Automatic single-trial discrimination of mental arithmetic, mental singing and the no-control state from prefrontal activity: toward a three-state NIRS-BCI

<p>Abstract</p> <p>Background</p> <p>Near-infrared spectroscopy (NIRS) is an optical imaging technology that has recently been investigated for use in a safe, non-invasive brain-computer interface (BCI) for individuals with severe motor impairments. To date, most NIRS-BCI studies have attempted to discriminate two mental states (e.g., a mental task and rest), which could potentially lead to a two-choice BCI system. In this study, we attempted to automatically differentiate three mental states - specifically, intentional activity due to 1) a mental arithmetic (MA) task and 2) a mental singing (MS) task, and 3) an unconstrained, "no-control (NC)" state - to investigate the feasibility of a three-choice system-paced NIRS-BCI.</p> <p>Results</p> <p>Deploying a dual-wavelength frequency domain near-infrared spectrometer, we interrogated nine sites around the frontopolar locations while 7 able-bodied adults performed mental arithmetic and mental singing to answer multiple-choice questions within a system-paced paradigm. With a linear classifier trained on a ten-dimensional feature set, an overall classification accuracy of 56.2% was achieved for the MA vs. MS vs. NC classification problem and all individual participant accuracies significantly exceeded chance (i.e., 33%). However, as anticipated based on results of previous work, the three-class discrimination was unsuccessful for three participants due to the ineffectiveness of the mental singing task. Excluding these three participants increases the accuracy rate to 62.5%. Even without training, three of the remaining four participants achieved accuracies approaching 70%, the value often cited as being necessary for effective BCI communication.</p> <p>Conclusions</p> <p>These results are encouraging and demonstrate the potential of a three-state system-paced NIRS-BCI with two intentional control states corresponding to mental arithmetic and mental singing.</p

A Brain-Computer Interface Based on Bilateral Transcranial Doppler Ultrasound

In this study, we investigate the feasibility of a BCI based on transcranial Doppler ultrasound (TCD), a medical imaging technique used to monitor cerebral blood flow velocity. We classified the cerebral blood flow velocity changes associated with two mental tasks - a word generation task, and a mental rotation task. Cerebral blood flow velocity was measured simultaneously within the left and right middle cerebral arteries while nine able-bodied adults alternated between mental activity (i.e. word generation or mental rotation) and relaxation. Using linear discriminant analysis and a set of time-domain features, word generation and mental rotation were classified with respective average accuracies of 82.9%10.5 and 85.7%10.0 across all participants. Accuracies for all participants significantly exceeded chance. These results indicate that TCD is a promising measurement modality for BCI research

A Cognitive Radio Tracking System for Indoor Environments

Advances in wireless communication have enabled mobility of personal computing services equipped with sensing and computing capabilities. This has motivated the development of location-based services (LBS) that are implemented on top of existing communication infrastructures to cater to changing user contexts. To enable and support the delivery of LBS, accurate, reliable, and realtime user location information is needed. This thesis introduces a cognitive dynamic system for tracking the position of mobile users using received signal strength (RSS) in Wireless Local Area Networks (WLAN). The main challenge in WLAN positioning is the unpredictable nature of the RSS-position relationship. Existing system rely on a set of training samples collected at a set of anchor points with known positions in the environment to characterize this relationship. The first contribution of this thesis is the use of nonparametric kernel density estimation for minimum mean square error positioning using the RSS training data. This formulation enables the rigorous study of state-space filtering in the context of WLAN positioning. The outcome is the Nonparametric Information (NI) filter, a novel recursive position estimator that incorporates both RSS measurements and a dynamic model of pedestrian motion during estimation. In contrast to traditional Kalman filtering approaches, the NI filter does not require the explicit knowledge of RSS-position relationship and is therefore well-suited for the WLAN positioning problem. The use of the dynamic motion model by the NI filter leads to the design of a cognitive dynamic tracking system. This design harnesses the benefits of feedback and position predictions from the filter to guide the selection of anchor points and radio sensors used during estimation. Experimental results using real measurement from an office environment demonstrate the effectiveness of proactive determination of sensing and estimation parameters in mitigating difficulties that arise due to the unpredictable nature of the indoor radio environment. In particular, the results indicate that the proposed cognitive design achieves an improvement of 3.19m (56\%) in positioning error relative to memoryless positioning alone.Ph

Evaluating the Usability of a Wearable Social Skills Training Technology for Children with Autism Spectrum Disorder

