Decoding dexterous finger movements in a neural prosthesis model approaching real-world conditions

The future of upper extremity rehabilitation robotics: research and practice

The loss of upper limb motor function can have a devastating effect on people's lives. To restore upper limb control and functionality, researchers and clinicians have developed interfaces to interact directly with the human body's motor system. In this invited review, we aim to provide details on the peripheral nerve interfaces and brain-machine interfaces that have been developed in the past 30 years for upper extremity control, and we highlight the challenges that still remain to transition the technology into the clinical market. The findings show that peripheral nerve interfaces and brain-machine interfaces have many similar characteristics that enable them to be concurrently developed. Decoding neural information from both interfaces may lead to novel physiological models that may one day fully restore upper limb motor function for a growing patient population.

Robust tactile sensory responses in finger area of primate motor cortex relevant to prosthetic control

OBJECTIVE

Challenges in improving the performance of dexterous upper-limb brain-machine interfaces (BMIs) have prompted renewed interest in quantifying the amount and type of sensory information naturally encoded in the primary motor cortex (M1). Previous single unit studies in monkeys showed M1 is responsive to tactile stimulation, as well as passive and active movement of the limbs. However, recent work in this area has focused primarily on proprioception. Here we examined instead how tactile somatosensation of the hand and fingers is represented in M1.

APPROACH

We recorded multi- and single units and thresholded neural activity from macaque M1 while gently brushing individual finger pads at 2 Hz. We also recorded broadband neural activity from electrocorticogram (ECoG) grids placed on human motor cortex, while applying the same tactile stimulus.

MAIN RESULTS

Units displaying significant differences in firing rates between individual fingers (p  <  0.05) represented up to 76.7% of sorted multiunits across four monkeys. After normalizing by the number of channels with significant motor finger responses, the percentage of electrodes with significant tactile responses was 74.9%  ±  24.7%. No somatotopic organization of finger preference was obvious across cortex, but many units exhibited cosine-like tuning across multiple digits. Sufficient sensory information was present in M1 to correctly decode stimulus position from multiunit activity above chance levels in all monkeys, and also from ECoG gamma power in two human subjects.

SIGNIFICANCE

These results provide some explanation for difficulties experienced by motor decoders in clinical trials of cortically controlled prosthetic hands, as well as the general problem of disentangling motor and sensory signals in primate motor cortex during dextrous tasks. Additionally, examination of unit tuning during tactile and proprioceptive inputs indicates cells are often tuned differently in different contexts, reinforcing the need for continued refinement of BMI training and decoding approaches to closed-loop BMI systems for dexterous grasping.

Neural control of finger movement via intracortical brain-machine interface

OBJECTIVE

Intracortical brain-machine interfaces (BMIs) are a promising source of prosthesis control signals for individuals with severe motor disabilities. Previous BMI studies have primarily focused on predicting and controlling whole-arm movements; precise control of hand kinematics, however, has not been fully demonstrated. Here, we investigate the continuous decoding of precise finger movements in rhesus macaques.

APPROACH

In order to elicit precise and repeatable finger movements, we have developed a novel behavioral task paradigm which requires the subject to acquire virtual fingertip position targets. In the physical control condition, four rhesus macaques performed this task by moving all four fingers together in order to acquire a single target. This movement was equivalent to controlling the aperture of a power grasp. During this task performance, we recorded neural spikes from intracortical electrode arrays in primary motor cortex.

MAIN RESULTS

Using a standard Kalman filter, we could reconstruct continuous finger movement offline with an average correlation of ρ  =  0.78 between actual and predicted position across four rhesus macaques. For two of the monkeys, this movement prediction was performed in real-time to enable direct brain control of the virtual hand. Compared to physical control, neural control performance was slightly degraded; however, the monkeys were still able to successfully perform the task with an average target acquisition rate of 83.1%. The monkeys' ability to arbitrarily specify fingertip position was also quantified using an information throughput metric. During brain control task performance, the monkeys achieved an average 1.01 bits s-1 throughput, similar to that achieved in previous studies which decoded upper-arm movements to control computer cursors using a standard Kalman filter.

