Home Use of a Wireless Intracortical Brain-Computer Interface by Individuals With Tetraplegia

Abstract

Individuals with neurological disease or injury such as amyotrophic lateral sclerosis, spinal cord injury or stroke may become tetraplegic, unable to speak or even locked-in. For people with these conditions, current assistive technologies are often ineffective. Brain-computer interfaces are being developed to enhance independence and restore communication in the absence of physical movement. Over the past decade, individuals with tetraplegia have achieved rapid on-screen typing and point-andclick control of tablet apps using intracortical brain-computer interfaces (iBCIs) that decode intended arm and hand movements from neural signals recorded by implanted microelectrode arrays. However, cables used to convey neural signals from the brain tether participants to amplifiers and decoding computers and require expert oversight during use, severely limiting when and where iBCIs could be available for use. Here, we demonstrate the first human use of a wireless broadband iBCI. Based on a prototype system previously used in pre-clinical research, we replaced the external cables of a 192-electrode iBCI with wireless transmitters and achieved high-resolution recording and decoding of broadband field potentials and spiking activity from people with paralysis. Two participants in an ongoing pilot clinical trial performed on-screen item selection tasks to assess iBCI-enabled cursor control. Communication bitrates were equivalent between cabled and wireless configurations. Participants also used the wireless iBCI to control a standard commercial tablet computer to browse the web and use several mobile applications. Within-day comparison of cabled and wireless interfaces evaluated bit error rate, packet loss, and the recovery of spike rates and spike waveforms from the recorded neural signals. In a representative use case, the wireless system recorded intracortical signals from two arrays in one participant continuously through a 24-hour period at home. Wireless multi-electrode recording of broadband neural signals over extended periods introduces a valuable tool for human neuroscience research and is an important step toward practical deployment of iBCI technology for independent use by individuals with paralysis. On-demand access to highperformance iBCI technology in the home promises to enhance independence and restore communication and mobility for individuals with severe motor impairment. 1

Brain–Machine Interfaces: Closed-Loop Control in an Adaptive System

“…Some of the most important advances may come not from optimizing the BMI per se but from optimizing the usefulness of the computer or machine being controlled. For example, enabling patients to use a tablet computer (6) or making BMIs more portable (47,(163)(164)(165) can have as much (or more) impact on quality of life as increasing decoder performance by a few percent. For some tasks, BMIs already perform similarly to other human-computer interfaces: Controlling a cursor to type on a screen resembles using a video-game controller to do the same.…”

“…Some BMIs leverage this by including spike sorting in the signal-processing pipeline, a source separation method that assigns each spiking event to a specific neuron. Decoding from sorted spikes is common (e.g., 13,47). However, cortical BMIs based on isolated single neurons suffer from recording instability (e.g., 48,49).…”

Ultra Low Power, Event-Driven Data Compression of Multi-Unit Activity

“…In that case the ring rate codeword is unnecessary as the decoder can assume all received channel has the ring rate of 1. An example of the encoding without lossless compression, with n = 4, k 1 = 2 and m 2 = 2, is given by: 0001 0100 1011 is shows that channel 1 (00) had a FR of 2 events (01) in the bin, channel 2 (01) had FR = 1 (00), channel 3 (10) had FR = 4 (11), and channel 4 had a FR = 0 (absent). In this work, this encoding was named the explicit event-driven (EED) encoding because the FR per channel is explicitly encoded in the m 2 -length codeword that follows the channel ID.…”

“…Wireless iBMIs (WI-BMI) consist of a small implant in the brain that communicates wirelessly with an external decoder, where more computationally demanding processing and/or decoding is performed. e nature of the wireless channel can be either acoustic with ultrasound [6], or electromagnetic with Radio Frequency (RF) waves, where the la er is more common [4,[7][8][9][10][11][12]. e bene t of WI-BMIs is that they eliminate physical percutaneous connections (wires breaching the skin) and the associated risks (infection, mechanical damage, etc), while signi cantly improving the quality of life of the user.…”