Extended home use of an advanced osseointegrated prosthetic arm improves function, performance, and control efficiency.

Objective.Full restoration of arm function using a prosthesis remains a grand challenge; however, advances in robotic hardware, surgical interventions, and machine learning are bringing seamless human-machine interfacing closer to reality.Approach.Through extensive data logging over 1 year, we monitored at-home use of the dexterous Modular Prosthetic Limb controlled through pattern recognition of electromyography (EMG) by an individual with a transhumeral amputation, targeted muscle reinnervation, and osseointegration (OI).Main results.Throughout the study, continuous prosthesis usage increased (1% per week,p< 0.001) and functional metrics improved up to 26% on control assessments and 76% on perceived workload evaluations. We observed increases in torque loading on the OI implant (up to 12.5% every month,p< 0.001) and prosthesis control performance (0.5% every month,p< 0.005), indicating enhanced user integration, acceptance, and proficiency. More importantly, the EMG signal magnitude necessary for prosthesis control decreased, up to 34.7% (p< 0.001), over time without degrading performance, demonstrating improved control efficiency with a machine learning-based myoelectric pattern recognition algorithm. The participant controlled the prosthesis up to one month without updating the pattern recognition algorithm. The participant customized prosthesis movements to perform specific tasks, such as individual finger control for piano playing and hand gestures for communication, which likely contributed to continued usage.Significance.This work demonstrates, in a single participant, the functional benefit of unconstrained use of a highly anthropomorphic prosthetic limb over an extended period. While hurdles remain for widespread use, including device reliability, results replication, and technical maturity beyond a prototype, this study offers insight as an example of the impact of advanced prosthesis technology for rehabilitation outside the laboratory.

Clinical evaluation of the revolutionizing prosthetics modular prosthetic limb system for upper extremity amputees.

Individuals with upper extremity (UE) amputation abandon prostheses due to challenges with significant device weight-particularly among myoelectric prostheses-and limited device dexterity, durability, and reliability among both myoelectric and body-powered prostheses. The Modular Prosthetic Limb (MPL) system couples an advanced UE prosthesis with a pattern recognition paradigm for intuitive, non-invasive prosthetic control. Pattern recognition accuracy and functional assessment-Box & Blocks (BB), Jebsen-Taylor Hand Function Test (JHFT), and Assessment of Capacity for Myoelectric Control (ACMC)-scores comprised the main outcomes. 10 participants were included in analyses, including seven individuals with traumatic amputation, two individuals with congenital limb absence, and one with amputation secondary to malignancy. The average (SD) time since limb loss, excluding congenital participants, was 85.9 (59.5) months. Participants controlled an average of eight motion classes compared to three with their conventional prostheses. All participants made continuous improvements in motion classifier accuracy, pathway completion efficiency, and MPL manipulation. BB and JHFT improvements were not statistically significant. ACMC performance improved for all participants, with mean (SD) scores of 162.6 (105.3), 213.4 (196.2), and 383.2 (154.3), p = 0.02 between the baseline, midpoint, and exit assessments, respectively. Feedback included lengthening the training period to further improve motion classifier accuracy and MPL control. The MPL has potential to restore functionality to individuals with acquired or congenital UE loss.

Individual finger control of a modular prosthetic limb using high-density electrocorticography in a human subject.

OBJECTIVE: We used native sensorimotor representations of fingers in a brain-machine interface (BMI) to achieve immediate online control of individual prosthetic fingers. APPROACH: Using high gamma responses recorded with a high-density electrocorticography (ECoG) array, we rapidly mapped the functional anatomy of cued finger movements. We used these cortical maps to select ECoG electrodes for a hierarchical linear discriminant analysis classification scheme to predict: (1) if any finger was moving, and, if so, (2) which digit was moving. To account for sensory feedback, we also mapped the spatiotemporal activation elicited by vibrotactile stimulation. Finally, we used this prediction framework to provide immediate online control over individual fingers of the Johns Hopkins University Applied Physics Laboratory modular prosthetic limb. MAIN RESULTS: The balanced classification accuracy for detection of movements during the online control session was 92% (chance: 50%). At the onset of movement, finger classification was 76% (chance: 20%), and 88% (chance: 25%) if the pinky and ring finger movements were coupled. Balanced accuracy of fully flexing the cued finger was 64%, and 77% had we combined pinky and ring commands. Offline decoding yielded a peak finger decoding accuracy of 96.5% (chance: 20%) when using an optimized selection of electrodes. Offline analysis demonstrated significant finger-specific activations throughout sensorimotor cortex. Activations either prior to movement onset or during sensory feedback led to discriminable finger control. SIGNIFICANCE: Our results demonstrate the ability of ECoG-based BMIs to leverage the native functional anatomy of sensorimotor cortical populations to immediately control individual finger movements in real time.

