Dimitar Stefanov

The smart house for older persons and persons with physical disabilities: structure, technology arrangements, and perspectives

Smart houses are considered a good alternative for the independent life of older persons and persons with disabilities. Numerous intelligent devices, embedded into the home environment, can provide the resident with both movement assistance and 24-h health monitoring. Modern home-installed systems tend to be not only physically versatile in functionality but also emotionally human-friendly, i.e., they may be able to perform their functions without disturbing the user and without causing him/her any pain, inconvenience, or movement restriction, instead possibly providing him/her with comfort and pleasure. Through an extensive survey, this paper analyzes the building blocks of smart houses, with particular attention paid to the health monitoring subsystem as an important component, by addressing the basic requirements of various sensors implemented from both research and clinical perspectives. The paper will then discuss some important issues of the future development of an intelligent residential space with a human-friendly health monitoring functional system.

Robotic smart house to assist people with movement disabilities

This paper introduces a new robotic smart house, Intelligent Sweet Home, developed at KAIST in Korea, which is based on several robotic agents and aims at testing advanced concepts for independent living of the elderly and people with disabilities. The work focuses on technical solutions for human-friendly assistance in motion/mobility and advanced human-machine interfaces that provide simple control of all assistive robotic systems and home-installed appliances. The smart house concept includes an intelligent bed, intelligent wheelchair, and robotic hoist for effortless transfer of the user between bed and wheelchair. The design solutions comply with most of the users’ requirements and suggestions collected by a special questionnaire survey of people with disabilities. The smart house responds to the users commands as well as to the recognized intentions of the user. Various interfaces, based on hand gestures, voice, body movement, and posture, have been studied and tested. The paper describes the overall system structure and explains the design and functionality of some main system components.

Which Robot Features Can Stimulate Better Responses from Children with Autism in Robot-Assisted Therapy?

This study explores the response of autistic children to a few design features of the robots for autism therapy and provides suggestions on the robot features that have a stronger influence on the therapeutic process. First, we investigate the effect of selected robot features on the development of social communication skills in autistic children. The results indicate that the toys “face” and “moving limb” usually draw the childrens attention and improve childrens facial expression skills, but do not contribute to the development of other social communication skills. Secondly, we study the response of children with low-functioning autism to robots with verbal communication functionalities. Test results show that children interacted with the verbal-featured robot more intensively than with the experimenter. We conclude that robots with faces and moving limbs can engage autistic children in a better way. Facial expression of the robots can elicit a greater response than prompting by humans.

Advances in Rehabilitation Robotics

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Real-time estimation of tongue movement based on suprahyoid muscle activity

In this study, we introduce a real-time method for tongue movement estimation based on the analysis of the surface electromyography (EMG) signals from the suprahyoid muscles, which usual function is to open the mouth and to control the position of the hyoid, the base of the tongue. Nine surface electrodes were affixed to the underside of the jaw and their signals were processed via multi-channel EMG system. The features of the EMG signals were extracted by using a root mean square (RMS) method. The dimension of the variables was reduced additionally from 108 to 10 by applying the Principal Component Analysis (PCA). The feature quantities of the reduced dimension set were associated with the tongue movements by using an artificial neural network. Results showed that the proposed method allows precise estimation of the tongue movements. For the test data set, the identification rate was greater than 97 % and the response time was less than 0.7 s. The proposed method could be implemented to facilitate novel approaches for alternative communication and control of assistive technology for supporting the independent living of people with severe quadriplegia.

Improving wheelchair prescription: an analysis of user needs and existing tools

Wheelchair users experience many situations that affect the stability and associated performance of their wheelchair. Stability is affected by user characteristics and abilities, environmental features and conditions, and wheelchair modification and accessories. Wheelchair prescribers need effective tools and methods to provide quantitative evaluation and prediction of the behavior of the user-wheelchair system in a variety of static and dynamic situations. Such information is very important to guide efficient management of associated risks and adjust chairs accordingly. This project involves a user-centered approach for design and evaluation of a load cell based wheelchair stability assessment system (Wheel-SAS). Here, the current methods for assessing stability are described, and their shortcomings explained. The user-centered design approach being applied to the development of the associated Wheel-SAS hardware and software is described. Future work including semi-structured interviews and an online survey with wheelchair prescribers and associated healthcare professionals for deriving user requirements and a design specification for a load cell system for measuring dynamic wheelchair stability are detailed.

Trajectory planning of a robot for lower limb rehabilitation

We introduce a method for lower-limb physical rehabilitation by means of a robot that applies preliminary defined forces to a patients foot while moving it on a preliminary defined trajectory. We developed a special musculoskeletal model that takes into consideration the generated muscle forces of 27 musculotendon actuators and joint stiffness of the leg and allows the calculation of the motion trajectory of the robot and the forces that the robot needs to apply to the foot in each moment of the therapeutic exercise. Robotic treatment programs are customized for the individual patient by using a genetic algorithm (GA) that refers to the musculoskeletal model and calculates the parameters of the spline curves of the motion trajectory of the robot and forces acting on the foot.

Toward gesture controlled wheelchair: A proof of concept study

This study focuses on the early stages of developing and testing an interactive approach for gesture-based wheelchair control that could facilitate the user in various tasks such as cooking and food serving. The proposed method allows a user to hold an object (tray, saucepan, etc) with both hands and to control at the same time the wheelchair direction via changing the position of his/her arms. The wheelchair control system contains an image sensor directed to the users arms. Sensor signals are processed via an image-recognition algorithm and the calculations for the arm positions are used for the computation of the wheelchair steering signals. Thus, the wheelchair direction depends on the arm positions and the user can control the wheelchair by moving his/her arms. An initial wheelchair prototype, operated by the intentional motions of one hand, was built and was tested by several initial experiments.

Robotic wheelchair control interface based on headrest pressure measurement

We introduce a novel approach for proportional head control for robotic wheelchairs. An array of force sensors embedded into the headrest is used to monitor the pressure distribution changes due to the intentional head motions of the patient. The force signals are analysed and converted into fully proportional signals that control the wheelchair direction and speed. We developed a prototype interface that generates signals similar to the signals of a standard joystick control box and connected the new interface to a standard Invacare wheelchair. Tests showed that all users adapted to the control algorithm very quickly and were able to follow very precisely complex target trajectories on various speeds. The interface does not require any attachments to the users head and does not cause any limitation of the users field of view.

Enhancement of the Communication Effectiveness of Interactive Robots for Autism Therapy by Using Touch and Colour Feedback

Abstract Previous studies in the field of robot assisted therapy demonstrated that robots engage autistic children’s attention in a better way. Therefore, the interactive robots appear to be a promising approach for improving the social interaction and communication skills of autistic children. However, most of the existing interactive robots use a very small number of communication variableswhich narrow their effectiveness to a few aspects of autistic childrens’ social communication behaviour. In the present work, we explore the effects of touching and colours on the communication effectiveness between a robot and an autistic child and their potential for further adjustability of the robot to child’s behaviour. Firstly, we investigated touching patterns of autistic and non-autistic children in three different situations and validated their responses by comparison of touching forces. Results showed that patterns of touching by non-autistic children have certain consistency, while reaction patterns in autistic children vary from person to person. Secondly, we studied the effect of colour feedback in autism therapy with the robot. Results showed that participants achieved better completion rate when colour feedback was provided. The results could support the design of more effective therapeutic robots for children with autism.