Human-to-human closed-loop control based on brain-to-brain interface and muscle-to-muscle interface

Abstract

Novel communication techniques have always been fascinating for humankind. This pilot study presents an approach to human interaction by combining direct brain-to-brain interface (BBI) and muscle-to-muscle interface (MMI) in a closed-loop pattern. In this system, artificial paths (data flows) functionally connect natural paths (nerves). The intention from one subject (sender) is recognized using electroencephalography (EEG) based brain-computer interface (BCI), which is sent out to trigger transcranial magnetic stimulation (TMS) on the other subject (receiver) and induce hand motion; meanwhile TMS results in a significant change on the motor evoked potentials (MEP) recorded by electromyography (EMG) of the receiver’s arm, which triggers functional electrical stimulation (FES) applied to the sender’s arm and generates hand motion. Human-controlled loop and automatic control loop experiments were performed with 6 pairs of healthy subjects to evaluate the performance of the introduced mechanism. The results indicated that response accuracy during human-controlled experiments was 85% which demonstrates the feasibility of the proposed method. During the automatic control test, two subjects could accomplish repetitive and reciprocal hand motion control up to 85 times consecutively.

Integrating information in the brain’s EM field: the cemi field theory of consciousness

“…Many of the predictions of the cemi field theory, such as that appropriately structured external EM fields will influence neural firing patterns and thoughts, have already been confirmed, as described above. The recent development of brain–computer interfaces ( Mashat et al 2017 ; Lazarou et al 2018 ; Nuyujukian et al 2018 ) that measure EEG signals and analyse those signals to generate limb motor outputs via TMS, effectively operates the same informational loop from neuron to neuron via the brain’s EM fields, as is proposed in the cemi field theory. Patients trained to use these devices experience EM field mediated motor control as their conscious actions.…”

Increasing Human Performance by Sharing Cognitive Load Using Brain-to-Brain Interface

“…The brain-to-brain interaction was also implemented in the form of human-animal interaction (Yoo et al, 2013), where the human volunteer's intention was translated to stimulate a rat's brain motor area responsible for the tail movement. Another type of BBI was demonstrated by Mashat et al (2017) in a closed-loop form, where the intention signal from a sender was recognized using EEG and sent out to trigger TMS of a receiver to induce hand motion; meanwhile, TMS resulted in a significant change in the motor evoked potentials recorded by electromyography of the receiver's arm, which triggered functional electrical stimulation applied to the sender's arm and generated hand motion.…”

Direct Communication Between Brains: A Systematic PRISMA Review of Brain-To-Brain Interface

“…MI EEG also functioned as a direct translation, where the imagined movement of a hand corresponded to a similar action on the receiving end (right hand movement begets right turn, etc.) in Yu et al (2014), Mashat et al (2017), Lee et al (2017), andZhang et al (2019). SSVEP EEG was applied in similar ways, with Stocco et al (2015) using the visually evoked potentials to create a simple binary signal (subject focusing on one flashing LED or another) while Li and Zhang (2016) and Koo et al (2017) used flashing LEDs on the left and right of a screen that corresponded to left and right movement of the receiver.…”

“…While these applications still only apply binary information transfer, they show more complex applications of such communication. Mashat et al (2017) created a B2BI system more focused on rehabilitation for patients. By combining a B2BI with functional electrical stimulation (FES), they argued that systems like this could allow more advanced physical therapy.…”