Demonstration of a semi-autonomous hybrid brain-machine interface using human intracranial EEG, eye tracking, and computer vision to control a robotic upper limb prosthetic.

To increase the ability of brain-machine interfaces (BMIs) to control advanced prostheses such as the modular prosthetic limb (MPL), we are developing a novel system: the Hybrid Augmented Reality Multimodal Operation Neural Integration Environment (HARMONIE). This system utilizes hybrid input, supervisory control, and intelligent robotics to allow users to identify an object (via eye tracking and computer vision) and initiate (via brain-control) a semi-autonomous reach-grasp-and-drop of the object by the MPL. Sequential iterations of HARMONIE were tested in two pilot subjects implanted with electrocorticographic (ECoG) and depth electrodes within motor areas. The subjects performed the complex task in 71.4% (20/28) and 67.7% (21/31) of trials after minimal training. Balanced accuracy for detecting movements was 91.1% and 92.9%, significantly greater than chance accuracies (p < 0.05). After BMI-based initiation, the MPL completed the entire task 100% (one object) and 70% (three objects) of the time. The MPL took approximately 12.2 s for task completion after system improvements implemented for the second subject. Our hybrid-BMI design prevented all but one baseline false positive from initiating the system. The novel approach demonstrated in this proof-of-principle study, using hybrid input, supervisory control, and intelligent robotics, addresses limitations of current BMIs.

Collaborative approach in the development of high-performance brain-computer interfaces for a neuroprosthetic arm: translation from animal models to human control.

Our research group recently demonstrated that a person with tetraplegia could use a brain-computer interface (BCI) to control a sophisticated anthropomorphic robotic arm with skill and speed approaching that of an able-bodied person. This multiyear study exemplifies important principles in translating research from foundational theory and animal experiments into a clinical study. We present a roadmap that may serve as an example for other areas of clinical device research as well as an update on study results. Prior to conducting a multiyear clinical trial, years of animal research preceded BCI testing in an epilepsy monitoring unit, and then in a short-term (28 days) clinical investigation. Scientists and engineers developed the necessary robotic and surgical hardware, software environment, data analysis techniques, and training paradigms. Coordination among researchers, funding institutes, and regulatory bodies ensured that the study would provide valuable scientific information in a safe environment for the study participant. Finally, clinicians from neurosurgery, anesthesiology, physiatry, psychology, and occupational therapy all worked in a multidisciplinary team along with the other researchers to conduct a multiyear BCI clinical study. This teamwork and coordination can be used as a model for others attempting to translate basic science into real-world clinical situations.

Simultaneous neural control of simple reaching and grasping with the modular prosthetic limb using intracranial EEG.

Intracranial electroencephalographic (iEEG) signals from two human subjects were used to achieve simultaneous neural control of reaching and grasping movements with the Johns Hopkins University Applied Physics Lab (JHU/APL) Modular Prosthetic Limb (MPL), a dexterous robotic prosthetic arm. We performed functional mapping of high gamma activity while the subject made reaching and grasping movements to identify task-selective electrodes. Independent, online control of reaching and grasping was then achieved using high gamma activity from a small subset of electrodes with a model trained on short blocks of reaching and grasping with no further adaptation. Classification accuracy did not decline (p < 0.05, one-way ANOVA) over three blocks of testing in either subject. Mean classification accuracy during independently executed overt reach and grasp movements for (Subject 1, Subject 2) were (0.85, 0.81) and (0.80, 0.96), respectively, and during simultaneous execution they were (0.83, 0.88) and (0.58, 0.88), respectively. Our models leveraged knowledge of the subject's individual functional neuroanatomy for reaching and grasping movements, allowing rapid acquisition of control in a time-sensitive clinical setting. We demonstrate the potential feasibility of verifying functionally meaningful iEEG-based control of the MPL prior to chronic implantation, during which additional capabilities of the MPL might be exploited with further training.

