Most people would like to be able to live at home as long as possible in a self-determined and responsible manner. In order to meet this demand, effective and affordable technical assistance systems will have to be developed in the future that offer senior citizens a greater degree of safety and support. The assistance systems currently available are an important component of outpatient care and nursing. However, their major drawback is that they only engage after an emergency has arisen.

A research group led by computer scientist Uwe Tronnier is working on the development of openIntelliCare, a predictive assistance system that quickly and reliably makes predictions about the patient’s state of health. Depending on the health profile, the patient can be equipped with devices such as a blood pressure monitor, pulse oximeter or ECG. These continuously record the patient’s vital signs and report them via a smartphone to the emergency call centre. Based on the clinical condition of the patient, doctors at the emergency call centre decide whether emergency measures must be taken. Accounting for data protection, the patient’s health data and the medical decisions based on them are collected in a computer system. For each new decision to be made, the computer checks the patient’s current levels for consistency with known cases and lists measures that have proven successful or unsuccessful in the past. This makes it possible, for example, to detect a deterioration in heart function long before the first symptoms appear in the patient.

openIntelliCare brings together different approaches from the fields of home emergency alert systems, sensor-based patient monitoring and emergency call centre management. It is offered as an open technology platform, so that even small service providers can offer such emergency alert services. By actively assessing the health status of patients, the system can improve the quality of care and reduce the costs of home medical support and prevention.

The Federal Ministry of Education and Research is supporting the research project with about 292,000 euros within the framework of FHprofUnt as part of the Research at Universities of Applied Sciences programme.