## 7 Discussion  
Currently, there is evidence showing that patients with neurological disorders, such as stroke, experience a lack of coordination in that the normal spatial and temporal relationships between eye and hand movements during tasks requiring coordination are impaired, despite intact visual function [4]. These eye-hand relationships may need to be specifically targeted during the assessment stage and subsequently during rehabilitation. Hence, the development of tools to help clinicians in both stages is especially relevant. More relevant features of state-of-the-art systems for EHC assessment include drawing-like tasks (related to fine motor coordination) [7,33], reaching tasks (related to gross motor coordination) [34,35], game-based user interfaces [31,32], and haptic feedback [25,41], which are usually addressed separately. However, such features are integrated into the multimodal game-based system proposed in this paper. Multimodality allows for better use of different input devices to explore new strategies for EHC using the same tool, namely the eye-hand coordination game. In a previous conference article by the authors of this paper [28], the development of the virtual environment was briefly presented and the main goals of the proposed framework were established. Also, two input devices with small workspaces, such as the mouse and tablet pen, were included (related to fine motor skills). However, the multimodal framework was neither technically validated nor extended to methods for quantifying gross motor coordination. The current paper adds two robotic devices and presents trials to validate the proposed framework. Firstly, the evaluation of fine motor coordination was addressed using a methodology similar to that in related studies, specifically the use of drawing tasks [7] that can include haptic assistance [17,41]. The analysis of endpoint trajectories from drawing tasks has shown positive results in EHC assessment [17,33]. In this way, the assessment mode proposed in this paper involved point-to-point drawing tasks in a game-like virtual scenario. The user can draw according to different difficulty levels based on the characteristics of paths designed by expert clinicians. One relevant feature of the proposed system is its multimodality, which currently includes devices such as a mouse, a tablet pen, the Phantom Omni, and a robotic arm. The inclusion of multimodal devices can provide more performance-based information for a more detailed evaluation [26]. For example, the tablet pen system may provide useful information about the pressure and orientation exerted when drawing. The robotic systems can offer haptic feedback and hand force detection. This performance-based information can be properly combined with the position tracking of traces in order to improve the diagnosis of motor skill problems. Moreover, similar to our previous conference paper [28], this paper also presents a novel method aimed at extending the assessment capabilities from fine to gross coordination by integrating a collaborative robotic arm into the game-based system. This new device promotes the use of whole-arm movements to move the ball through the labyrinths. Motor skills describe the ability to control and coordinate movements. This can include fine motor control (e.g., small movements of the fingers and hands) and gross motor control (for example, large and coordinated movements of the arms, trunk, and legs) [53]. Gross motor skills require the coordination of large body parts for actions such as sitting, running, jumping, and throwing, while fine motor skills require the coordination of smaller movements between the fingers, hands, and feet for actions such as grasping, manipulating small objects, writing, and using scissors [37]. In the scope of this paper, fine motor skills can be evaluated using small devices such as a mouse, a tablet pen, or the Phantom Omni since they promote drawing tasks similar to writing.