A benchtop system to assess the feasibility of a fully independent and implantable brain-machine interface
Po T. WangEverardo CamachoMing WangYongcheng LiSusan J. ShawMichelle ArmacostHui GongDaniel R. KramerBrian LeeRichard A. AndersenCharles Y. LiuPayam HeydariZoran NenadicAn H
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Abstract:
State-of-the-art invasive brain-machine interfaces (BMIs) have shown significant promise, but rely on external electronics and wired connections between the brain and these external components. This configuration presents health risks and limits practical use. These limitations can be addressed by designing a fully implantable BMI similar to existing FDA-approved implantable devices. Here, a prototype BMI system whose size and power consumption are comparable to those of fully implantable medical devices was designed and implemented, and its performance was tested at the benchtop and bedside.A prototype of a fully implantable BMI system was designed and implemented as a miniaturized embedded system. This benchtop analogue was tested in its ability to acquire signals, train a decoder, perform online decoding, wirelessly control external devices, and operate independently on battery. Furthermore, performance metrics such as power consumption were benchmarked.An analogue of a fully implantable BMI was fabricated with a miniaturized form factor. A patient undergoing epilepsy surgery evaluation with an electrocorticogram (ECoG) grid implanted over the primary motor cortex was recruited to operate the system. Seven online runs were performed with an average binary state decoding accuracy of 87.0% (lag optimized, or 85.0% at fixed latency). The system was powered by a wirelessly rechargeable battery, consumed ∼150 mW, and operated for >60 h on a single battery cycle.The BMI analogue achieved immediate and accurate decoding of ECoG signals underlying hand movements. A wirelessly rechargeable battery and other supporting functions allowed the system to function independently. In addition to the small footprint and acceptable power and heat dissipation, these results suggest that fully implantable BMI systems are feasible.Keywords:
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Motor Imagery
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Assistive technology control interface theory describes interface activation and interface deactivation as distinct properties of any control interface. Separating control of activation and deactivation allows precise timing of the duration of the activation. Objective. We propose a novel P300 brain-computer interface (BCI) functionality with separate control of the initial activation and the deactivation (hold-release) of a selection. Approach. Using two different layouts and off-line analysis, we tested the accuracy with which subjects could (1) hold their selection and (2) quickly change between selections. Main results. Mean accuracy across all subjects for the hold-release algorithm was 85% with one hold-release classification and 100% with two hold-release classifications. Using a layout designed to lower perceptual errors, accuracy increased to a mean of 90% and the time subjects could hold a selection was 40% longer than with the standard layout. Hold-release functionality provides improved response time (6-16 times faster) over the initial P300 BCI selection by allowing the BCI to make hold-release decisions from very few flashes instead of after multiple sequences of flashes. Significance. For the BCI user, hold-release functionality allows for faster, more continuous control with a P300 BCI, creating new options for BCI applications.
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The P300-based brain-computer interface (P300 BCI) is currently a very popular topic in assistive technology development. However, only a few simple P300 BCI-based games have been designed so far. Here, we analyze the shortcomings of this BCI in gaming applications and show that solutions for overcoming them already exist, although these techniques are dispersed over several different games. Additionally, new approaches to improve the P300 BCI accuracy and flexibility are currently being proposed in the more general P300 BCI research. The P300 BCI, even in its current form, not only exhibits relatively high speed and accuracy, but also can be used without user training, after a short calibration. Taking these facts together, the broader use of the P300 BCI in BCI-controlled video games is recommended.
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