Affecting 1 in 68, autism spectrum disorder (ASD) is a complex neurodevelopmental disorder characterized by social skill impairments. While prognosis can be significantly improved with intervention, few evidence-based interventions exist for social skill deficits in ASD. Existing interventions are resource-intensive, their outcomes vary widely for different individuals, and they often do not generalize to new contexts. Technology-aided intervention is a motivating, low-cost, and versatile approach for social skills training in ASD. Although early studies support the feasibility of technology-aided intervention, existing approaches have been criticized for teaching social skills through human-to-computer interaction, paradoxically leading to increased social isolation. To address this gap, we propose a system to help guide human-to-human interaction called Holli, a wearable technology to serve as a social skills coach for children with ASD. The Google Glass-based application listens to conversations and prompts the user with appropriate social responses. In this paper, we describe a usability study we conducted to determine the feasibility of using wearable technology to prompt children with ASD throughout social conversations. Fifteen children with ASD (mean age = 12.92 ± 2.33, verbal intelligent quotient = 103.3 ± 18.73) used the application while engaging in a restaurant-themed interaction with a research assistant. The application was evaluated on its effectiveness (i.e., how accurately the application responds), efficiency (i.e., how quickly the user and the application respond), and user satisfaction (based on a post-session questionnaire). All users were able to successfully complete the 10-turn exchange while using Holli. The results indicated the Holli accurately detected and recognized user utterance in real time. Participants reported positive experiences of using the application. To the best of our knowledge, this system is the first technology-aided intervention for ASD that employs human-to-human social coaching, and our results demonstrate the device is a viable medium for treatment delivery

Functional autonomic nervous system profile in children with autism spectrum disorder

Abstract Background Autonomic dysregulation has been recently reported as a feature of autism spectrum disorder (ASD). However, the nature of autonomic atypicalities in ASD remain largely unknown. The goal of this study was to characterize the cardiac autonomic profile of children with ASD across four domains affected in ASD (anxiety, attention, response inhibition, and social cognition), and suggested to be affected by autonomic dysregulation. Methods We compared measures of autonomic cardiac regulation in typically developing children (n = 34) and those with ASD (n = 40) as the children performed tasks eliciting anxiety, attention, response inhibition, and social cognition. Heart rate was used to quantify overall autonomic arousal, and respiratory sinus arrhythmia (RSA) was used as an index of vagal influences. Associations between atypical autonomic findings and intellectual functioning (Weschler scale), ASD symptomatology (Social Communication Questionnaire score), and co-morbid anxiety (Revised Children’s Anxiety and Depression Scale) were also investigated. Results The ASD group had marginally elevated basal heart rate, and showed decreased heart rate reactivity to social anxiety and increased RSA reactivity to the social cognition task. In this group, heart rate reactivity to the social anxiety task was positively correlated with IQ and task performance, and negatively correlated with generalized anxiety. RSA reactivity in the social cognition task was positively correlated with IQ. Conclusions Our data suggest overall autonomic hyperarousal in ASD and selective atypical reactivity to social tasks

Kernel-Based Positioning in Wireless Local Area Networks

The recent proliferation of Location-Based Services (LBSs) has necessitated the development of effective indoor positioning solutions. In such a context, Wireless Local Area Network (WLAN) positioning is a particularly viable solution in terms of hardware and installation costs due to the ubiquity of WLAN infrastructures. This paper examines three aspects of the problem of indoor WLAN positioning using received signal strength (RSS). First, we show that, due to the variability of RSS features over space, a spatially localized positioning method leads to improved positioning results. Second, we explore the problem of access point (AP) selection for positioning and demonstrate the need for further research in this area. Third, we present a kernelized distance calculation algorithm for comparing RSS observations to RSS training records. Experimental results indicate that the proposed system leads to a 17 percent (0.56 m) improvement over the widely used K-nearest neighbor and histogram-based methods

Thermal Imaging of the Periorbital Regions during the Presentation of an Auditory Startle Stimulus

Infrared thermal imaging of the inner canthi of the periorbital regions of the face can potentially serve as an input signal modality for an alternative access system for individuals with conditions that preclude speech or voluntary movement, such as total locked-in syndrome. However, it is unknown if the temperature of these regions is affected by the human startle response, as changes in the facial temperature of the periorbital regions manifested during the startle response could generate false positives in a thermography-based access system. This study presents an examination of the temperature characteristics of the periorbital regions of 11 able-bodied adult participants before and after a 102 dB auditory startle stimulus. The results indicate that the startle response has no substantial effect on the mean temperature of the periorbital regions. This indicates that thermography-based access solutions would be insensitive to startle reactions in their user, an important advantage over other modalities being considered in the context of access solutions for individuals with a severe motor disability