Patients with neurological disorders – such as after a stroke or paraplegia – often have motor impairment. With technical support, the impaired motor functions can be strengthened and potentially restored. Before now, the electric stimulation therapy systems and interactive neuroprostheses used for this purpose have had to be tailored to the individual patient – an expensive and time-consuming process. Non-invasive electric stimulation systems that adapt autonomously to users and their environmental interactions could reduce the cost of tailored rehabilitation.
The goal of the research partners in SmartSense4Life is to build a configurable electronic measurement platform to record and evaluate biosignal and sensor data, along with various other information. This will make it possible to create a self-learning system with feedback loops that can adapt autonomously to users and their environment.
The solution explained
The platform is conceived for integration into an electric stimulation system. To permit a broad range of applications via simple software configurations, the system’s design will be modular. The sensors will communicate with the sensor platform via a secure radio interface. This will be made possible by the comprehensive integration of a wide range of sensor, processing and wireless communication components. Although this will entail high one-off development costs, manufacturing will be inexpensive. The components to be developed in this project will be designed so as to make the overall system smaller and easier for patients and therapists to operate. In the longer term, the components will also facilitate the automatic adjustment of stimulation parameters and improve monitoring. At the same time, the system’s design will fulfill the latest (constantly increasing) requirements for data security, not least because the chips for individual components will be developed independently.
Within the project, Fraunhofer IIS/EAS is responsible for the specification and development of the modular platform and for the application- and person-based human-machine interface[r1] . In addition, the EAS division is involved in the implementation and system design of closed-loop systems for the demonstrators.