rEAsSiGN - Evaluation of a fall relevant gait analysis

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rEAsSiGN - Project profile

Objectives and procedure

The aim is to develop easy-to-use software that provides formal and informal carers and other health care professionals with a digital and effective tool for identifying the risk of falling and making decisions on preventive and mobility-preserving measures.
The research and development project addresses the following sub-segments:

  1. Fall risk identification
  2. Longer term fall prediction
  3. Automated recommendations for fall prevention/prophylaxis

Within the project applied for, the Research Group Geriatrics is mainly responsible for the research, identification and classification of general and specific fall risk factors from different data sources as well as the final evaluation of the individual digital applications developed in this R&D project for fall risk identifying gait analysis and fall prediction.
Using a smartphone/tablet camera, gait sequences are recorded and recognised as such. The generated data will be fed into a fall risk model (motion model) to be developed, thus training a neural network. With the help of an artificial intelligence (AI) these are calculated and their deviations from the healthy gait pattern are analysed and interpreted.

Innovation and perspectives

The individual fall risk of a person should be determined holistically with the help of artificial intelligence combined with biomechanical models of the human gait. From this, the risk of falling is determined and intervention measures are to be addressed individually and according to need. Digital solutions can relieve the burden on skilled workers and contribute to improving the quality of care. Both fall prediction and fall prevention deal with complex multifactorial problems due to the interaction between physiological, behavioural and environmental factors contributing to falls; the degree of innovation of the planned project is correspondingly high.

Project duration

04/2020 - 03/2022

Project leadership

Dr. Anika Heimann-Steinert

Head of Working Group Age and Technology

Dr. Nils Lahmann

Conductor of the working group empirical care research/ deputy head of Geriatrics Research Group

Staff members

Simone Kuntz

Research Assistant

Kathrin Raeder

Research Assistant

Nicole Strutz

Research Assistant

More information about the project