The human brain acts as an intelligent sensor by helping in effective signal communication and execution of logical functions and instructions, thus, coordinating all functions of the human body. More importantly, it shows the potential to combine prior knowledge with adaptive learning, thus ensuring constant improvement. These qualities help the brain to interact efficiently with both, the body (brain-body) as well as the environment (brain-environment). This dissertation attempts to apply the brain-body-environment interactions (BBEI) to elevate human existence and enhance our day-to-day experiences. For instance, when one stepped out of the house in the past, one had to carry keys (for unlocking), money (for purchasing), and a phone (for communication). With the advent of smartphones, this scenario changed completely and today, it is often enough to carry just one's smartphone because all the above activities can be performed with a single device. In the future, with advanced research and progress in BBEI interactions, one will be able to perform many activities by dictating it in one's mind without any physical involvement. This dissertation aims to shift the paradigm of existing brain-computer-interfaces from just ‘control' to ‘monitor, control, enhance, and restore' in three main areas - healthcare, transportation safety, and cryptography. In healthcare, measures were developed for understanding brain-body interactions by correlating cerebral autoregulation with brain signals. The variation in estimated blood flow of brain (obtained through EEG) was detected with evoked change in blood pressure, thus, enabling EEG metrics to be used as a first hand screening tool to check impaired cerebral autoregulation. To enhance road safety, distracted drivers' behavior in various multitasking scenarios while driving was identified by significant changes in the time-frequency spectrum of the EEG signals. A distraction metric was calculated to rank the severity of a distraction task that can be used as an intuitive measure for distraction in people - analogous to the Richter scale for earthquakes. In cryptography, brain-environment interactions (BBEI) were qualitatively and quantitatively modeled to obtain cancelable biometrics and cryptographic keys using brain signals. Two different datasets were used to analyze the key generation process and it was observed that neurokeys established for every subject-task combination were unique, consistent, and can be revoked and re-issued in case of a breach. This dissertation envisions a future where humans and technology are intuitively connected by a seamless flow of information through ‘the most intelligent sensor', the brain.
| Identifer | oai:union.ndltd.org:unt.edu/info:ark/67531/metadc862723 |
| Date | 08 1900 |
| Creators | Bajwa, Garima |
| Contributors | Dantu, Ram, Joseph, Rajiv M, Caragea, Cornelia, Do, Hyunsook |
| Publisher | University of North Texas |
| Source Sets | University of North Texas |
| Language | English |
| Detected Language | English |
| Type | Thesis or Dissertation |
| Format | Text |
| Rights | Public, Bajwa, Garima, Copyright, Copyright is held by the author, unless otherwise noted. All rights Reserved. |
Page generated in 0.0025 seconds