Tracking and Classification of Head Movement for Augmentative and Alternative Communication Systems

The use of assistive technologies can mitigate or reduce the challenges faced by individuals with motor disabilities to use computer systems. However, those who feature severe involuntary movements often have fewer options at hand. This work describes an application that can recognize the user’s head using a conventional webcam, track its motion, model the desired functional movement, and recognize it to enable the use of a virtual keyboard. The proposed classifier features a flexible structure and may be personalized for different user need. Experimental results obtained with participants with no neurological disorders have shown that classifiers based on Hidden Markov Models provided similar or better performance than a classifier based on position threshold. However, motion segmentation and interpretation modules were sensitive to involuntary movements featured by participants with cerebral palsy that took part in the study.

Traded and combined cooperative control of a smart wheelchair

This article deals with a human–machine cooperative system for the control of a smart wheelchair for people with motor disabilities. The choice of a traded control mode is first argued. The paper then pursues two objectives. The first is to describe the design of the cooperative system by focusing on the dialogue and the interaction between the pilot and the robot. The second objective is to introduce a new cooperative mode. In this one, three features are proposed: two semi-autonomous features, a wall following and a doorway crossing, during which the user can intervene punctually to rectify a trajectory or a path, and an assisted mode where, conversely, the machine intervenes in a manual control to avoid obstacles. This mode of intervention of an entity, human or machine, supervising a movement controlled by the other is referred as “combined control.” Examples of scenarios exploiting the cooperative capabilities of the system are presented and discussed.

Does One Size Fit All? A Case Study to Discuss Findings of an Augmented Hands-Free Robot Teleoperation Concept for People with and without Motor Disabilities

Hands-free robot teleoperation and augmented reality have the potential to create an inclusive environment for people with motor disabilities. It may allow them to teleoperate robotic arms to manipulate objects. However, the experiences evoked by the same teleoperation concept and augmented reality can vary significantly for people with motor disabilities compared to those without disabilities. In this paper, we report the experiences of Miss L., a person with multiple sclerosis, when teleoperating a robotic arm in a hands-free multimodal manner using a virtual menu and visual hints presented through the Microsoft HoloLens 2. We discuss our findings and compare her experiences to those of people without disabilities using the same teleoperation concept. Additionally, we present three learning points from comparing these experiences: a re-evaluation of the metrics used to measure performance, being aware of the bias, and considering variability in abilities, which evokes different experiences. We consider these learning points can be extrapolated to carrying human–robot interaction evaluations with mixed groups of participants with and without disabilities.

Visual Gesture-Based Character Recognition Systems for Design of Assistive Technologies for People With Special Necessities

In the present scenario, around 15% of the world's population experience some form of disability. So, there has been an enormous increase in the demand for assistive techniques for overcoming the restraints faced by people with physical impairments. More recently, gesture-based character recognition (GBCR) has emerged as an assistive tool of immense importance, especially for facilitating the needs of persons with special necessities. Such GBCR systems serve as a powerful mediator for communication among people having hearing and speech impairments. They can also serve as a rehabilitative aid for people with motor disabilities who cannot write with pen on paper, or face difficulty in using common human-machine interactive (HMI) devices. This chapter provides a glimpse of disability prevalence around the globe and particularly in India, emphasizes the importance of learning-based GBCR systems in practical education of differently-abled children, and highlights the novel research contributions made in this field.

An FPGA-Embedded Brain-Computer Interface System to Support Individual Autonomy in Locked-In Individuals

Brain-computer interfaces (BCI) can detect specific EEG patterns and translate them into control signals for external devices by providing people suffering from severe motor disabilities with an alternative/additional channel to communicate and interact with the outer world. Many EEG-based BCIs rely on the P300 event-related potentials, mainly because they require training times for the user relatively short and provide higher selection speed. This paper proposes a P300-based portable embedded BCI system realized through an embedded hardware platform based on FPGA (field-programmable gate array), ensuring flexibility, reliability, and high-performance features. The system acquires EEG data during user visual stimulation and processes them in a real-time way to correctly detect and recognize the EEG features. The BCI system is designed to allow to user to perform communication and domotic controls.

