, processes and delete the images afterwards in the caregiver’s facility. Data will never leave the local network unless explicit agreed for e.g. calibrations.
- Fewer false alarms
- Increase safety of clients (fall prevention and detection)
- Time savings for clinical staff
The software provides detailed insight into a persons daily rhythm through the activity report, allowing for personalised alarm setting based on the individual risk profile, e.g: “Person on floor”, “Person out of room”, “Person not returning from toilet”, “Person got up from chair” or “Person on edge of bed.
- Understanding living patterns
- Indication in restlessness at night
- Indication if client withdraws more frequently.
Kepler Night Nurse is registered as medical device and may be used in European hospitals and healthcare facilities.
Visit Kepler Vision Technologies here
Ward 24/7 is an advanced clinical software technology build to introduce intelligent alarms and early detection of clinical deterioration. Today clinical staff spend hours for manual measurement of vital signs to perform routine EWS scoring across wards. Introducing wireless sensors for automated vitals sigs also introduces to many false alarms for the caregivers, hence there is a need for an intelligent interpretation of patient data.
Ward 24/7 enables continuously patient monitoring of vital signs without introducing a high number of false alarms for the clinical personnel and supports detection of clinical deterioration for a reduction of severe adverse event.
Visit WARD 24 | 7 here