Advanced technologies for intuitive control and sensation of prosthetics

Unveiling EMG semantics: a prototype-learning approach to generalizable gesture classification

Objective.Upper limb loss can profoundly impact an individual's quality of life, posing challenges to both physical capabilities and emotional well-being. To restore limb function by decoding electromyography (EMG) signals, in this paper, we present a novel deep prototype learning method for accurate and generalizable EMG-based gesture classification. Existing methods suffer from limitations in generalization across subjects due to the diverse nature of individual muscle responses, impeding seamless applicability in broader populations.Approach.By leveraging deep prototype learning, we introduce a method that goes beyond direct output prediction. Instead, it matches new EMG inputs to a set of learned prototypes and predicts the corresponding labels.Main results.This novel methodology significantly enhances the model's classification performance and generalizability by discriminating subtle differences between gestures, making it more reliable and precise in real-world applications. Our experiments on four Ninapro datasets suggest that our deep prototype learning classifier outperforms state-of-the-art methods in terms of intra-subject and inter-subject classification accuracy in gesture prediction.Significance.The results from our experiments validate the effectiveness of the proposed method and pave the way for future advancements in the field of EMG gesture classification for upper limb prosthetics.

Recent Advances in Biomimetics for the Development of Bio-Inspired Prosthetic Limbs

Recent advancements in biomimetics have spurred significant innovations in prosthetic limb development by leveraging the intricate designs and mechanisms found in nature. Biomimetics, also known as "nature-inspired engineering", involves studying and emulating biological systems to address complex human challenges. This comprehensive review provides insights into the latest trends in biomimetic prosthetics, focusing on leveraging knowledge from natural biomechanics, sensory feedback mechanisms, and control systems to closely mimic biological appendages. Highlighted breakthroughs include the integration of cutting-edge materials and manufacturing techniques such as 3D printing, facilitating seamless anatomical integration of prosthetic limbs. Additionally, the incorporation of neural interfaces and sensory feedback systems enhances control and movement, while technologies like 3D scanning enable personalized customization, optimizing comfort and functionality for individual users. Ongoing research efforts in biomimetics hold promise for further advancements, offering enhanced mobility and integration for individuals with limb loss or impairment. This review illuminates the dynamic landscape of biomimetic prosthetic technology, emphasizing its transformative potential in rehabilitation and assistive technologies. It envisions a future where prosthetic solutions seamlessly integrate with the human body, augmenting both mobility and quality of life.

Clinical outcomes of peripheral nerve interfaces for rehabilitation in paralysis and amputation: a literature review

Peripheral nerve interfaces (PNIs) are electrical systems designed to integrate with peripheral nerves in patients, such as following central nervous system (CNS) injuries to augment or replace CNS control and restore function. We review the literature for clinical trials and studies containing clinical outcome measures to explore the utility of human applications of PNIs. We discuss the various types of electrodes currently used for PNI systems and their functionalities and limitations. We discuss important design characteristics of PNI systems, including biocompatibility, resolution and specificity, efficacy, and longevity, to highlight their importance in the current and future development of PNIs. The clinical outcomes of PNI systems are also discussed. Finally, we review relevant PNI clinical trials that were conducted, up to the present date, to restore the sensory and motor function of upper or lower limbs in amputees, spinal cord injury patients, or intact individuals and describe their significant findings. This review highlights the current progress in the field of PNIs and serves as a foundation for future development and application of PNI systems.

Toward the Development of User-Centered Neurointegrated Lower Limb Prostheses

The last few years witnessed radical improvements in lower-limb prostheses. Researchers have presented innovative solutions to overcome the limits of the first generation of prostheses, refining specific aspects which could be implemented in future prostheses designs. Each aspect of lower-limb prostheses has been upgraded, but despite these advances, a number of deficiencies remain and the most capable limb prostheses fall far short of the capabilities of the healthy limb. This article describes the current state of prosthesis technology; identifies a number of deficiencies across the spectrum of lower limb prosthetic components with respect to users' needs; and discusses research opportunities in design and control that would substantially improve functionality concerning each deficiency. In doing so, the authors present a roadmap of patients related issues that should be addressed in order to fulfill the vision of a next-generation, neurally-integrated, highly-functional lower limb prosthesis.