SIGNIFICANCE

This is, to our knowledge, the first demonstration of brain control of finger-level fine motor skills. We believe that these results represent an important step towards full and dexterous control of neural prosthetic devices.

Robust Wireless Power Transmission to mm-Sized Free-Floating Distributed Implants

This paper presents an inductive link for wireless power transmission (WPT) to mm-sized free-floating implants (FFIs) distributed in a large three-dimensional space in the neural tissue that is insensitive to the exact location of the receiver (Rx). The proposed structure utilizes a high-Q resonator on the target wirelessly powered plane that encompasses randomly positioned multiple FFIs, all powered by a large external transmitter (Tx). Based on resonant WPT fundamentals, we have devised a detailed method for optimization of the FFIs and explored design strategies and safety concerns, such as coil segmentation and specific absorption rate limits using realistic finite element simulation models in HFSS including head tissue layers, respectively. We have built several FFI prototypes to conduct accurate measurements and to characterize the performance of the proposed WPT method. Measurement results on 1-mm receivers operating at 60 MHz show power transfer efficiency and power delivered to the load at 2.4% and 1.3 mW, respectively, within 14-18 mm of Tx-Rx separation and 7 cm² of brain surface.

Restoring motor control and sensory feedback in people with upper extremity amputations using arrays of 96 microelectrodes implanted in the median and ulnar nerves

OBJECTIVE

An important goal of neuroprosthetic research is to establish bidirectional communication between the user and new prosthetic limbs that are capable of controlling >20 different movements. One strategy for achieving this goal is to interface the prosthetic limb directly with efferent and afferent fibres in the peripheral nervous system using an array of intrafascicular microelectrodes. This approach would provide access to a large number of independent neural pathways for controlling high degree-of-freedom prosthetic limbs, as well as evoking multiple-complex sensory percepts.

APPROACH

Utah Slanted Electrode Arrays (USEAs, 96 recording/stimulating electrodes) were implanted for 30 days into the median (Subject 1-M, 31 years post-amputation) or ulnar (Subject 2-U, 1.5 years post-amputation) nerves of two amputees. Neural activity was recorded during intended movements of the subject's phantom fingers and a linear Kalman filter was used to decode the neural data. Microelectrode stimulation of varying amplitudes and frequencies was delivered via single or multiple electrodes to investigate the number, size and quality of sensory percepts that could be evoked. Device performance over time was assessed by measuring: electrode impedances, signal-to-noise ratios (SNRs), stimulation thresholds, number and stability of evoked percepts.

MAIN RESULTS

The subjects were able to proportionally, control individual fingers of a virtual robotic hand, with 13 different movements decoded offline (r = 0.48) and two movements decoded online. Electrical stimulation across one USEA evoked >80 sensory percepts. Varying the stimulation parameters modulated percept quality. Devices remained intrafascicularly implanted for the duration of the study with no significant changes in the SNRs or percept thresholds.

SIGNIFICANCE

This study demonstrated that an array of 96 microelectrodes can be implanted into the human peripheral nervous system for up to 1 month durations. Such an array could provide intuitive control of a virtual prosthetic hand with broad sensory feedback.

Restoring sensorimotor function through intracortical interfaces: progress and looming challenges

The loss of a limb or paralysis resulting from spinal cord injury has devastating consequences on quality of life. One approach to restoring lost sensory and motor abilities in amputees and patients with tetraplegia is to supply them with implants that provide a direct interface with the CNS. Such brain-machine interfaces might enable a patient to exert voluntary control over a prosthetic or robotic limb or over the electrically induced contractions of paralysed muscles. A parallel interface could convey sensory information about the consequences of these movements back to the patient. Recent developments in the algorithms that decode motor intention from neuronal activity and in approaches to convey sensory feedback by electrically stimulating neurons, using biomimetic and adaptation-based approaches, have shown the promise of invasive interfaces with sensorimotor cortices, although substantial challenges remain.