RESUMEN
Advanced data analysis and visualization methodologies have played an important role in making surface electromyography both a valuable diagnostic methodology of neuromuscular disorders and a robust brain-machine interface, usable as a simple interface for prosthesis control, arm movement analysis, stiffness control, gait analysis, etc. But for diagnostic purposes, as well as for interfaces where the activation of single muscles is of interest, surface EMG suffers from severe crosstalk between deep and superficial muscle activation, making the reliable detection of the source of the signal, as well as reliable quantification of deeper muscle activation, prohibitively difficult. To address these issues we present a novel approach for processing surface electromyographic data. Our approach enables the reconstruction of 3D muscular activity location, making the depth of muscular activity directly visible. This is even possible when deep muscles are overlaid with superficial muscles, such as seen in the human forearm. The method, which we call imaging EMG (iEMG), is based on using the crosstalk between a sufficiently large number of surface electromyographic electrodes to reconstruct the 3D generating electrical potential distribution within a given area. Our results are validated by in vivo measurements of iEMG and ultrasound on the human forearm.
Asunto(s)
Electromiografía/métodos , Músculo Esquelético/diagnóstico por imagen , Músculo Esquelético/fisiología , Adulto , Electrodos , Electromiografía/instrumentación , Antebrazo/diagnóstico por imagen , Antebrazo/fisiología , Humanos , Masculino , UltrasonografíaRESUMEN
In order to stably grasp an object with an artificial hand, a priori knowledge of the object's properties is a major advantage, especially to ensure subsequent manipulation of the object held by the hand. This is also true for hand prostheses: pre-shaping of the hand while approaching the object, similar to able-bodied, allows the wearer for a much faster and more intuitive way of handling and grasping an object. For hand prostheses, it would be advantageous to obtain this information about object properties from a surface electromyography (sEMG) signal, which is already present and used to control the active prosthetic hand. We describe experiments in which human subjects grasp different objects at different positions while their muscular activity is recorded through eight sEMG electrodes placed on the forearm. Results show that sEMG data, gathered before the hand is in contact with the object, can be used to obtain relevant information on object properties such as size and weight.
Asunto(s)
Brazo/fisiología , Electromiografía/métodos , Fuerza de la Mano/fisiología , Movimiento/fisiología , Contracción Muscular/fisiología , Músculo Esquelético/fisiología , Desempeño Psicomotor/fisiología , Femenino , Humanos , Masculino , Reproducibilidad de los Resultados , Sensibilidad y Especificidad , Adulto JovenRESUMEN
The construction of robotic systems that can move the way humans do, with respect to agility, stability and precision, is a necessary prerequisite for the successful integration of robotic systems in human environments. We explain human-centered views on robotics, based on the three basic ingredients (1) actuation; (2) sensing; and (3) control, and formulate detailed examples thereof.