CONICET | Buscador de Institutos y Recursos Humanos

Most neurological diseases are usually accompanied by a broad spectrum of oculomotor alterations. Being able to record and analyze these different types of eye movements would be a valuable tool to understand the functional integrity of brain structures. Nowadays, video-oculography is the most widely used eye-movements assessing method. This paper presents a study of the existing eye tracking video-oculography techniques and also analyzes the importance of measuring slight head movements for diseases diagnosis. In particular, two types of methods are reviewed and compared, including appearance-based and feature-based methods which are further subdivided into 2D-mapping and 3D model-based approaches. In order to demonstrate the advantages and disadvantages of these different eye tracking methods for disease diagnosis, a series of comparisons are conducted between them, addressing the complexity of the system, the accuracy achieved, the ability to measure head movements and the external conditions for which they have been designed. Lastly, it also highlights the open challenges in this research field and discusses possible future directions.