Biomechanics Sensor Node for Virtual Reality: A Wearable Device Applied to Gait Recovery for Neurofunctional Rehabilitation

Abstract

In several segments of the health areas, sensing has become a trend. Sensors allow data quantification for use in decision making or even to predict the clinical evolution of a given treatment, such as in rehabilitation therapies to restore patients’ motor and cognitive functions. This paper presents the Biomechanics Sensor Node (BSN), composed of an inertial measurement unit (IMU), developed to infer input information and control virtual environments. We also present a software solution, which integrates the BSN data with Unity Editor, one of the most used game engine nowadays. This asset allows Unity-developed virtual reality applications to use BSN a secure interaction device. Thus, during rehabilitation sessions, the patient receives visual stimuli from the virtual environment, controlled by the BSN device, while the therapist has access to the information about the movements performed in the therapy.

Accuracy study of the Oculus Touch v2 versus inertial sensor for a single-axis rotation simulating the elbow’s range of motion

“…In addition, these solutions could lead to the development of personalized training methods for upper extremity rehabilitation. There are similar systems that integrate more inertial sensors for motion capture of all body segments (Brandão et al 2020;Fitzgerald et al 2007). These solutions allow the patient to receive realtime visual stimuli from a virtual environment, and they provide the therapist with information about the movements performed during therapy.…”

Virtual and Augmented Reality for Neurofunctional Recovery and Human Movement Analysis

“…Among the projects aimed at the creation and testing of new technologies for neurorehabilitation, the BRAINN_VR research line is responsible for the areas of development in a) virtual and augmented reality interfaces [1,2,6,8,16,19,20] (immersive and nonimmersive virtual environments) associated with adapted physical activity and context physical and neurofunctional rehabilitation; b) wearable devices for sensing and body recognition associated with the control of virtual environments [3,7,9,12,14,15] (from gestural interaction) and; c) movement analysis solution to quantify the functional evolution and describe the motor behaviour associated with gestural interaction [4,5,17] (KinesiOS software). Figure 2 presents the environment's set-up for carrying out the tests.…”