Protego

Personalized alaRming and cOntextualized dispaTching through lifEstyle monitorinG

To deal with the changing care requirements for the ageing population, we need to improve the efficiency of transmural care. Through the use of contextual AI services, PROTEGO will significantly improve alarm assessments, resource use and workflows within assisted living, homecare and call centers. By facilitating transmural care, residential care facilities will be relieved of unnecessary hospitalizations.

Today, personal alarm systems and monitoring devices need to be assessed and handled by caregivers, who are often unable to quickly assess the priority and validity of the alarm due to a lack of contextual and sensor data. As a result, one third of all interventions are false alarms. The nature of the required intervention is also hard to estimate, leading to inefficient dispatching, care workflows and use of resources.

Televic Healthcare innovation protego

Unplanned requests for aid

PROTEGO aims to increase the efficiency of care organizations by optimizing the handling of acute, unplanned events. It will do so by offering caregivers the required context and by making workflows adaptive to accurately assess, manage and dispatch unplanned requests for aid. Contextual AI services will enrich alarms by using contextual sensor and profile information (medical information, alarm history etc.). AI recommenders use, amongst other things, the result of the root cause analysis (the reason the call was made) to suggest the most appropriate dispatch strategy.

PROTEGO will achieve the following innovations:

  1. accurate assessment and prioritization of incoming unplanned events through AI services
  2. proactive alarms from home by detecting deviations in lifestyle patterns
  3. adaptive and interactive care workflows
  4. comprehensive patient and call overviews in personalized dynamic dashboards

Interested to read the full story? 

Protego is an imec.ICON project and is supported by VLAIO.

THC collaborates with Amaron, ML2Grow, Z-Plus and imec.IDLAB.