Adaptive Brain-Computer Interface Systems For Communication in People with Severe Neuromuscular Disabilities

Brain-computer interfaces (BCI) have the potential to restore communication or control abilities in individuals with severe neuromuscular limitations, such as those with amyotrophic lateral sclerosis (ALS). The role of a BCI is to extract and decode relevant information that conveys a user's intent directly from brain electro-physiological signals and translate this information into executable commands to control external devices. However, the BCI decision-making process is error-prone due to noisy electro-physiological data, representing the classic problem of efficiently transmitting and receiving information via a noisy communication channel.

This research focuses on P300-based BCIs which rely predominantly on event-related potentials (ERP) that are elicited as a function of a user's uncertainty regarding stimulus events, in either an acoustic or a visual oddball recognition task. The P300-based BCI system enables users to communicate messages from a set of choices by selecting a target character or icon that conveys a desired intent or action. P300-based BCIs have been widely researched as a communication alternative, especially in individuals with ALS who represent a target BCI user population. For the P300-based BCI, repeated data measurements are required to enhance the low signal-to-noise ratio of the elicited ERPs embedded in electroencephalography (EEG) data, in order to improve the accuracy of the target character estimation process. As a result, BCIs have relatively slower speeds when compared to other commercial assistive communication devices, and this limits BCI adoption by their target user population. The goal of this research is to develop algorithms that take into account the physical limitations of the target BCI population to improve the efficiency of ERP-based spellers for real-world communication.

In this work, it is hypothesised that building adaptive capabilities into the BCI framework can potentially give the BCI system the flexibility to improve performance by adjusting system parameters in response to changing user inputs. The research in this work addresses three potential areas for improvement within the P300 speller framework: information optimisation, target character estimation and error correction. The visual interface and its operation control the method by which the ERPs are elicited through the presentation of stimulus events. The parameters of the stimulus presentation paradigm can be modified to modulate and enhance the elicited ERPs. A new stimulus presentation paradigm is developed in order to maximise the information content that is presented to the user by tuning stimulus paradigm parameters to positively affect performance. Internally, the BCI system determines the amount of data to collect and the method by which these data are processed to estimate the user's target character. Algorithms that exploit language information are developed to enhance the target character estimation process and to correct erroneous BCI selections. In addition, a new model-based method to predict BCI performance is developed, an approach which is independent of stimulus presentation paradigm and accounts for dynamic data collection. The studies presented in this work provide evidence that the proposed methods for incorporating adaptive strategies in the three areas have the potential to significantly improve BCI communication rates, and the proposed method for predicting BCI performance provides a reliable means to pre-assess BCI performance without extensive online testing.

Barriers to reporting child maltreatment: do emergency medical services professionals fully understand their role as mandatory reporters?

BACKGROUND: Child maltreatment is underreported in the United States and in North Carolina. In North Carolina and other states, mandatory reporting laws require various professionals to make reports, thereby helping to reduce underreporting of child maltreatment. This study aims to understand why emergency medical services (EMS) professionals may fail to report suspicions of maltreatment despite mandatory reporting policies. METHODS: A web-based, anonymous, voluntary survey of EMS professionals in North Carolina was used to assess knowledge of their agency's written protocols and potential reasons for underreporting suspicion of maltreatment (n=444). Results were based on descriptive statistics. Responses of line staff and leadership personnel were compared using chi-square analysis. RESULTS: Thirty-eight percent of respondents were unaware of their agency's written protocols regarding reporting of child maltreatment. Additionally, 25% of EMS professionals who knew of their agency's protocol incorrectly believed that the report should be filed by someone other than the person with firsthand knowledge of the suspected maltreatment. Leadership personnel generally understood reporting requirements better than did line staff. Respondents indicated that peers may fail to report maltreatment for several reasons: they believe another authority would file the report, including the hospital (52.3%) or law enforcement (27.7%); they are uncertain whether they had witnessed abuse (47.7%); and they are uncertain about what should be reported (41.4%). LIMITATIONS: This survey may not generalize to all EMS professionals in North Carolina. CONCLUSIONS: Training opportunities for EMS professionals that address proper identification and reporting of child maltreatment, as well as cross-agency information sharing, are warranted.