Design of an AI Platform to Support Home-Based Self-Training Music Interventions for Chronic Stroke Patients
David Sanchez-Pinsach, Mehmet Oğuz Mülâyim, Jennifer Grau-Sánchez, Emma Segura, Berta Juan-Corbella, Josep Lluís Arcos, Jesús Cerquides, Monique Messaggi-Sartor, Esther Duarte, Antoni Rogriguez-Fornells
In the Play&Sing project, we are developing an AI platform to support home-based self-training interventions for chronic stroke patients. A large percentage of patients suffering from this disease show motor deficits that clearly hinder their daily activities and diminish their quality of life. In this project we are proposing and testing a new Music Supported Therapy (MST) to induce upper limb motor recovery.With the help of a tablet-based application and a small musical keyboard, we are developing an AI platform to support home-based MST. Specifically, the role of AI algorithms is to support therapists and to boost user engagement by personalizing the interventions according to patient needs and preferences. AI algorithms will provide the therapists with hindsight and foresight tools. In the proposed MST, patients are performing 30 training sessions of 45 minutes with a frequency of 3 sessions per week. In this paper we present our platform and preliminary experiments conducted at a pilot phase.
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