ABSTRACT
Accuracy in vein detection is important for intravenous applications such as venipuncture and other medical procedures. The near-infrared (NIR) imaging technique is used to visualize veins based on the difference of absorption of the infrared light by the oxyhemoglobin present in the blood and surrounding tissue. A problem commonly found during the visualization of veins is attributed to the source of light, saturation, low contrast, and dispersion, which are causes of inhomogeneous illumination. In this work, the design and implementation of a light source with LEDs in the range of 750-860 nm are presented. To obtain the design, a numerical simulation was made using the near-field diffraction theory to obtain homogeneous illumination at 40 cm of the sample, with a radial arrangement of three concentric LED rings. With the developed light source, an experimental scheme for the acquisition of vein patterns was implemented. Using a basic algorithm for the identification of intravenous patterns, a prototype was obtained that we believe can be used in intravenous applications and other medical procedures.
Subject(s)
Lighting/instrumentation , Lighting/methods , Veins/diagnostic imaging , Equipment Design , Infrared Rays , Lasers , Phantoms, Imaging , PhlebotomyABSTRACT
Resumen En este trabajo se presenta un algoritmo para estimar el ángulo de rodilla a partir del ángulo de cadera y parámetros de marcha, el cual sólo utiliza un sensor en el muslo para la estimación. Para el desarrollo del algoritmo fue indispensable realizar un análisis de marcha para establecer parámetros de diseño. Se utilizó la correlación natural entre cadera y rodilla para separar los movimientos de flexión-extensión de marcha en dos etapas:1) movimientos donde el pie no está en contacto total con el piso; 2) movimientos de contacto total del pie con el piso. La estimación es para movimientos de marcha, se realiza en tiempo real y la variación de velocidad en la marcha no afecta la estimación del ángulo. Se utilizaron regresores lineales para aproximar el ángulo estimado de rodilla al ángulo real. En todos los casos de estudio de marcha, los resultados mostraron una aproximación aceptable del ángulo de la rodilla; el error promedio de estimación fue de 8.25◦. El principal logro de este trabajo fue desarrollar un algoritmo para dar una posible solución al problema de coordinación entre el cuerpo humano y prótesis transfemorales inteligentes, aun ante cambios de velocidad en la marcha.
Abstract This paper presents an algorithm to estimate the knee angle from hip angle and gait parameters. This algorithm uses a single sensor on the thigh to achieve the estimation. Hip-knee natural correlations were employed in order to analyze the gait flexion-extension movements in two stages: 1) when the foot is not in full contact with the floor (swing phase and heel contact); 2) when the whole sole makes contact with the ground (stance phase). The estimation is developed in real-time for gait movements and speed fluctuations do not distort the angle estimated. In addition, the simple linear regression were used to approximate the estimated angle to actual knee angle. The experimental results obtained from the gait studies, showed an acceptable knee angle approximation; the mean error estimation was 8.25◦. The major goal of this work was the development of an algorithm that can solve the problem of human body-intelligent transfemoral prosthesis coordination, even if there are gait speed fluctuations.
