Digital implant allows man with paralysis to walk again

An electronic brain implant that acts as a “digital bridge” between the brain and the spinal cord has enabled a 40-year-old man with chronic tetraplegia to stand and walk on his own.

“We conceived a wireless, digital bridge between the brain and spinal cord that restored natural control over lower limb movements to stand and walk on complex terrains after paralysis due to a spinal cord injury,” the researchers said. “Moreover, neurorehabilitation mediated neurological improvements that persisted even when the bridge was switched off.”

A spinal cord injury disrupts communication between the brain and the region of the spinal cord that controls walking, which then lead to paralysis. [https://apps.who.int/iris/handle/10665/94192; Nat Rev Dis Primer 2017;3:17018]

A group of researchers then worked to restore this communication using a digital bridge between the brain and the spinal cord.

This brain‒spline interface (BSI) consists of fully implanted recording and stimulation systems, which form a direct link between cortical signals and the analogue modulation of epidural electrical stimulation that targets the spinal cord regions involved in the process of walking. [Nature 2018;563:65-71; Nat Med 2022;28:260-271; Nature 2022;611:540-547]

“A highly reliable BSI is calibrated within a few minutes,” the researchers said. “This reliability has remained stable over 1 year, including during independent use at home.”

According to the patient, a Dutch man named Gert-Jan Oskam who sustained a spinal cord injury in a cycling accident 12 years ago, the BSI allowed him natural control over the movements of his legs to stand, walk, climb stairs, and even negotiate complex terrains. BSI-supported neurorehabilitation also improved his neurological recovery. [Nature 2023;618:126-133; https://t.ly/5-Ht]

Notably, Oskam regained his ability to walk with crutches overground even when the BSI was turned off. This digital bridge formed a framework that restored natural control of movement after paralysis.

Digital bridge

The researchers constructed this digital bridge by integrating two fully implanted systems that wirelessly record cortical activity and stimulation of the lumbosacral spinal cord in real time. Two external antennas are also embedded within a personalized headset to ensure reliable coupling with the implants.

The first antenna controls the implanted device through inductive coupling (high frequency, 13.56 MHz). The second, ultrahigh frequency antenna (UHF, 402–405 MHz) transmits electrocorticographic signals to a portable base station and processing unit, which produces online predictions of motor intentions based on these signals.

The decoded motor intentions are then converted into commands that are passed onto tailored software that runs on the same processing unit.

“These commands are delivered to the ACTIVA RC implantable pulse generator, which is commonly used to deliver deep brain stimulation in patients with Parkinson’s disease,” the researchers said. “We upgraded this implant with wireless communication modules that enabled real-time adjustment over the location and timing of epidural electrical stimulation with a latency of about 100 ms.”

Device explantation

A subcutaneous infection to Staphylococcus aureus at the cortical implant led the researchers to explant the device 167 days after implantation, but the second implant showed no sign of infection and remained in place and fully functional.

“After recovery from the surgery and antibiotics treatment … neurorehabilitation and daily use could continue as planned by the protocol,” the researchers said. “Implantation of a new cortical implant was performed on 9 March 2023.”

Notably, it remains unclear whether the device will work in other injury locations and severities since the validation of this digital bridge was restricted to a single person. However, the researchers are positive that this approach will be applicable to other people with paralysis, as suggested by several observations. [J Neural Eng 2021;18:056026; J Neural Eng 2022;19:026021]