Brígida Mónica Faria

Evaluation of Distinct Input Methods of an Intelligent Wheelchair in Simulated and Real Environments: A Performance and Usability Study

This article 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 IW 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 IW 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.

Machine Learning algorithms applied to the classification of robotic soccer formations and opponent teams

Machine Learning (ML) and Knowledge Discovery (KD) are research areas with several different applications but that share a common objective of acquiring more and new information from data. This paper presents an application of several ML techniques in the identification of the opponent team and also on the classification of robotic soccer formations in the context of RoboCup international robotic soccer competition. RoboCup international project includes several distinct leagues were teams composed by different types of real or simulated robots play soccer games following a set of pre-established rules. The simulated 2D league uses simulated robots encouraging research on artificial intelligence methodologies like high-level coordination and machine learning techniques. The experimental tests performed, using four distinct datasets, enabled us to conclude that the Support Vector Machines (SVM) technique has higher accuracy than the k-Nearest Neighbor, Neural Networks and Kernel Naïve Bayes in terms of adaptation to a new kind of data. Also, the experimental results enable to conclude that using the Principal Component Analysis SVM achieves worse results than using simpler methods that have as primary assumption the distance between samples, like k-NN.

A Survey on Intelligent Wheelchair Prototypes and Simulators

Nowadays more than 700 million persons around the world have some kind of disability or handicap. During the last decades the elderly population in most of the European countries and across all the most civilized countries is also growing at an increasing pace. This phenomenon is receiving increasing attention from the scientific community, during the last years, and several solutions are being proposed in order to allow a more independent life to the people belonging to those groups. In this context Intelligent Wheelchairs (IW) are instruments that are a natural development of the scientific work that has been conducted to improve the traditional Wheelchair characteristics using health informatics, assistive robotics and human computer interface technologies. Some of the most important features of the IW are their navigation capabilities and automatic adaptation of their interface to the user. This paper presents the evolution and state of art concerning IWs prototypes and simulators and intelligent human-computer interfaces in the context of this devices. Our study enabled us to conclude that although several Intelligent Wheelchair prototypes are being developed in a large number of research projects, around the world, the adaptation of their user interface to the patient is an often neglected research topic. Thus, projects aiming at developing new concepts of Intelligent Wheelchairs are needed mainly using multimodal interfaces and wheelchair interfaces adapted to the user characteristics.

Patient Classification and Automatic Configuration of an Intelligent Wheelchair

The access to instruments that allow higher autonomy to people is increasing and the scientific community is giving special attention on designing and developing such systems. Intelligent Wheelchairs (IW) are an example of how the knowledge on robotics and artificial intelligence may be applied to this field. IWs can have different interfaces and multimodal interfaces enabling several inputs such as head movements, joystick, facial expressions and voice commands. This paper describes the foundations for creating a simple procedure for extracting user profiles, which can be used to adequately select the best IW command mode for each user. The methodology consists on an interactive wizard composed by a flexible set of simple tasks presented to the user, and a method for extracting and analyzing the user’s execution of those tasks. The results showed that it is possible to extract simple user profiles, using the proposed method.

Adapted Control Methods for Cerebral Palsy Users of an Intelligent Wheelchair

The development of an intelligent wheel chair (IW) platform that may be easily adapted to any commercial electric powered wheelchair and aid any person with special mobility needs is the main objective of the IntellWheels project. To be able to achieve this main objective, three distinct control methods were implemented in the IW: manual, shared and automatic. Several algorithms were developed for each of these control methods. This paper presents three of the most significant of those algorithms with emphasis on the shared control method. Experiments were performed by users suffering from cerebral palsy, using a realistic simulator, in order to validate the approach. The experiments revealed the importance of using shared (aided) controls for users with severe disabilities. The patients still felt having complete control over the wheelchair movement when using a shared control at a 50 % level and thus this control type was very well accepted. Thus it may be used in intelligent wheelchairs since it is able to correct the direction in case of involuntary movements of the user but still gives him a sense of complete control over the IW movement.

Cerebral Palsy EEG Signals Classification: Facial Expressions and Thoughts for Driving an Intelligent Wheelchair

Brain Computer Interfaces (BCI) enables interaction between users and hardware systems, through the recognition of brainwave activity. However, the current BCI systems still have a very low accuracy on the recognition of facial expressions and thoughts. This makes it very difficult to use these devices to enable safe and robust commands of complex devices such as an Intelligent Wheelchair. This paper presents an approach to expand the use of a brain computer interface for driving an intelligent wheelchair by patients suffering from cerebral palsy. The approach was based on appropriate signal preprocessing based on Hjorth parameters, a forward approach for variable selection and several data mining algorithms for classification such as naive Bayes, neural networks and support vector machines. Experiments were performed using 30 individuals suffering from IV and V degrees of cerebral palsy on the Gross Motor Function (GMF) measure. The results achieved showed that the preprocessing and variable selection methods were effective enabling to improve the results of a commercial BCI product by 57%. With the developed system it was also possible for users to perform a circuit in a simulated environment using just facial expressions and thoughts.

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.

Intelligent Wheelchair Driving: A Comparative Study of Cerebral Palsy Adults with Distinct Boccia Experience

An electronic wheelchair facilitates the autonomy and independence of a person, however specific cognitive, sensorial and perceptual skills are needed to conduct the assistive technology. These skills are also inherent to the sport boccia. Thus, the aim of this study is to understand the relationship between the experience of the participant in driving a wheelchair in relation to their autonomy and independence and also examine the practice of boccia in relation to the cognitive skills and performance in driving an intelligent wheelchair using a simulator. It was performed an evaluation of 28 participants, 6 of whom had no experience driving an electronic wheelchair and 22 had experience, 15 practice boccia and 13 did not practice this type of adapted sports. In the collection of data was tested three interfaces command of a smart wheelchair in a simulator. It was showed a good performance of the participants with experience in using electronic wheelchair and practitioners of boccia. It was also possible to observe that the autonomous and independent participants showed good results.

Intelligent Wheelchair Manual Control Methods

Assistive Technologies may greatly contribute to give autonomy and independence for individuals with physical limitations. Electric wheelchairs are examples of those assistive technologies and nowadays each time becoming more intelligent due to the use of technology that provides assisted safer driving. Usually, the user controls the electric wheelchair with a conventional analog joystick. However, this implies the need for an appropriate methodology to map the position of the joystick handle, in a Cartesian coordinate system, to the wheelchair wheels intended velocities. This mapping is very important since it will determine the response behavior of the wheelchair to the user manual control. This paper describes the implementation of several joystick mappings in an intelligent wheelchair (IW) prototype. Experiments were performed in a realistic simulator using cerebral palsy users with distinct driving abilities. The users had 6 different joystick control mapping methods and for each user the usability and the users’ preference order was measured. The results achieved show that a linear mapping, with appropriate parameters, between the joystick’s coordinates and the wheelchair wheel speeds is preferred by the majority of the users.

IntellWheels: Intelligent wheelchair with user-centered design

Intelligent wheelchairs can become an important solution to assist physically impaired individuals who find it difficult or impossible to drive regular powered wheelchairs. However, when designing the hardware architecture several projects compromise the user comfort and the wheelchair normal usability in order to solve robotic problems. In this paper we describe the main concepts regarding the design of the IntellWheels intelligent wheelchair. Our approach has a user-centered perspective, in which the needs and limitations of physically impaired users are given extensive attention at each stage of the design process. Finally, our design was evaluated through a public opinion assessment. A statistical analysis suggested that the design was effective to mitigate the visual and ergonomic impacts caused by the addition of sensorial and processing capabilities on the wheelchair.