Evaluation of distinct input methods of an intelligent wheelchair in simulated and real environments: a performance and usability study

This paper focuses on evaluating the usability of an Intelligent Wheelchair (IW) in both real and simulated environments. The wheelchair is controlled at a high-level by a flexible multimodal interface, using voice commands, facial expressions, head movements and joystick as its main inputs. A Quasi-experimental design was applied including a deterministic sample with a questionnaire that enabled to apply the System Usability Scale. The subjects were divided in two independent samples: 46 individuals performing the experiment with an Intelligent Wheelchair in a simulated environment (28 using different commands in a sequential way and 18 with the liberty to choose the command); 12 individuals performing the experiment with a real IW. The main conclusion achieved by this study is that the usability of the Intelligent Wheelchair in a real environment is higher than in the simulated environment. However there were not statistical evidences to affirm that there are differences between the real and simulated wheelchairs in terms of safety and control. Also, most of users considered the multimodal way of driving the wheelchair very practical and satisfactory. Thus, it may be concluded that the multimodal interfaces enables very easy and safe control of the IW both in simulated and real environments.

A Methodology for Creating an Adapted Command Language for Driving an Intelligent Wheelchair

Intelligent wheelchairs (IW) are technologies that can increase the autonomy and independence of elderly people and patients suffering from some kind of disability. Nowadays the intelligent wheelchairs and the human-machine studies are very active research areas. This paper presents a methodology and a Data Analysis System (DAS) that provides an adapted command language to an user of the IW. This command language is a set of input sequences that can be created using inputs from an input device or a combination of the inputs available in a multimodal interface. The results show that there are statistical evidences to affirm that the mean of the evaluation of the DAS generated command language is higher than the mean of the evaluation of the command language recommended by the health specialist (p value = 0.002) with a sample of 11 cerebral palsy users. This work demonstrates that it is possible to adapt an intelligent wheelchair interface to the user even when the users present heterogeneous and severe physical constraints.