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In neuroscience, the frontier of brain-computer interfaces (BCI) holds the promise of bridging the gap between the human brain and external devices, offering revolutionary applications in fields ranging from robotics and prosthetics to communication and beyond. In the lab, scientists studying and developing new BCI technology leverage the human brain’s electrical and physiological signals.

Electroencephalography (EEG), functional near-infrared spectroscopy (fNIRS), and steady-state visually evoked potentials (SSVEP) are among the primary physiological and psychophysiological signals utilized in these investigations. Multimodal integration of two or more signal types allows researchers and engineers to take advantage of multiple data streams in their applications and studies.

EEG, which can measure electrical activity in the brain, is a cornerstone of BCI research. Researchers can decode various mental states and intentions by analyzing EEG patterns, enabling users to control external devices through mere thought. fNIRS complements EEG by measuring changes in blood oxygenation levels, offering insights into brain function with superior spatial resolution. SSVEP, on the other hand, capitalizes on the brain’s response to visual stimuli, providing a means for precise control in BCI applications.

The practical implications of BCI research extend far beyond the laboratory setting. In robotics, BCIs facilitate direct brain-to-machine communication, empowering users to manipulate robotic arms or navigate autonomous vehicles with their thoughts alone. A study published in the Journal of Information Science Engineering explored ways that an SSVEP-based BCI could be used to control assembly line robots via a headset measuring the operator’s EEG signals. The signals would communicate instructions to robots while operators identified defective parts, which the robots would pick out. During the experiment, EEG signals were obtained using a B-Alert X24 headset. The EEG-based BCI produced a 93.33% success rate in correctly identifying and removing defective parts from the assembly line process, allowing the operator to effectively “collaborate with the robot and communicate defective parts without manually operating the robot.”

Prosthetics benefit immensely from BCI advancements, enabling seamless integration with the user’s neural signals for intuitive control and enhanced functionality. A 2023 study by a team of researchers from the University of California Irvine explored the viability of creating low-cost cortical stimulators for bi-directional BCI (BD-BCI) research. BD-BCI takes brain-computer-interfaces to the next level with the brain not only providing motor commands to an artificial limb but also allowing it to receive sensory input from such a device. A BIOPAC data acquisition and analysis system was used to validate the charge balancing of subcortical electrocorticographic (ECoG) implants used in a stimulator. The charge balancing test was performed on phantom tissue designed to simulate real brain tissue. The resulting study successfully demonstrated “clinical validation of a fully-programmable electrical stimulator, integrated into an embedded BCI system.”

As researchers continue to refine BCI technologies, the possibilities for real-world applications are boundless. BIOPAC is among the companies on the cutting edge of BCI research, partnering with other innovators to provide the latest in multimodal BCI technologies such as Axon-R. For additional information on Axon-R, check out our recent webinar on the device.

Are you planning to explore the frontiers of BCI in the lab? Our regional customer reps have all the knowledge you need to integrate BIOPAC products into your BCI study.

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