Towards assessing the preferred usage features of upper limb prostheses: most important items regarding prosthesis use in people with major unilateral upper limb absence-a Dutch national survey

PURPOSE

To determine which items regarding prosthesis use were considered most important by adults with major unilateral upper limb absence (ULA) and to develop a patient-reported outcome measure to assess the preferred usage features of upper limb prostheses: PUF-ULP.

MATERIALS AND METHODS

Based on a qualitative meta-synthesis combined with input from patients and clinicians a graphical diagram of 79 items related to prosthesis use was developed. Adults with ULA (N = 358; mean age = 55.4 ± 16.5 years; 52.0% male/40.8% female/7.3% unknown) selected their top-10 of most important items from this diagram. This study is registered in the Netherlands Trial Register: NL7682.

RESULTS

Most selected items were "wearing comfort" (54.0% of cases), "grabbing, picking up, and holding" (34.3%), and "weight" (31.4%). All subpopulations (i.e. age, sex, origin of ULA, level of ULA, and prosthesis type), except multi-grip myoelectric hand prosthesis users (MHP), selected "wearing comfort" most. Nine items were included in the PUF-ULP: "wearing comfort," "functionality," "independence," "work, hobby, and household," "user-friendly," "life-like appearance," "phantom limb pain," "overuse complaints," and "reliability."

CONCLUSIONS

All prosthesis users, except MHP-users, considered wearing comfort most important, which might be of interest for future research and industry. The PUF-ULP can be used to reflect the match between users and their prostheses.IMPLICATIONS FOR REHABILITATIONAll persons with upper limb absence, except multi-grip myoelectric hand prosthesis users, considered "wearing comfort" most important regarding prosthesis use, which highlights that prosthesis wearing comfort deserves more attention in future research to increase the value placed by the user on their upper limb prosthesis.Regarding prosthesis use, men considered "ease of control" more important compared to the overall population, while women considered "independence," "household," "life-like appearance," "overuse complaints," and "anonymity" more important.Persons with a mono- or multi-grip myoelectric upper limb prosthesis rated function-related items as more important compared to the overall population, while persons with a passive/cosmetic prosthesis rated comfort-related and appearance-related items as more important.The newly developed measurement tool, also called the PUF-ULP, provides a single score that represents the match between the user and their upper limb prosthesis.

Closed-loop stimulation of lateral cervical spinal cord in upper-limb amputees to enable sensory discrimination: a case study

Modern myoelectric prosthetic hands have multiple independently controllable degrees of freedom, but require constant visual attention to use effectively. Somatosensory feedback provides information not available through vision alone and is essential for fine motor control of our limbs. Similarly, stimulation of the nervous system can potentially provide artificial somatosensory feedback to reduce the reliance on visual cues to efficiently operate prosthetic devices. We have shown previously that epidural stimulation of the lateral cervical spinal cord can evoke tactile sensations perceived as emanating from the missing arm and hand in people with upper-limb amputation. In this case study, two subjects with upper-limb amputation used this somatotopically-matched tactile feedback to discriminate object size and compliance while controlling a prosthetic hand. With less than 30 min of practice each day, both subjects were able to use artificial somatosensory feedback to perform a subset of the discrimination tasks at a success level well above chance. Subject 1 was consistently more adept at determining object size (74% accuracy; chance: 33%) while Subject 2 achieved a higher accuracy level in determining object compliance (60% accuracy; chance 33%). In each subject, discrimination of the other object property was only slightly above or at chance level suggesting that the task design and stimulation encoding scheme are important determinants of which object property could be reliably identified. Our observations suggest that changes in the intensity of artificial somatosensory feedback provided via spinal cord stimulation can be readily used to infer information about object properties with minimal training.

Artificial Intelligence Enables Real-Time and Intuitive Control of Prostheses via Nerve Interface

OBJECTIVE

The next generation prosthetic hand that moves and feels like a real hand requires a robust neural interconnection between the human minds and machines.

METHODS

Here we present a neuroprosthetic system to demonstrate that principle by employing an artificial intelligence (AI) agent to translate the amputees movement intent through a peripheral nerve interface. The AI agent is designed based on the recurrent neural network (RNN) and could simultaneously decode six degree-of-freedom (DOF) from multichannel nerve data in real-time. The decoder's performance is characterized in motor decoding experiments with three human amputees.

