Due to an ageing society, the increase in chronic diseases, more cost-intensive health care and the lack of qualified personnel, the health care system is currently facing major challenges. In this context, the rehabilitation and care of neuromotor diseases is considered a special challenge.
76% of people in need of long-term care in Germany are currently being cared for at home (51.7% by relatives and 24.3% with the help of an ambulatory care service) and this proportion is expected to increase in the future.1 However, the high and intensive level of stationary care can currently only be transferred to the ambulatory sector to a limited extent. For example, a number of aids that are used in the clinical environment for nursing and rehabilitation are not available in ambulatory care.
The present use case addresses this challenge and aims at the decisive transfer from the stationary care and rehabilitation to the ambulatory sector. The use of exoskeleton systems can contribute to closing this gap in care by transferring system and therapy-relevant data to the home context without media discontinuity.
The aim here is to ensure that patients continue to be cared for by therapists at home by means of telepresence and that they carry out self-determined therapy measures with the help of robotic upper body assistance. The progress of the treatment is reliably monitored and evaluated by continuous data collection. Thus, the provision of an individual training program as well as a continuous control of the training can be ensured at any time.
What added value does the "GAIA-X project" offer?
With the principle of data sovereignty, GAIA-X directly addresses an obstacle to the digitisation of the health sector: sensitive personalised data can be securely collected and exchanged.
In addition, GAIA-X ensures secure communication between therapist and patient and provides a database for storing and using exercises, training programs and therapeutic measures. Longterm and case-specific evaluation allows therapy successes to be tracked and adopted as general recommendations for use.
Personalised medicine is characterised by the cooperation of different treating doctors and therapists. The harmonized presentation and evaluation of data coupled with a reliable access rights system enables the creation of effective and individual treatment plans.
Use Case Team
Dr. Elsa A. Kirchner – German Research Center for Artificial Intelligence – Robotics Innovation Center (DFKI RIC)
Niels Will – German Research Center for Artificial Intelligence – Robotics Innovation Center (DFKI RIC)
Marc Tabie – German Research Center for Artificial Intelligence – Robotics Innovation Center (DFKI RIC)