The ability of new AI models to assist humans in performing tasks is creating new business models and transforming existing ones at breakneck speed. One of the application areas benefiting from this technology is healthcare. The work presented in this article falls within this domain. In this sense, our work focuses on how AI can be used to facilitate the work of therapists responsible for the physical rehabilitation of stroke patients. In particular, we present a decision support system integrated in a global remote rehabilitation system composed of two interconnected applications: the one used by the therapist to define routines and monitor patients and the one used by the patient to perform rehabilitation exercises autonomously. The decision support system is based on the use of fuzzy logic, which significantly increases its scalability and interpretability. The proposed system is capable of automatically suggesting personalised modifications to the rehabilitation routine assigned to a patient by the therapist, based on the patient's performance. In addition, this system integrates aspects of XAI by being able to justify why it suggests such modifications, so that the therapist has more information when validating or not validating the modifications proposed by the artificial system. The paper discusses a case study describing how a stroke patient's routine is automatically adjusted by the system.