Videojuego de realidad virtual para realizar ejercicios en bicicleta estacionaria mediante el uso de un sistema de detección de movimiento y visor Google Cardboard

A pesar del amplio conocimiento de los beneficios que la actividad física puede brindar para mejorar el estado de salud y prevenir cierto tipo de enfermedades crónicas no transmisibles a largo plazo, existen diversas limitaciones que dificultan que las personas puedan ejercitarse de forma regular como la falta de tiempo por sus condiciones laborales, tráfico en el traslado cotidiano y, más recientemente, un contexto de pandemia que limita los lugares y horas en que las que pueden salir a realizar todo tipo de actividades. Si bien muchas personas cuentan con bicicletas, ergómetros u otros equipos de entrenamiento dentro de sus casas, no todas ellas están dispuestas a seguir una rutina de ejercicios. Una de las principales razones por las que las personas no realizan ejercicios de forma regular es la falta de motivación y la falta de resultados a corto plazo. Actualmente existen diversas investigaciones que buscan resolver este problema a través de la adición de componentes lúdicos con diversos tipos de contenido añadido. Precisamente, los exergames de realidad virtual han demostrado influir positivamente en la motivación de las personas para permitir que estas puedan ejercitarse de manera divertida y prolongada. Por ello, el presente trabajo tiene por finalidad sentar una base de conocimiento para la implementación un exergame de realidad virtual para bicicletas estacionarias que afecte positivamente las necesidades psicológicas de las personas con la finalidad de mantenerlas motivadas a través de técnicas de gamificación que serán validadas en base a los resultados de investigaciones previas.Despite extensive knowledge that Physical activity can contribute to maintain a healthy condition and decrease the probabilities to suffer non-contagious chronic diseases in the long term, there are several limitations that prevent people from exercising regularly like lack of time due to working conditions, traffic in daily commute and, more recently, a pandemic context that limits the places and hours in which they can go out to do all kinds of activities. Although many people have bicycles, ergometers and other sorts of training machines, not all of them are willing to maintain a regular exercise routine. One of the main reasons for which people don´t exercise regularly is due to lack of motivation and no evident short-term results. Currently, there are plenty of investigations that seek to solve this problem by adding different sorts of ludic components with varied content. Precisely, virtual reality exergames have been shown to positively influence people's motivation to allow them to exercise in a fun and prolonged way. Therefore, the present work aims to establish a knowledge base for the implementation of a virtual reality exergame for stationary bicycles that positively affects the psychological needs of people in order to keep them motivated through gamification techniques that will be validated based on the results of previous research.Trabajo de investigació

Bicyclist Longitudinal Motion Modeling

69A43551747123Bike is a promising, human-powered, and emission-free transportation mode that is being increasingly advocated as a sustainable mode of transportation due to its significant positive impacts on congestion and the environment. Cities in the United States have experienced a rapid increase in bicycle ridership over the past decade. However, despite the growing popularity of bicycles for short-distance commuting and even for mid-distance recreational trips, researchers have generally ignored the investigation of bicycle traffic flow dynamics. Due to the shared space and frequent interactions among heterogeneous road users, bicycle flow dynamics should be evaluated to determine the tendency of lateral dispersion and its effects on traffic efficiency and safety. Therefore, this research effort proposes to model bicyclist longitudinal motion while accounting for bicycle interactions using vehicular traffic flow techniques. From the comparison of different states of motion for these two transport modes, the authors assumed there is no major difference between vehicular and bicyclist traffic characteristics. The study revamps the Fadhloun-Rakha car-following model previously developed by the research team to make it representative of bicycle traffic flow dynamics. The possibility of capturing cyclists\u2019 behaviors through revamping certain aspects of existing car-following models is investigated. Accordingly, 33 participants were recruited to ride the bike simulator and drive the car simulator simultaneously. The participants were recruited to operate a bike-simulator in order to test the proposed model under realistic traffic conditions and verify the output of the proposed model formulation remains valid when bicyclists are operating under realistic traffic conditions. Both simulators were integrated together, and each participant could inform about the location of another participant in the simulation interval. Six scenarios based on the initial position of the bike and car were developed. Based on the collected data, the Fadhloun-Rakha model was validated to ensure the development of a good descriptor for speed and acceleration and deceleration behaviors. A reliable sample including 100 model parameters values was selected. Root Mean Square Error (RMSE) for the mentioned sample was obtained, and the smallest RMSE in each scenario was identified. Using the obtained RMSEs, the speed and acceleration trajectories for the smallest RMSE in each scenario were drawn. Eventually, the optimal values of the model parameters (a,b,d) in each scenario were specified