First-in-human implementation of a bidirectional somatosensory neuroprosthetic system with wireless communication

Abstract

Background: Limitations in upper limb prosthesis function and lack of sensory feedback are major contributors to high prosthesis abandonment rates. Peripheral nerve stimulation and intramuscular recording can restore touch and relay motor intentions for individuals with upper limb loss. Percutaneous systems have enabled significant progress in implanted neural interfaces but require chronic lead maintenance and unwieldy external equipment. Fully implanted sensorimotor systems without percutaneous leads are crucial for advancing implanted neuroprosthetic technologies to long-term community use and commercialization.

Methods: We present the first-in-human technical performance of the implanted Somatosensory Electrical Neurostimulation and Sensing (iSens®) system-an implanted, high-channel count myoelectric sensing and nerve stimulation system that uses wireless communication for advanced prosthetic systems. Two individuals with unilateral transradial amputations received iSens® with four 16-channel composite Flat Interface Nerve Electrodes (C-FINEs) and four Tetra Intramuscular (TIM) electrodes. This study achieved two key objectives to demonstrate system feasibility prior to long-term community use: (1) evaluating the chronic stability of extraneural cuff electrodes, intramuscular electrodes, and active implantable devices in a wirelessly connected system and (2) assessing the impacts of peripheral nerve stimulation on three degree-of-freedom controller performance in a wirelessly connected system to validate iSens® as a bidirectional interface.

Results: Similar to prior percutaneous systems, we demonstrate chronically stable extraneural cuff electrodes and intramuscular electrodes in a wirelessly connected implanted system for more than two years in one participant and four months in the second participant, whose iSens® system was explanted due to an infection of unknown origin. Using an artificial neural network controller trained on implanted electromyographic data collected during known hand movements, one participant commanded a virtual hand and sensorized prosthesis in 3 degrees-of-freedom. The iSens® system simultaneously produced stimulation for sensation while recording high resolution muscle activity for real-time control. Although restored sensation did not significantly improve initial trials of prosthetic controller performance, the participant reported that sensation was helpful for functional tasks.

Conclusions: This case series describes a wirelessly connected, bidirectional neuroprosthetic system with somatosensory feedback and advanced myoelectric prosthetic control that is ready for implementation in long-term home use clinical trials.

Trial registration: ClinicalTrials.gov ID: NCT04430218, 2020-06-30.

Keywords: Implanted neural interfaces; Intramuscular electrodes; Myoelectric control; Neuroprosthesis; Peripheral nerve stimulation; Upper limb loss; Wireless communication.

Fig. 1

iSens® system implanted and external components. (Left) Overview of the iSens® system implanted components. The system can support up to four Smart Leads, but only two are shown. In the example illustration, the INC powers and enables communication to one Smart Stim Lead and one Smart Sense Lead via a bifurcated lead. The Smart Stim Lead connects to two 16 C-FINEs, and the Smart Sense Lead connects to two TIMs. (Right) External system components consist of a BLE-connected Hub with wired connections to a phone and advanced prosthesis with sensors

Fig. 2

iSens® X-rays. X-rays showing iSens® implanted components in a S01 and b S02. To improve lead organization compared to S01’s original surgery, implanted device components and connectors in S02’s system were deliberately routed along the same direction, and excess lead length was intentionally organized to reduce bulk

Fig. 3

Active implantable device communication across time. Successful and unsuccessful communication at each encounter for S01 (top) and S02 (bottom). Wireless communication between the Hub and INC was confirmed by successful reception of BLE RSSI and battery level information by the Hub. Wired communication between the INC and each Smart Lead was confirmed by successful discovery of each Smart lead as shown in the Hub user interface. One Smart Stim Lead in S01 was disconnected and left unpowered during the revision surgery due to surgical risks associated with replacing the module

Fig. 4

Threshold charge and tissue resistance across time. a Perceptual threshold charge and b tissue resistance across time for each C-FINE. Box charts represent the distribution of threshold and resistance values across all contacts per C-FINE within each visit, and solid lines represent the fit linear regression model across all time points

Fig. 5

iSens®-elicited sensory locations. Somatosensory locations, excluding proprioception-only percepts, elicited with iSens® during two testing sessions for a S01 and b S02. All locations were drawn at threshold perception. c Location similarity across all combinations of experimental sessions per C-FINE contact, grouped by C-FINE. A higher Jaccard similarity indicates more instances of overlapped pixels between location drawings from multiple sessions, suggesting stable locations. A Jaccard similarity of 1 represents two perfectly overlapped location drawings, and a Jaccard similarity of 0 represents no overlap. Jaccard similarities greater than 0 but less than 1 indicate that the two locations are in similar areas but vary in terms of the center position and area size. Significance: * represents p < 0.05, and ** represents p < 0.01

Fig. 6

Percent of percepts reported on the hand and categorized quality descriptors across time. a Percent of contacts per C-FINE evoking percepts located in the hand, distal to the wrist, across time for S01 (left) and S02 (right), excluding proprioception-only percepts. b Percent of all C-FINE contacts evoking tactile, proprioceptive, and pain quality descriptors as reported by S01 (left) and S02 (right) across time. Participants could report an unlimited number of quality descriptors, so the total percentage reported across all quality descriptor categories does not sum to 100%

Fig. 7

EMG channel crosstalk across time. Mean EMG channel cross correlation per Smart Sense Lead, from eight channels, across time in a S01 and b S02

Fig. 8

Intramuscular EMG channel performance. Examples of raw EMG and computed WFL recorded while participants move to 18 postures, with and without 70 Hz single contact stimulation via the proximal median (pM) nerve C-FINEs. a Example EMG channel that displayed low noise and clear amplitude modulations during rest and movement phases, regardless of stimulation. b Example EMG channel that showed increased EMG signal power with stimulation throughout all moments in time and at all frequencies. c Example EMG channel that showed increased noise at the stimulation frequency and harmonics through the trial. d Categorization of intramuscular EMG recording performance for each participant

Fig. 9

Virtual environment myoelectric control posture matching using iSens® and a 3 DOF ANN controller. a S01’s time-to-target to match postures presented on a monitor screen, with and without stimulation. Each target posture was presented three times for each condition. b S01’s path efficiency while attempting to move to each posture, with and without stimulation

Fig. 10

Activities of daily living functional performance using iSens® and an advanced prosthesis with sensors. a AM-ULA summary score for each condition. The AM-ULA was repeated three times per condition, with and without stimulation. b Survey rating mean and standard deviation for survey questions reported after each task in the AM-ULA, with and without stimulation