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Dr. Oliver Amft
Julia Seiter
Lars Büthe


iCareNet is a Marie-Curie project funded by the European Union.
The main objective of the iCareNet is to make a decisive contribution towards context-aware systems in healthcare, wellness and assisted living (HWA) applications, leveraged through an interdisciplinary perspective ranging from sensing and sensor integration, to human-computer interaction and social factors in deploying solutions.

Context awareness has the potential to revolutionise the way people interact with information technology. Whereas conventional computers, merely interpret explicit user input, context-aware systems analyse and automatically respond upon users' behaviour. This enables electronic systems to assist users in situations in which the use of conventional computers and mobile devices is out of question.

iCareNet unites efforts of an interdisciplinary network of leading European research groups and a strong industrial participation. Currently the network comprises 11 full partners and 13 associate partners from several countries including Germany, United Kingdom, Switzerland, Finland, Denmark, Israel, and the Netherlands. Researchers receive comprehensive inter-domain training through a series of network-wide training events. iCareNet carries out broad-spectrum bottom-up research on eight application fields across HWA continuum, fundamental technology and methodology, and converts concepts into general guidelines for system architectures and design methodologies for context-aware solutions.
We work on the following sub-projects:

Long-term, comprehensive monitoring of daily routine for assisted living applications:
The aging society introduces several difficulties into elderly care, one of them being the increasing number of elderly people to monitor on a regular basis. Tracking daily routine could enable the detection of a changing trend in behavior which might be connected to the person's health condition. We develop and evaluate an ambient-wearable ubiquitous context-aware system that infers activity routines in daily life. Sensor modalities that are considered include movement (inertial) and location (indoor beacons, outdoor GPS). Discovery methods that infer daily routine patterns from sensor data without prior model learning are developed. The system and methods will be evaluated in an assisted living installation.

High-density meshed sensing garment using integrated sensors:
We contribute to the iCareNet be developing a low power, flat and flexible orientation sensor. The sensor can be integrated into textiles without altering the wearer's comfort due to its bendability. A wireless read-out functionality is designed without the need of any power supply for the sensor. This allows a comfortable readout without the need for any wiring in the textile.

The integration of this sensor into garments will then allow to detect the body posture of the wearer which is useful in rehabilitation. Instead of continuous supervision by a therapist, patients can perform their exercise while being monitored with an electronic system.


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