Stefanie Blain

A Review of Emerging Access Technologies for Individuals With Severe Motor Impairments

Research and development in the field of access technologies for individuals with severe motor impairments has accelerated over the past 10 years. Many emergent alternatives to conventional mechanical switches, such as infrared sensing, electromyography, oculography, and computer vision, have been investigated for those retaining some limited volitional motor ability. At the same time, electroencephalography, electrocorticography, intracortical recordings, and electro-dermal activity have been explored for those presenting as locked in. The relevant literature is scattered across many disciplines, obfuscating the strength of the clinical evidence in support of the different access technologies currently in development. This article systematically organizes the literature on the aforementioned access technologies, summarizing their underlying operational mechanisms while reviewing the clinical evidence reported between 1996 and 2006. Research evidence within this period is generally found to be at the case study or uncontrolled study level, with very modest sample sizes. Novel mechanical switches and electroencephalography-based access systems dominate the literature, whereas many other movement-based access modalities have emerged with promising early findings. Access methods for those without extant physical movement constitute a critical direction for future and ongoing research efforts.

Peripheral Autonomic Signals as Access Pathways for Individuals with Severe Disabilities: A Literature Appraisal

Many individuals with severe and multiple disabilities do not have an access pathway that enables them to interface with their environment because they are not afforded a binary switch that they can reliably control. While recent research has focused on the self-regulation of central signals of the autonomic nervous system (ANS) to create brain- computer interfaces (BCIs) for these individuals, there has been less focus on the peripheral signals of the ANS as an access pathway. An appraisal of the literature in the areas of biofeedback, polygraphy and mental exercises uncovered considerable evidence that peripheral ANS signals can be voluntarily controlled and thus have the potential to be used as an access pathway by the target population. However, the issues of speed, metabolic noise and pathological change must be addressed before peripheral ANS signals can be used as either a complementary or alternative access pathway to existing brain-computer interfaces.

Bedside computer access for an individual with severe and multiple disabilities: A case study

Purpose. This case study documents the process of designing a custom-tailored bedside computer access solution for a 20-year old individual with quadriplegia and reports the effects of computer access on her participation in life activities. Method. We adopted a person-focused approach to match the individual to an access solution. Two months after the access solutions introduction, we measured its impact using a 2-dimensional Fitts Law test and questionnaire from the ISO 9241-9 standards document, typing tests, a usage log and a semi-structured interview. The Canadian Occupational Performance Measure was also administered pre- and post- access, focusing on the clients perceived ability to use the computer. Results. After 2 months, the individual was spending an average of 8.4 h per day on the computer, engaging in electronic communication, recreational, and educational activities. She learned single-switch typing with a throughput of 1.03 bits/s and targeting accuracy of 87.5%. The questionnaire revealed that the client was thoroughly satisfied with the interface. These results were interpreted as positive gains in the International Classification of Functioning, Disability and Health domains of communication and social interaction. Conclusions. By addressing individual goals, abilities and relevant environmental factors, a bedside computer access solution can be developed for individuals in long-term care. The introduction of a computer access solution augmented the participants communication, leisure and educational activities, as well as perceived independence.

A cardiorespiratory classifier of voluntary and involuntary electrodermal activity

BackgroundElectrodermal reactions (EDRs) can be attributed to many origins, including spontaneous fluctuations of electrodermal activity (EDA) and stimuli such as deep inspirations, voluntary mental activity and startling events. In fields that use EDA as a measure of psychophysiological state, the fact that EDRs may be elicited from many different stimuli is often ignored. This study attempts to classify observed EDRs as voluntary (i.e., generated from intentional respiratory or mental activity) or involuntary (i.e., generated from startling events or spontaneous electrodermal fluctuations).MethodsEight able-bodied participants were subjected to conditions that would cause a change in EDA: music imagery, startling noises, and deep inspirations. A user-centered cardiorespiratory classifier consisting of 1) an EDR detector, 2) a respiratory filter and 3) a cardiorespiratory filter was developed to automatically detect a participants EDRs and to classify the origin of their stimulation as voluntary or involuntary.ResultsDetected EDRs were classified with a positive predictive value of 78%, a negative predictive value of 81% and an overall accuracy of 78%. Without the classifier, EDRs could only be correctly attributed as voluntary or involuntary with an accuracy of 50%.ConclusionsThe proposed classifier may enable investigators to form more accurate interpretations of electrodermal activity as a measure of an individuals psychophysiological state.

