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 electrodermal 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.

This pilot study examined the effects of Therapeutic Clowning on inpatients in a pediatric rehabilitation hospital. Ten disabled children with varied physical and verbal expressive abilities participated in all or portions of the data collection protocol. Employing a mixed-method, single-subject ABAB study design, measures of physiological arousal, emotion and behavior were obtained from eight children under two conditions—television exposure and therapeutic clown interventions. Four peripheral autonomic nervous system (ANS) signals were recorded as measures of physiological arousal; these signals were analyzed with respect to measures of emotion (verbal self reports of mood) and behavior (facial expressions and vocalizations). Semistructured interviews were completed with verbally expressive children (n = 7) and nurses of participating children (n = 13). Significant differences among children were found in response to the clown intervention relative to television exposure. Physiologically, changes in ANS signals occurred either more frequently or in different patterns. Emotionally, children's (self) and nurses' (observed) reports of mood were elevated positively. Behaviorally, children exhibited more positive and fewer negative facial expressions and vocalizations of emotion during the clown intervention. Content and themes extracted from the interviews corroborated these findings. The results suggest that this popular psychosocial intervention has a direct and positive impact on hospitalized children. This pilot study contributes to the current understanding of the importance of alternative approaches in promoting well-being within healthcare settings.

BackgroundSilent aspiration or the inhalation of foodstuffs without overt physiological signs presents a serious health issue for children with dysphagia. To date, there are no reliable means of detecting aspiration in the home or community. An assistive technology that performs in these environments could inform caregivers of adverse events and potentially reduce the morbidity and anxiety of the feeding experience for the child and caregiver, respectively. This paper proposes a classifier for automatic classification of aspiration and swallow vibration signals non-invasively recorded on the neck of children with dysphagia.MethodsVibration 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. Five potentially discriminatory mathematical features were extracted from the accelerometry signals. All possible combinations of the five features were investigated in the design of radial basis function classifiers. Performance of different classifiers was compared and the best feature sets were identified.ResultsOptimal feature combinations for two, three and four features resulted in statistically comparable adjusted accuracies with a radial basis classifier. In particular, the feature pairing of dispersion ratio and normality achieved an adjusted accuracy of 79.8 ± 7.3%, a sensitivity of 79.4 ± 11.7% and specificity of 80.3 ± 12.8% for aspiration detection. Addition of a third feature, namely energy, increased adjusted accuracy to 81.3 ± 8.5% but the change was not statistically significant. A closer look at normality and dispersion ratio features suggest leptokurticity and the frequency and magnitude of atypical values as distinguishing characteristics between swallows and aspirations. The achieved accuracies are 30% higher than those reported for bedside cervical auscultation.ConclusionThe proposed aspiration classification algorithm provides promising accuracy for aspiration detection in children. The classifier is conducive to hardware implementation as a non-invasive, portable "aspirometer". Future research should focus on further enhancement of accuracy rates by considering other signal features, classifier methods, or an augmented variety of training samples. The present study is an important first step towards the eventual development of wearable intelligent intervention systems for the diagnosis and management of aspiration.