You Will Grasp Again: A Direct Spinal Cord/Computer Interface with the Spared Motor Neurons Restores the Dexterous Control of the Paralyzed Hand after Chronic Spinal Cord Injury

Abstract

The paralysis of the muscles controlling the hand dramatically limits the quality of life of individuals living with spinal cord injury (SCI). Here, we present a non-invasive neural interface technology that will change the lives of individuals living with cervical SCI (C4-C6). We demonstrate that eight motor- and sensory-complete SCI individuals (C5-C6, n = 7; C4, n = 1) are still able to task-modulate in real-time the activity of populations of spinal motor neurons with spared corticospinal pathways. In all tested patients, we identified groups of motor units under voluntary control that encoded a variety of hand movements. The motor unit discharges were mapped into more than 10 degrees of freedom, ranging from grasping to individual hand digit flexions and extensions. We then mapped the neural dynamics into a real-time controlled virtual hand. The patients were able to match the cue hand posture by proportionally controlling four degrees of freedom (opening and closing the hand and index flexion/extension). These results demonstrate that wearable muscle sensors provide access to voluntarily controlled neural activity in complete cervical SCI individuals.

Sensing the Full Dynamics of the Human Hand with a Neural Interface and Deep Learning

“…The two groups mentioned before are very similar as they both output the kinematic signal that the sEMG encoded and not predefined classes. Their main distinction is that one does it discreetly [11], [12] while the other continuously [14]–[16], [18]–[26], [28]–[30], [38]. From our review, it appears that the discrete version has not been explored much as it is subject to the same problem we found for gesture recognition.…”

“…We believe that 14 DoFs are the minimum, as these are all the flexion/extension DoFs that the hand has and are sufficient to perform different types of grasping while still being useful enough even if fine-tuning through abduction and adduction is not given. Surprisingly a large number of previous works [14], [15], [19], [21]–[26], [28]–[30], [38] fall through because of this criterion and we are left with only a few contenders.…”

“…Before investigating the other two groups that do allow the user to influence the speed of movement we need to understand something that is arbitrarily decided in almost all works -how do we encode kinematics in the first place? There are two ways of doing this in the literature: defining the joints of the hand as 3D points in Cartesian space [13] or calculating the angles between said joints [14]- [16], [18]- [26], [28]- [30], [38]. Just from the citations we listed it can be seen that there is an unbalance and clear preference for using the joint angles representation (Fig.…”

“…There have been numerous relevant attempts trying to fill this specific need [6]- [37] by exploiting the EMG signals to reconstruct the movement intent, yet all have some limitations that hinder the access to the large number of degrees of freedom from the human hand. We will delve into the shortcomings of these works later in the discussion section, but for now, here is a brief overview of the limitations of current sEMG decoding systems: 1) errors that are too big for some or all of the fingers [13]- [16], [18], [20]- [23], [25], [26], [38], 2) achieving less than 14 degrees of freedom (DoF) that the hand needs for executing flexion and extension movements [14], [15], [19], [21]- [26], [28]- [30], [38], and 3) or not attempting unseen combinations of different movements [13]- [16], [18]- [26], [28], [29], [31], [38].…”

NeurOne: High-performance Motor Unit-Computer Interface for the Paralyzed

“…Ting et al demonstrated that an individual with motor complete SCI still had functional motor neurons that can be extracted through the decomposition of HD-sEMG signals (20, 21). Similarly, we found unique motor units in eight motor complete SCI patients with a lesion at level C5-C6 who attempted predetermined hand movements (22). These patients were also able to track a visual cue on a monitor by modulating the discharge rate of the identified motor units in real-time (22).…”