On the use of peripheral autonomic signals for binary control of body-machine interfaces.

In this work, the potential of using peripheral autonomic (PA) responses as control signals for body-machine interfaces that require no physical movement was investigated. Electrodermal activity, skin temperature, heart rate and respiration rate were collected from six participants and hidden Markov models (HMMs) were used to automatically detect when a subject was performing music imagery as opposed to being at rest. Experiments were performed under controlled silent conditions as well as in the presence of continuous and startle (e.g. door slamming) ambient noise. By developing subject-specific HMMs, music imagery was detected under silent conditions with the average sensitivity and specificity of 94.2% and 93.3%, respectively. In the presence of startle noise stimuli, the system sensitivity and specificity levels of 78.8% and 80.2% were attained, respectively. In environments corrupted by continuous ambient and startle noise, the system specificity further decreased to 75.9%. To improve the system robustness against environmental noise, a startle noise detection and compensation strategy were proposed. Once in place, performance levels were shown to be comparable to those observed in silence. The obtained results suggest that PA signals, combined with HMMs, can be useful tools for the development of body-machine interfaces that allow individuals with severe motor impairments to communicate and/or to interact with their environment.

Conscious Control of Electrodermal Activity: The Potential of Mental Exercises

Few practical methods of communicating with people who are locked-in currently exit. This study investigates conscious control of physiological signals, specifically electrodermal activity, to generate two distinguishable and reproducible states. These states can be translated into a binary signal to control a communication device for people who are locked in. Breathing rates, mental arithmetic and mental music were investigated as means of controlling electrodermal activity. Features extracted from the signals included mean, range and number of electrodermal reactions. For these of four subjects, at least one mental technique caused a reproducible, statistically significant the potential of using mental exercises to develop volitional control of electrodermal activity.

A Radial Basis Function Classifier for Pediatric Aspiration Detection

Silent aspiration presents a serious health issue for children with dysphagia. To date, there is no satisfactory means of detecting aspiration in the home or community. In an effort to design a practical device that could offer reliability, non-invasiveness, portability, and easy usability, radial basis functions based on cervical accelerometry signals were investigated. Vibration signals associated with safe swallows and aspirations, both identified via videofluoroscopy, were collected from over 100 children with neurologically-based dysphagia using a single-axis accelerometer. Three time-domain discriminatory mathematical features were extracted from the accelerometry signals. An exhaustive set of all possible combinations of the features was investigated in the design of radial basis function classifiers. The feature pairing of dispersion ratio and normality achieved an accuracy of 81.03plusmn5.78%, a false negative rate of 9.06plusmn4.84%, and a false positive rate of 9.91plusmn5.03% for aspiration detection. The proposed classifier can be easily implemented in a hand-held device

Revealing Personhood Through Biomusic of Individuals Without Communicative Interaction Ability

An increasing number of people are unable to engage in communicative interactions because of their inability to move, speak, and control traditional augmentative and alternative communication devices. According to social interactionist theory, the existence of the human self hinges on successful interaction with others; consequently, those who cannot interact are at risk of not being accorded personhood. This article is a request for research towards the development of technologies that would give caregivers access to the autonomic physiological signals of individuals who are unable to communicate. It explores the hypothesis that meaningful manifestation of signals that change according to mental and emotional states will reveal individual personhood. We hypothesize that music is ideally suited as the basis of interaction with this population, and that physiologically driven musical expression is a form of individual biomusic that can enrich social interaction.