Metformin Repurposing for Parkinson Disease Therapy: Opportunities and Challenges

Parkinson disease (PD) is a severe neurodegenerative disorder that affects around 2% of the population over 65 years old. It is characterized by the progressive loss of nigrostriatal dopaminergic neurons, resulting in motor disabilities of the patients. At present, only symptomatic cures are available, without suppressing disease progression. In this frame, the anti-diabetic drug metformin has been investigated as a potential disease modifier for PD, being a low-cost and generally well-tolerated medication, which has been successfully used for decades in the treatment of type 2 diabetes mellitus. Despite the precise mechanisms of action of metformin being not fully elucidated, the drug has been known to influence many cellular pathways that are associated with PD pathology. In this review, we present the evidence in the literature supporting the neuroprotective role of metformin, i.e., autophagy upregulation, degradation of pathological α-synuclein species, and regulation of mitochondrial functions. The epidemiological studies conducted in diabetic patients under metformin therapy aimed at evaluating the correlation between long-term metformin consumption and the risk of developing PD are also discussed. Finally, we provide an interpretation for the controversial results obtained both in experimental models and in clinical studies, thus providing a possible rationale for future investigations for the repositioning of metformin for PD therapy.

Methodology for the study and prediction of stiffness characteristics during bending rials for the design of adaptive clothing for people with motor disabilities

The article analyses the existing methods of studying the characteristics of bending stiffness. Topicality of improving the methodology for assessing and predicting bending stiffness in relation to the operating conditions of the studied contingent of consumers is substantiated. The methodology includes two main stages – an experimental study of the stiffness characteristics taking into account the characteristics of the range under study and a stage of forecasting the design solutions of the product. Comprehensive experimen-tal studies of the bending characteristics of modern fabrics of the jacket assortment for adaptive clothing of people with motor disabilities have been carried out. For an objective assessment of wear during use, the proposed method implements an additional forced bending of samples in opposite directions in order to bring the test results closer to real operating conditions. The results of experimental studies can be used at the design stage to predict the bending characteristics of the fabrics of the jacket assortment of clothing for people with motor disabilities.

Customizing skills for assistive robotic manipulators, an inverse reinforcement learning approach with error-related potentials

Robotic assistance via motorized robotic arm manipulators can be of valuable assistance to individuals with upper-limb motor disabilities. Brain-computer interfaces (BCI) offer an intuitive means to control such assistive robotic manipulators. However, BCI performance may vary due to the non-stationary nature of the electroencephalogram (EEG) signals. It, hence, cannot be used safely for controlling tasks where errors may be detrimental to the user. Avoiding obstacles is one such task. As there exist many techniques to avoid obstacles in robotics, we propose to give the control to the robot to avoid obstacles and to leave to the user the choice of the robot behavior to do so a matter of personal preference as some users may be more daring while others more careful. We enable the users to train the robot controller to adapt its way to approach obstacles relying on BCI that detects error-related potentials (ErrP), indicative of the user’s error expectation of the robot’s current strategy to meet their preferences. Gaussian process-based inverse reinforcement learning, in combination with the ErrP-BCI, infers the user’s preference and updates the obstacle avoidance controller so as to generate personalized robot trajectories. We validate the approach in experiments with thirteen able-bodied subjects using a robotic arm that picks up, places and avoids real-life objects. Results show that the algorithm can learn user’s preference and adapt the robot behavior rapidly using less than five demonstrations not necessarily optimal.

ATTITUDES OF GOVERNMENT SCHOOL PRINCIPALS TOWARDS INTEGRATING STUDENTS WITH PHYSICAL DISABILITIES IN NABLUS GOVERNORATE

The study aimed to measure the attitudes of public school principals towards integrating students with motor disabilities in Nablus governorate and to measure the differences in the attitudes of government school principals towards integrating students with mobility disabilities in Nablus Governorate according to the different variables (gender, educational level, experience), and the descriptive survey method was used, and it was The study population consisted of all school principals in Nablus governorate, totaling (267) principals. The questionnaire was randomly distributed to a sample of (167) principals in Nablus governorate, which was statistically analyzed. The study showed the presence of high positive attitudes among public school principals towards integrating students with motor disabilities in Nablus governorate, and the presence of apparent differences in the attitudes of government school principals towards integrating students with motor disabilities in Nablus governorate due to gender in favor of females, and the absence of differences due to educational level and experience Based on the results of the study, it recommends preparing schools in a way that contributes to educating all workers to better accept the idea of inclusion in order to be successful in an optimal manner, and the need to issue legislation by the competent authorities, which guarantees the principle of equal opportunities for the disabled to obtain education, and the necessity of holding courses And workshops for managers in the field of inclusion of the disabled and special methods of dealing with them‎.