title: Sequential hypothesis testing for automatic detection of task-related changes in cerebral perfusion in a brain-computer interface.
abstract: Evidence suggests that the cerebral blood flow patterns accompanying cognitive activity are retained in many locked-in patients. These patterns can be monitored using transcranial Doppler ultrasound (TCD), a medical imaging technique that measures bilateral cerebral blood flow velocities. Recently, TCD has been proposed as an alternative imaging modality for brain-computer interfaces (BCIs). However, most previous TCD-BCI studies have performed offline analyses with impractically lengthy tasks. In this study, we designed a BCI that automatically differentiates between counting and verbal fluency tasks using sequential hypothesis testing to make decisions as quickly as possible. Ten able-bodied participants silently alternated between counting and verbal fluency tasks within the paradigm of a simulated on-screen keyboard. During this experiment, blood flow velocities were recorded within the left and right middle cerebral arteries using bilateral TCD. Twelve features were used to characterize TCD signals. In a simulated online analysis, sequential hypothesis testing was used to update estimates of class probability every 250 ms as TCD data were processed. Classification was terminated once a threshold level of certainty was reached. Mean classification accuracy across all participants was 72% after an average of 23s, compared to an offline analysis which obtained a classification accuracy of 80% after 45 s. This represents a substantial gain in data transmission rate, while maintaining classification accuracies exceeding 70%. Furthermore, a range of decision times between 19 and 28s was observed, suggesting that the ability of sequential hypothesis testing to adapt the task duration for each individual participant is critical to achieving consistent performance across participants. These results indicate that sequential hypothesis testing is a promising alternative for online TCD-BCIs.
authors.affiliation: Bloorview Research Institute, Holland Bloorview Kids Rehabilitation Hospital, Toronto, ON, Canada; Institute of Biomaterials and Biomedical Engineering, University of Toronto, Toronto, ON, Canada.
authors.forename: Hayley G
authors.initials: HG
authors.lastname: Faulkner
authors.affiliation: Bloorview Research Institute, Holland Bloorview Kids Rehabilitation Hospital, Toronto, ON, Canada; Institute of Biomaterials and Biomedical Engineering, University of Toronto, Toronto, ON, Canada.
authors.forename: Andrew
authors.initials: A
authors.lastname: Myrden
authors.affiliation: Bloorview Research Institute, Holland Bloorview Kids Rehabilitation Hospital, Toronto, ON, Canada.
authors.forename: Michael
authors.initials: M
authors.lastname: Li
authors.affiliation: Bloorview Research Institute, Holland Bloorview Kids Rehabilitation Hospital, Toronto, ON, Canada.
authors.forename: Khondaker
authors.initials: K
authors.lastname: Mamun
authors.affiliation: Bloorview Research Institute, Holland Bloorview Kids Rehabilitation Hospital, Toronto, ON, Canada; Institute of Biomaterials and Biomedical Engineering, University of Toronto, Toronto, ON, Canada. Electronic address: tom.chau@utoronto.ca.
authors.forename: Tom
authors.initials: T
authors.lastname: Chau
mesh_terms: D000328:Adult; D062207:Brain-Computer Interfaces; D002540:Cerebral Cortex / Q000098:blood supply* / Q000502:physiology*; D003071:Cognition / Q000502:physiology*; D003657:Decision Making / Q000502:physiology*; D005260:Female; D006801:Humans; D008297:Male; D010363:Pattern Recognition, Automated; D012815:Signal Processing, Computer-Assisted; D017585:Ultrasonography, Doppler, Transcranial; D055815:Young Adult
keywords: Brain–computer interface; Functional transcranial Doppler; Verbal fluency task