RESULTS

First, we show the AI agent enables amputees to intuitively control a prosthetic hand with individual finger and wrist movements up to 97-98% accuracy. Second, we demonstrate the AI agent's real-time performance by measuring the reaction time and information throughput in a hand gesture matching task. Third, we investigate the AI agent's long-term uses and show the decoder's robust predictive performance over a 16-month implant duration. Conclusion & significance: Our study demonstrates the potential of AI-enabled nerve technology, underling the next generation of dexterous and intuitive prosthetic hands.

A portable, self-contained neuroprosthetic hand with deep learning-based finger control

Objective.Deep learning-based neural decoders have emerged as the prominent approach to enable dexterous and intuitive control of neuroprosthetic hands. Yet few studies have materialized the use of deep learning in clinical settings due to its high computational requirements.Approach.Recent advancements of edge computing devices bring the potential to alleviate this problem. Here we present the implementation of a neuroprosthetic hand with embedded deep learning-based control. The neural decoder is designed based on the recurrent neural network architecture and deployed on the NVIDIA Jetson Nano-a compacted yet powerful edge computing platform for deep learning inference. This enables the implementation of the neuroprosthetic hand as a portable and self-contained unit with real-time control of individual finger movements.Main results.A pilot study with a transradial amputee is conducted to evaluate the proposed system using peripheral nerve signals acquired from implanted intrafascicular microelectrodes. The preliminary experiment results show the system's capabilities of providing robust, high-accuracy (95%-99%) and low-latency (50-120 ms) control of individual finger movements in various laboratory and real-world environments.Conclusion.This work is a technological demonstration of modern edge computing platforms to enable the effective use of deep learning-based neural decoders for neuroprosthesis control as an autonomous system.Significance.The proposed system helps pioneer the deployment of deep neural networks in clinical applications underlying a new class of wearable biomedical devices with embedded artificial intelligence.Clinical trial registration: DExterous Hand Control Through Fascicular Targeting (DEFT). Identifier: NCT02994160.

Acquisition of Surface EMG Using Flexible and Low-Profile Electrodes for Lower Extremity Neuroprosthetic Control

For persons with lower extremity (LE) amputation, acquisition of surface electromyography (sEMG) from within the prosthetic socket remains a significant challenge due to the dynamic loads experienced during the gait cycle. However, these signals are critical for both understanding the clinical effects of LE amputation and determining the desired control trajectories of active LE prostheses. Current solutions for collecting within-socket sEMG are generally (i) incompatible with a subject's prescribed prosthetic socket and liners, (ii) uncomfortable, and (iii) expensive. This study presents an alternative within-socket sEMG acquisition paradigm using a novel flexible and low-profile electrode. First, the practical performance of this Sub-Liner Interface for Prosthetics (SLIP) electrode is compared to that of commercial Ag/AgCl electrodes within a cohort of subjects without amputation. Then, the corresponding SLIP electrode sEMG acquisition paradigm is implemented in a single subject with unilateral transtibial amputation performing unconstrained movements and walking on level ground. Finally, a quantitative questionnaire characterizes subjective comfort for SLIP electrode and commercial Ag/AgCl electrode instrumentation setups. Quantitative analyses suggest comparable signal qualities between SLIP and Ag/AgCl electrodes while qualitative analyses suggest the feasibility of using the SLIP electrode for real-time sEMG data collection from load-bearing, ambulatory subjects with LE amputation.

The Need to Work Arm in Arm: Calling for Collaboration in Delivering Neuroprosthetic Limb Replacements

Over the last few decades there has been a push to enhance the use of advanced prosthetics within the fields of biomedical engineering, neuroscience, and surgery. Through the development of peripheral neural interfaces and invasive electrodes, an individual's own nervous system can be used to control a prosthesis. With novel improvements in neural recording and signal decoding, this intimate communication has paved the way for bidirectional and intuitive control of prostheses. While various collaborations between engineers and surgeons have led to considerable success with motor control and pain management, it has been significantly more challenging to restore sensation. Many of the existing peripheral neural interfaces have demonstrated success in one of these modalities; however, none are currently able to fully restore limb function. Though this is in part due to the complexity of the human somatosensory system and stability of bioelectronics, the fragmentary and as-yet uncoordinated nature of the neuroprosthetic industry further complicates this advancement. In this review, we provide a comprehensive overview of the current field of neuroprosthetics and explore potential strategies to address its unique challenges. These include exploration of electrodes, surgical techniques, control methods, and prosthetic technology. Additionally, we propose a new approach to optimizing prosthetic limb function and facilitating clinical application by capitalizing on available resources. It is incumbent upon academia and industry to encourage collaboration and utilization of different peripheral neural interfaces in combination with each other to create versatile limbs that not only improve function but quality of life. Despite the rapidly evolving technology, if the field continues to work in divided "silos," we will delay achieving the critical, valuable outcome: creating a prosthetic limb that is right for the patient and positively affects their life.

