Stroke affects everybody differently, and it is difficult to say how much of a recovery is possible. Many stroke survivors experi- ence the most dramatic recovery during their stay in hospital in the weeks after their stroke. But many also continue to improve over a longer time, sometimes over a number of years. The goal of rehabilitation is to help survivors become as independent as possible and to attain the best possible quality of life.
Rehabilitation does not “cure” stroke; it does not reverse brain damage. High quality rehabilitation is essential to regain many – if not all – capabilities to lead a meaningful, fulfilling and even productive life. We aim at a cost effective and sleek infrastructure with integrated sensors. This infrastructure will collect relevant physical and medical parameters of a patients’ status for checkups and relapse prevention. It will support off- and online management and monitoring of the rehabilitation protocol, promote patient’s social participation and community building.
Rehab at Home aims at dealing with the issue of rehabilitation from a 360° perspective. A remote healthcare computational architecture will be provided based on distributed smart sensors (first processing layer) and personalized physiological assistive and intelligent algorithms integrated in a multilevel physiological human model.
Rehab at Home will provide new IT business opportunities in the field of home rehabilitation and enable new services to be deployed by rehabilitation centers. Rehab at Home is expected to decrease the costs for treating diseases common to the elderly. Rehab at Home will enable active and healthy ageing through effec- tive and engaging rehabilitation as well as social inclusion and community building.
Rehab at Home will use low price medical devices to carry out the rehabilitation exercises. The feedback to see if the exercises are done correctly will be monitored via a display. Service providers are connected via the Internet to the patient. The effectiveness will be reviewed by medical studies.
The research leading to these results has received funding from the European Union Seventh Framework Programme (FP7/2007-2013) under grant agreement n° 306113.