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The motivation behind the Intelligent Elderly Care research is based on the number of elderly people in need of help with the activities in the EU is rapidly increasing, while the number of young workers is decreasing. Elder care will therefore have to be provided by intelligent computer systems in future.
Intelligent systems can play an important role in sustainable elderly care. The elder requires 24 hour monitoring in order to be able to detect falls, dizziness, illness, unusual behaviour due to dementia, etc. These issues are not met adequately, so more advanced solutions are needed. Tests were performed to evaluate movement patterns on various subjects when engaged in normal activities, falling and several health problems under medical supervision.
The Elderly Care system uses Ubisense, Smart technology, Accelerometers and Gyroscopes and is based on intelligent interpretation of movement patterns. The research includes hundreds of hours of recording over a period of two years, and is currently being intensively tested in several European countries, and is currently being intensively tested on the elderly at their homes in Italy.
ResearchThree tests are carried out on volunteers who are asked to wear Accelerometers and Gyroscopes, both of which are typically worn on the waist or chest. Accelerometers measure accelerations, which can be used to detect the impact due to fall. Gyroscopes measure angular velocities and can also be used for fall detection. The Ubisense location sensors are mounted on the wall and the tags are attached to the patients clothes. The Smart motion-capture system is also used for tracking positions of tags.
The Three Tests:
First test - five people imitated falls and four health problems: hemiplegia, back pain, leg pain and Parkinson’s disease. These recordings were captured with the Smart sensor system.
Second test - ten people imitated falls. The recordings were captured with the Ubisense system and Accelerometers.
Third test - four people imitated falls and the four same health problems. The recordings were captured with the Ubisense system.