A new approach of inducing proprioceptive illusion by transcutaneous electrical stimulation

BACKGROUND

Neurotraumas or neurodegenerative diseases often result in proprioceptive deficits, which makes it challenging for the nervous system to adapt to the compromised sensorimotor conditions. Also, in human machine interactions, such as prosthesis control and teleoperation, proprioceptive mismatch limits accuracy and intuitiveness of controlling active joints in robotic agents. To address these proprioceptive deficits, several invasive and non-invasive approaches like vibration, electrical nerve stimulation, and skin stretch have been introduced. However, proprioceptive modulation is still challenging as the current solutions have limitations in terms of effectiveness, usability, and consistency. In this paper, we propose a new way of modulating proprioception using transcutaneous electrical stimulation. We hypothesized that transcutaneous electrical stimulation on elbow flexor muscles will induce illusion of elbow joint extension.

METHOD

Eight healthy human subjects participated in the study to test the hypothesis. Transcutaneous electrodes were placed on different locations targeting elbow flexor muscles on human subjects and experiments were conducted to identify the best locations for electrode placement, and best electrical stimulation parameters, to maximize induced proprioceptive effect. Arm matching experiments and Pinocchio illusion test were performed for quantitative and qualitative analysis of the observed effects. One-way repeated ANOVA test was performed on the data collected in arm matching experiment for statistical analysis.

RESULTS

We identified the best location for transcutaneous electrodes to induce the proprioceptive illusion, as one electrode on the muscle belly of biceps brachii short head and the other on the distal myotendinous junction of brachioradialis. The results for arm-matching and Pinocchio illusion tests showed that transcutaneous electrical stimulation using identified electrode location and electrical stimulation parameters evoked the illusion of elbow joint extension for all eight subjects, which supports our hypothesis. On average, subjects reported 6.81° angular illusion of elbow joint extension in arm-matching tests and nose elongated to 1.78 × height in Pinocchio illusion test.

CONCLUSIONS

Transcutaneous electrical stimulation, applied between the the synergistic elbow flexor muscles, consistently modulated elbow joint proprioception with the illusion of elbow joint extension, which has immense potential to be translated into various real-world applications, including neuroprosthesis, rehabilitation, teleoperation, mixed reality, and etc.

Closed-Loop Plantar Cutaneous Augmentation by Electrical Nerve Stimulation Increases Ankle Plantarflexion During Treadmill Walking

Ankle plantarflexion plays an important role in forward propulsion and anterior-posterior balance during locomotion. This component of gait is often critically impacted by neurotraumas and neurological diseases. We hypothesized that augmenting plantar cutaneous feedback, via closed-loop distal-tibial nerve stimulation, could increase ankle plantarflexion during walking. To test the hypothesis, one intact rat walked on a motorized treadmill with implanted electronic device and electrodes for closed-loop neural recording and stimulation. Constant-current biphasic electrical pulse train was applied to distal-tibial nerve, based on electromyogram recorded from the medial gastrocnemius muscle, to be timed with the stance phase. The stimulation current threshold to evoke plantar cutaneous feedback was set at 30 μA (1·T), based on compound action potential evoked by stimulation. The maximum ankle joint angle at plantarflexion, during the application of stimulation currents of 3.3·T and 6.6·T, respectively, was increased from 149.4° (baseline) to 165.4° and 161.6°. The minimum ankle joint angle at dorsiflexion was decreased from 59.4° (baseline) to 53.1°, during the application of stimulation currents of 3.3·T, but not changed by 6.6·T. Plantar cutaneous augmentation also changed other gait kinematic parameters. Stance duty factor was increased from 51.9% (baseline) to 65.7% and 64.0%, respectively, by 3.3·T and 6.6·T, primarily due to a decrease in swing duration. Cycle duration was consistently decreased by the stimulation. In the control trial after two stimulation trials, a strong after-effect was detected in overall gait kinematics as well as ankle plantarflexion, suggesting that this stimulation has the potential for producing long-term changes in gait kinematics.