Recognises bed-exit tendencies in several stages and provides information depending on the individual monitoring scenario
Care givers can intervene immediately and thus ensure the fastest possible fall rescue.
Monitors patient activity to assess sleep quality or validate therapeutic measures, supports delirium therapy and detects sudden restlessness and agitation.
Automatically detects lying positions and mobilisation in order to identify and minimise the risk of pressure sores at an early stage.
Alerts according to patient-specific monitoring scenario as soon as patients get up from chairs, wheelchairs, etc.
Recognises when there is no return to bed at night, for example after a visit to the toilet.
Detects when entering or leaving defined areas, e.g. toilet or patient room.
Monitors room and bed presence individually and in real time, even in shared rooms.
Recognising indicators for leaving the bed, wheelchair or similar at an early stage provides a decisive time advantage and leads to a significant reduction in falls.
Targeted and early alerting reduces the nursing effort in the patient’s room compared to other prevention systems, such as bell mats.
Compared to previously used prevention measures, QUMEA has achieved cost savings of between 49 and 76%.
After an initial system evaluation, the vast majority of users are clearly in favour of QUMEA.
QUMEA nominated as a finalist for the Swiss Medtech Award 2025
The Swiss Medtech Award honours companies in the Swiss medical technology sector - QUMEA is one of the contenders.
QUMEA wins largest European tender for digital mobility monitoring to date
Sweden's Västra Götaland Region (VGR) will be relying on the Swiss company's AI-supported technology over the next eight years to improve patient safety in its hospitals.
Human Bytes and QUMEA Partner to Bring Smarter Patient Monitoring to Danish Healthcare
Human Bytes and QUMEA are joining forces to introduce radar-based mobility monitoring to hospitals and elderly care facilities across Denmark.