Utilizing IoT Devices for Monitoring and Adjusting Clinical Pathway Exercises

Clinical pathways play a crucial role in the rehabilitation process of patients during and after a clinical stay. Posterior to the clinical stay, patients are usually left to their own devices. This fact hampers the adequate treatment of the patient as there is no longer a technical controlling and guiding instance. For this reason, this work describes the current status of the virtual coach, a) a semantic representation framework for clinical pathways with their immanent exercises and combines this semantic representation framework with b) a reinforcement learning approach for computing the optimal exercise severity level according to the current patient capabilities and recovery. The semantic representation and linkage of heterogeneous Internet of Things (IoT) devices to medical exercises helps to monitor and adjust exercise recommendations according to sensed environmental states. The combination of IoT with semantic web technologies as well as reinforcement learning contributes towards an optimal rehabilitation process.