2026-04-17T18:52:36Zhttps://riubu.ubu.es/oai/request

oai:riubu.ubu.es:10259/75362023-04-18T10:42:52Zcom_10259_4141com_10259_5086com_10259_2604com_10259_4219com_10259_4996com_10259_3989com_10259.4_106com_10259_5377com_10259_6688col_10259_4142col_10259_4220col_10259_6689col_10259_4999col_10259_5378

00925njm 22002777a 4500 dc Ramírez Sanz, José Miguel author Garrido Labrador, José Luis author Olivares Gil, Alicia author García Bustillo, Álvaro author Arnaiz González, Álvar author Diez Pastor, José Francisco author Jahouh, Maha author González Santos, Josefa author González Bernal, Jerónimo author Allende-Río, Marta author Valiñas Sieiro, Florita author Trejo Gabriel y Galán, José Mª author Cubo Delgado, Esther author 2023-02 The consolidation of telerehabilitation for the treatment of many diseases over the last decades is a consequence of its cost-effective results and its ability to offer access to rehabilitation in remote areas. Telerehabilitation operates over a distance, so vulnerable patients are never exposed to unnecessary risks. Despite its low cost, the need for a professional to assess therapeutic exercises and proper corporal movements online should also be mentioned. The focus of this paper is on a telerehabilitation system for patients suffering from Parkinson’s disease in remote villages and other less accessible locations. A full-stack is presented using big data frameworks that facilitate communication between the patient and the occupational therapist, the recording of each session, and real-time skeleton identification using artificial intelligence techniques. Big data technologies are used to process the numerous videos that are generated during the course of treating simultaneous patients. Moreover, the skeleton of each patient can be estimated using deep neural networks for automated evaluation of corporal exercises, which is of immense help to the therapists in charge of the treatment programs. http://hdl.handle.net/10259/7536 10.3390/healthcare11040507 2227-9032 Parkinson’s disease Telerehabilitation Telemedicine Big data Artificial intelligence in healthcare A Low-Cost System Using a Big-Data Deep-Learning Framework for Assessing Physical Telerehabilitation: A Proof-of-Concept