Augmented reality system with application in physical rehabilitation

• Autor(a) principal: Yu Jin
• Data de Publicação: 2019
• Tipo de documento: Dissertação
• Idioma: eng
• Título da fonte: Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
• Texto Completo: http://hdl.handle.net/10071/20311
• topic: Augmented reality; Physical rehabilitation; Physical prameters; Motion sensors; Localization sensors; Realidade aumentada; Reabilitação física; Parâmetros físicos; Sensores de movimento; Sensores de localização

The aging phenomenon causes increased physiotherapy services requirements, with increased costs associated with long rehabilitation periods. Traditional rehabilitation methods rely on the subjective assessment of physiotherapists without supported training data. To overcome the shortcoming of traditional rehabilitation method and improve the efficiency of rehabilitation, AR (Augmented Reality) which represents a promissory technology that provides an immersive interaction with real and virtual objects is used. The AR devices may assure the capture body posture and scan the real environment that conducted to a growing number of AR applications focused on physical rehabilitation. In this MSc thesis, an AR platform used to materialize a physical rehabilitation plan for stroke patients is presented. Gait training is a significant part of physical rehabilitation for stroke patients. AR represents a promissory solution for training assessment providing information to the patients and physiotherapists about exercises to be done and the reached results. As part of MSc work an iOS application was developed in unity 3D platform. This application immersing patients in a mixed environment that combine real-world and virtual objects. The human computer interface is materialized by an iPhone as head-mounted 3D display and a set of wireless sensors for physiological and motion parameters measurement. The position and velocity of the patient are recorded by a smart carpet that includes capacitive sensors connected to a computation unit characterized by Wi-Fi communication capabilities. AR training scenario and the corresponding experimental results are part of the thesis.