Bioengineers and cognitive scientists have developed the first portable 64-channel wearable brain activity monitoring system that rivals the advanced equipment in the lab.
The system fits well with real-world applications because it is equipped with an eeg sensor that provides high-density brain activity data. It includes a 64-channel battery wearable eeg helmet and a sophisticated software for interpreting and analyzing data. Its wide range of applications, from scientific research to clinical diagnosis can be used.
The research team at the Institute of Neurological Computing at the Jacobs Institute of Engineering in the United States posted the result in a special issue of Wearables, the latest edition of ieee Bioengineering.
It is necessary to get rid of the laboratory "bondage"
The main purpose of this study is to help eeg system get out of the shackles of the laboratory. Scientists expect future neuroimaging systems to work with mobile sensors and smartphones to track the state of the brain and enhance brain function throughout the day.
They hope that future neuroimaging will bring new therapies to nervous system diseases. Gert Cohen-Boggs, a leading developer in the study at Bioengineering at Jacobs College, said: "We want the brain to solve its own problems and are now avoiding invasive technologies such as deep brain stimulation and prescription drugs. Instead, brain synapse plasticity initiates self-healing procedures. "
Tim Mullen, lead author of the paper and director of the University of California, San Diego, development-related software, said: "The time is right for a brain-computer interface as smart as a smartphone."
For this moment to come, the sensor needs to become not only as simple as wearable, but also as comfortable as its algorithms for data analysis to be able to cut off interference from meaningless information outside. The paper entitled "Real-time Neuroimaging and Cognitive Monitoring of Wearable EEG Systems" is an important first step in this direction.
Octopus helmet "flexible" full
A team headed by Mike Weichler, technical director at cognionics, has developed the octopus-shaped eeg helmet, each of its "arms" flexible so that it adapts to different head types. The sensor at the "arm" end is designed to touch the scalp first while mixing as little interference noise as possible.
The researchers spent four years refining the sensor's material formulation. The part of the sensor that touches the user's hair is made of a flexible substrate of silver and carbon that allows the sensor to remain flexible and durable in transmitting high quality signals where a silver / silver chloride coating is the key. In addition, the built-in conductive hydrogel membrane also allows the sensor to work directly on the exposed skin surface.
The researchers said the next step is to improve the helmet performance of the wearer on the move. After all, the helmet captures the signal as the wearer walks on foot, but the performance is poor when running and other strenuous activities.
Data analysis software "noise reduction" is good
Software that analyzes the data captured in the helmet was developed by Mullen's team. In EEG data, brain signals need to be separated from interfering signals. The weak current sent from the brain is usually easily disturbed by high-amplitude signals such as walk-in and talking.
Researchers have designed an algorithm for this, in real time these two types of signals can be separated, the trial wearers when the rest of the data and dynamic data comparison does not meet the requirements of the direct treatment as noise, and then get relatively simple Brain signal data.
But data analysis does not stop there. Using known brain anatomy and collected data, researchers can track signals generated interactively from different regions of the brain in real time, creating a constantly changing network of brain activity. Then, they allow the computer to connect to a special network of brain activity, learning the brain's cognitive and behavioral patterns.
Mullen said: "The highest state in this field is to track the changes in the distributed brain network at the speed of thought.We are close to this goal, but have not yet captured this Holy Grail."
Innovative start-ups by the "sought after"
Yuchi and Mullen have created their own brain technology business company.
Yuchi's company Cognionics, which sells helmets to research institutes, is also popular with neurofeedgesters. The ultimate goal of research in this area is to get helmets into clinics to help diagnose diseases such as stroke and epilepsy.
Mullen's startup, qusp, has developed a cloud-based software platform that provides continuous, real-time brain and body signal analysis with the goal of making brain-machine interfaces and advanced signal processing methods easier to work with A wide variety of everyday applications fit well with wearable devices.
Cognionics is developing an upgraded version of the eeg system with funding from the Defense Advanced Research Projects Agency (darpa), while qusp is developing graphics software that makes it easier to quickly design and analyze brain signals.
Cowens Burgess believes that the efforts of these innovative companies, it is to help Jacobs Institute of Engineering Institute of Computing to get rid of the laboratory "bondage" of successful practices.
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