Development of a Human Cranial Bone Surrogate for Impact Studies.

In order to replicate the fracture behavior of the intact human skull under impact it becomes necessary to develop a material having the mechanical properties of cranial bone. The most important properties to replicate in a surrogate human skull were found to be the fracture toughness and tensile strength of the cranial tables as well as the bending strength of the three-layer (inner table-diplöe-outer table) architecture of the human skull. The materials selected to represent the surrogate cranial tables consisted of two different epoxy resins systems with random milled glass fiber to enhance the strength and stiffness and the materials to represent the surrogate diplöe consisted of three low density foams. Forty-one three-point bending fracture toughness tests were performed on nine material combinations. The materials that best represented the fracture toughness of cranial tables were then selected and formed into tensile samples and tested. These materials were then used with the two surrogate diplöe foam materials to create the three-layer surrogate cranial bone samples for three-point bending tests. Drop tower tests were performed on flat samples created from these materials and the fracture patterns were very similar to the linear fractures in pendulum impacts of intact human skulls, previously reported in the literature. The surrogate cranial tables had the quasi-static fracture toughness and tensile strength of 2.5 MPa√ m and 53 ± 4.9 MPa, respectively, while the same properties of human compact bone were 3.1 ± 1.8 MPa√ m and 68 ± 18 MPa, respectively. The cranial surrogate had a quasi-static bending strength of 68 ± 5.7 MPa, while that of cranial bone was 82 ± 26 MPa. This material/design is currently being used to construct spherical shell samples for drop tower and ballistic tests.

Versatile synthesis and micropatterning of nonfouling polymer brushes on the wafer scale.

In this article, the authors describe new approaches to synthesize and pattern surfaces with poly[oligo(ethylene glycol) methyl methacrylate] (POEGMA) polymer brushes synthesized by surface-initiated atom transfer radical polymerization. These patterned coatings confer "nonfouling" properties protein and cell resistance-to the surface in a biological milieu. The versatile routes for the synthesis of POEGMA demonstrated here offer clear advantages over other techniques previously used in terms of their simplicity, reliability, and ability to pattern large-area substrates. They also demonstrate that POEGMA polymer brushes can be patterned directly by photolithography, plasma ashing, and reactive ion etching to create patterns at the micro- and nanoscale over large areas with high throughput and repeatability, while preserving the protein and cell resistance of the POEGMA brush.

Three-dimensional parallel holographic micropatterning using a spatial light modulator.

We present a micropatterning method for the automatic transfer and arbitrary positioning of computer-generated three-dimensional structures within a substrate. The Gerchberg-Saxton algorithm and an electrically addressed spatial light modulator (SLM) are used to create and display phase holograms, respectively. A holographic approach to light manipulation enables arbitrary and efficient parallel photo-patterning. Multiple pyramidal microstructures were created simultaneously in a photosensitive adhesive. A scanning electron microscope was used to confirm successful replication of the desired microscale structures.

Biocatalytic microcontact printing.

Immobilized biocatalytic lithography is presented as an application of soft lithography. In traditional microcontact printing, diffusion limits resolution of pattern transfer. By using an immobilized catalyst, the lateral resolution of microcontact printing would depend only on the length and flexibility of the tether (<2 nm) as opposed to diffusion (>100 nm). In the work, exonuclease reversibly immobilized on a relief-patterned stamp is used to ablate ssDNA monolayers Percent of ablation was determined via confocal fluorescence microscopy to be approximately 70%.