Sistema de apoio ao diagnóstico de sobrecargas plantares

• Autor(a) principal: Coelho, João Vítor da Silva
• Data de Publicação: 2021
• Tipo de documento: Dissertação
• Idioma: eng
• Título da fonte: Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
• Texto Completo: http://hdl.handle.net/10400.22/19686
• topic: Technology; Mobile applications; Web applications; Diabetes Mellitus; Diabetic foot ulcers; mHealth; Tecnologia; Aplicações móveis; Aplicações web; Úlceras do pé diabético

Diabetes Mellitus (DM) is a chronic disease that impacts the quality of life of individuals of various age groups, being listed among the 10 leading causes of death in adults. Associated with this disease are diabetic foot ulcers, which cause a reduction in the patient's mobility, quality of life and even amputation of the affected limb. In order to prevent this situation, the study in question aims to develop a mobile application to monitor the patient's gait. The gait data will be collected from a sensorised insole with pressure, temperature, and humidity sensors, with its subsequent analysis and real-time provision of warnings if situations conducive to the formation of a foot ulcer are found. As this insole has not yet been developed, a second mobile application was created to send data replicating several phases of the human gait. In addition, a web application was developed for healthcare professionals, where they can access the patient's personal data as well as various types of statistics associated with their gait, helping the professional to make decisions regarding the improvements that can be made regarding the way the patient performs the gait. All applications were properly tested and proved to be responsive on different devices, environments, and operating system versions. Throughout the development process, it was possible to observe that they will help the healthcare professional to detect more easily patterns in the patient's gait and will alert the patient to the need to change the way he supports the foot, with the provision of information in real time. In order to continue this study, it is hoped in the future to link this system with a clinical record repository, to create a learning algorithm that can use other parameters besides the reading records to create alerts, and finally, it would be useful to develop the application for the IOS operating system.