| Title | A Trusted Bluetooth Performance Evaluation Model for Brain Computer Interfaces |
| Publication Type | Conference Paper |
| Year of Publication | 2019 |
| Authors | Karim, Hassan, Rawat, Danda |
| Conference Name | 2019 IEEE 20th International Conference on Information Reuse and Integration for Data Science (IRI) |
| Keywords | ambulatory care, BCI hardware performance, BCI Safety, Bluetooth, Bluetooth operating parameters, bluetooth security, brain computer interface, brain computer interfaces, brain function classification accuracy, brain state, brain-computer interfaces, composability, Cyber physical system, cyber physical systems, data privacy, electroencephalography, feedback, fitness tracking, Human Behavior, medical signal processing, mobile BCI technology, mobile computing, Mobile Cyber Security, mobile EEG-based BCI applications, mobile neurofeedback applications, neurophysiology, Performance Rating, privacy, pubcrawl, resilience, Resiliency, security, system-on-chip, telemedicine, TMBCI, Trusted Mobile BCI Performance, wearable |
| Abstract | Bluetooth enables excellent mobility in Brain Computer Interface (BCI) research and other use cases including ambulatory care, telemedicine, fitness tracking and mindfulness training. Although significant research exists for an all-encompassing BCI performance rating, almost all the literature addresses performance in terms of brain state or brain function classification accuracy. For the few published experiments that address BCI hardware performance, they too, focused on improving classification accuracy. This paper explores some of the more recent studies and proposes a trusted performance rating for BCI applications based on the enhanced privacy, yet reduced bandwidth needs of mobile EEG-based BCI applications. This paper proposes a set of Bluetooth operating parameters required to meet the performance, usability and privacy requirements of reliable and secure mobile neuro-feedback applications. It presents a rating model, "Trusted Mobile BCI", based on those operating parameters, and validated the model with studies that leveraged mobile BCI technology. |
| DOI | 10.1109/IRI.2019.00021 |
| Citation Key | karim_trusted_2019 |
A Trusted Bluetooth Performance Evaluation Model for Brain Computer Interfaces