Abstract
Brain–machine interfaces (BMIs) are promising devices that can be used as neuroprostheses by severely disabled individuals. Brain surface electroencephalograms (electrocorticograms, ECoGs) can provide input signals that can then be decoded to enable communication with others and to control intelligent prostheses and home electronics. However, conventional systems use wired ECoG recordings. Therefore, the development of wireless systems for clinical ECoG BMIs is a major goal in the field. We developed a fully implantable ECoG signal recording device for human ECoG BMI, i.e., a wireless human ECoG-based real-time BMI system (W-HERBS). In this system, three-dimensional (3D) high-density subdural multiple electrodes are fitted to the brain surface and ECoG measurement units record 128-channel (ch) ECoG signals at a sampling rate of 1 kHz. The units transfer data to the data and power management unit implanted subcutaneously in the abdomen through a subcutaneous stretchable spiral cable. The data and power management unit then communicates with a workstation outside the body and wirelessly receives 400 mW of power from an external wireless transmitter. The workstation records and analyzes the received data in the frequency domain and controls external devices based on analyses. We investigated the performance of the proposed system. We were able to use W-HERBS to detect sine waves with a 4.8-μV amplitude and a 60–200-Hz bandwidth from the ECoG BMIs. W-HERBS is the first fully implantable ECoG-based BMI system with more than 100 ch. It is capable of recording 128-ch subdural ECoG signals with sufficient input-referred noise (3 μVrms) and with an acceptable time delay (250 ms). The system contributes to the clinical application of high-performance BMIs and to experimental brain research.
Highlights
Multiple diseases and symptomatic states lead to the loss of muscular control without disruption of the patient’s cognitive ability
ECoG recording is commonly used in medical treatments for intractable epilepsy, and recent studies have demonstrated the decoding of arm trajectories (Pistohl et al, 2008; Schalk et al, 2008; Nakanishi et al, 2013; Bundy et al, 2016) and finger movements (Scherer et al, 2009; Nakanishi et al, 2014) using human ECoG signals
wireless human ECoG-based real-time BMI system (W-HERBS) is regarded as the first fully implantable ECoG Brain–machine interfaces (BMIs) system able to detect high gamma bandwidth signals at 4.8-μV amplitude and control motor movements based on data analyses
Summary
Multiple diseases and symptomatic states lead to the loss of muscular control without disruption of the patient’s cognitive ability. We focused on real-time robot arm control achieved using ECoG-based BMIs (Yanagisawa et al, 2009, 2011, 2012) and the development of a fully implantable wireless recording device (Hirata et al, 2011) in this study. The 3D high-density multiple electrodes used here are precisely fitted to the cerebral cortex and stably record subdural ECoGs from target cerebral areas (Morris et al, 2015) These electrode arrays can maintain contact with the entire area of the hand motor cortex (approximately 20 mm × 20 mm) with 2.5-mm inter-electrode spacing and provide sufficient information for hand movement assistance in real-time. W-HERBS is regarded as the first fully implantable ECoG BMI system able to detect high gamma bandwidth signals at 4.8-μV amplitude and control motor movements based on data analyses. Our third prototype will have fixed basic electrical components and arrangements, and a preset shape for the titanium casing, which would in turn allow the use of such hermetic seals
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