Medical gait analysis for movement disorders
Reliable diagnostics and therapy monitoring for fall prevention
Poor gait is a cardinal symptom in many chronic diseases (e.g. neurological, geriatric or orthopedic diseases) and is often the cause of serious falls in patients with movement disorders. Maintaining the ability to walk through medication or physiotherapy is therefore one of the main goals of therapeutic approaches.
The constant increase in symptoms associated with chronic movement disorders such as Parkinson’s make it necessary to continuously adapt the therapy over the years. So far, however, the extent of the restricted movement could only be assessed at three to four doctor visits a year. There was a lack of objective data collected from the patient’s everyday life.
The quality of life of Parkinson’s patients is severely restricted by mobility losses. To make matters worse, the ability to walk changes over the course of the day (fluctuations), which often leads to falls. The necessary individualized medication adjustment (dose/time of administration) is only possible to a limited extent with the previous care structures – it requires a hospital stay of several days. With gait characteristics (gait analysis) continuously collected from everyday life, the doctor treating you receives an exact picture of the course of the disease and the effectiveness of his therapy.
The foundations for the development were laid in two research projects: In the eGaIT project, gait characteristics were calculated on the basis of internal sensors on the outside of the shoe using signal analysis and pattern recognition methods, which objectively represent the disease stage. To do this, the patient carries out standardized tests. In the follow-up project Mobile GaitLab, sensors integrated into the shoe continuously recorded the gait quality in everyday life. Using machine learning, the system will in future also predict symptoms (freezing, falls) and thus enable personalized therapy.
“Without the two research projects, it would not have been possible for us to advance the system so far. Through the funding, the project sponsors showed their trust in our consortium and especially in us as a start-up very early on. The employees of the project sponsors were always at our side with advice and action in both funding periods.”
Research funding and transfer of results
For the research project computer-assisted biometric gait analysis (“eGaIT” – embedded gait analysis using intelligent technology) with total costs of €895,000, the Bavarian Research Foundation approved a grant of around €438,000 in the period 12/2011 – 12/2014. Due to a promising market response, one of the managing directors of the applicant at the time, ASTRUM IT GmbH, founded the company Portabiles HealthCare Technologies GmbH together with the academic partners in 2016.
The further development of the product was carried out in the follow-up project entitled Mobile GaitLab: Telemedical gait analysis in patients with Parkinson’s syndrome in the project consortium with total costs of around €1.1 million as part of the Bavarian funding program for medical technology (BayMED) by the Bavarian State Ministry of Economics , regional development and energy with a subsidy of approx. €545,000 in the period 08/2017 – 01/2019 and supported by the project sponsor Bavaria in the implementation.
In order to be able to communicate and present the project professionally, ASTRUM IT and Portable HealthCare Technologies used the various platforms of Bayern Innovativ GmbH, such as the MedTechPharma 2012 and 2014 congresses, MT Connect, MedTech Live and, with the support of Bayern Innovativ, the NeuroRescue Final Conference in Barcelona.