Fraunhofer Research Institution for Individualized Medical Technology and Engineering IMTEDigital Rehabilitation Programme for Assessing Mobility in Older Adults Using 3D Motion Tracking
About
The DREAM research project investigates mobility in older adults with the aim of identifying individual fall risks at an early stage and optimising digital rehabilitation interventions. To achieve this, movement data from the DigiCare digital training programme are combined with activity sensors and three-dimensional gait analyses. Based on these data, a method for assessing individual resilience to falls will be developed and integrated into the digital training management system.
Opportunity
Approximately one in three people aged over 65 experiences at least one fall each year. Falls are often caused by a combination of physical limitations, such as impaired balance, and external factors. Precise analyses of movement patterns and physical activity are essential for identifying individual fall risks at an early stage and developing appropriate preventive measures. However, existing assessment methods provide only limited insight into the complex movement patterns encountered in everyday life.
Solution/Product Description
In the DREAM project, the twelve-week DigiCare digital rehabilitation programme is being supplemented and evaluated through the continuous monitoring of everyday activities using wearable motion sensors. In addition, three-dimensional gait analyses are conducted on an instrumented perturbation treadmill to investigate stability and responsiveness to unexpected disturbances.
The collected movement data are analysed using computational methods and used to develop an assessment tool for individual fall resilience. In the long term, the findings are intended to be incorporated into DigiCare's training management system, enabling rehabilitation interventions to be tailored to individual needs and systematically optimised.
Why us
DREAM combines the continuous monitoring of everyday physical activity with detailed three-dimensional gait analysis under controlled perturbation conditions. By integrating digital training data, wearable sensor technology and instrumented motion analysis, the project establishes a comprehensive approach to assessing individual fall risks. Integrating these findings into the DigiCare rehabilitation programme provides the foundation for data-driven, personalised training management and more targeted fall prevention.
The project partners are the University of Lübeck and DigiRehab GmbH.
