Closed-loop neuromuscular electrical stimulation using feedforward-feedback control and textile electrodes to regulate grasp force in quadriplegia

Benchtop Performance of Novel Mixed Ionic-Electronic Conductive Electrode Form Factors for Biopotential Recordings

Background: Traditional gel-based (wet) electrodes for biopotential recordings have several shortcomings that limit their practicality for real-world measurements. Dry electrodes may improve usability, but they often suffer from reduced signal quality. We sought to evaluate the biopotential recording properties of a novel mixed ionic-electronic conductive (MIEC) material for improved performance. Methods: We fabricated four MIEC electrode form factors and compared their signal recording properties to two control electrodes, which are electrodes commonly used for biopotential recordings (Ag-AgCl and stainless steel). We used an agar synthetic skin to characterize the impedance of each electrode form factor. An electrical phantom setup allowed us to compare the recording quality of simulated biopotentials with ground-truth sources. Results: All MIEC electrode form factors yielded impedances in a similar range to the control electrodes (all <80 kΩ at 100 Hz). Three of the four MIEC samples produced similar signal-to-noise ratios and interfacial charge transfers as the control electrodes. Conclusions: The MIEC electrodes demonstrated similar and, in some cases, better signal recording characteristics than current state-of-the-art electrodes. MIEC electrodes can also be fabricated into a myriad of form factors, underscoring the great potential this novel material has across a wide range of biopotential recording applications.

Porous Conductive Textiles for Wearable Electronics

Over the years, researchers have made significant strides in the development of novel flexible/stretchable and conductive materials, enabling the creation of cutting-edge electronic devices for wearable applications. Among these, porous conductive textiles (PCTs) have emerged as an ideal material platform for wearable electronics, owing to their light weight, flexibility, permeability, and wearing comfort. This Review aims to present a comprehensive overview of the progress and state of the art of utilizing PCTs for the design and fabrication of a wide variety of wearable electronic devices and their integrated wearable systems. To begin with, we elucidate how PCTs revolutionize the form factors of wearable electronics. We then discuss the preparation strategies of PCTs, in terms of the raw materials, fabrication processes, and key properties. Afterward, we provide detailed illustrations of how PCTs are used as basic building blocks to design and fabricate a wide variety of intrinsically flexible or stretchable devices, including sensors, actuators, therapeutic devices, energy-harvesting and storage devices, and displays. We further describe the techniques and strategies for wearable electronic systems either by hybridizing conventional off-the-shelf rigid electronic components with PCTs or by integrating multiple fibrous devices made of PCTs. Subsequently, we highlight some important wearable application scenarios in healthcare, sports and training, converging technologies, and professional specialists. At the end of the Review, we discuss the challenges and perspectives on future research directions and give overall conclusions. As the demand for more personalized and interconnected devices continues to grow, PCT-based wearables hold immense potential to redefine the landscape of wearable technology and reshape the way we live, work, and play.

Neural Bypasses: Literature Review and Future Directions in Developing Artificial Neural Connections

Reported neuro-modulation schemes in the literature are typically classified as closed-loop or open-loop. A novel group of recently developed neuro-modulation devices may be better described as a neural bypass, which attempts to transmit neural data from one location of the nervous system to another. The most common form of neural bypasses in the literature utilize EEG recordings of cortical information paired with functional electrical stimulation for effector muscle output, most commonly for assistive applications and rehabilitation in spinal cord injury or stroke. Other neural bypass locations that have also been described, or may soon be in development, include cortical-spinal bypasses, cortical-cortical bypasses, autonomic bypasses, peripheral-central bypasses, and inter-subject bypasses. The most common recording devices include EEG, ECoG, and microelectrode arrays, while stimulation devices include both invasive and noninvasive electrodes. Several devices are in development to improve the temporal and spatial resolution and biocompatibility for neuronal recording and stimulation. A major barrier to entry includes neuroplasticity and current decoding mechanisms that regularly require retraining. Neural bypasses are a unique class of neuro-modulation. Continued advancement of neural recording and stimulating devices with high spatial and temporal resolution, combined with decoding mechanisms uninhibited by neuroplasticity, can expand the therapeutic capability of neural bypassing. Overall, neural bypasses are a promising modality to improve the treatment of common neurologic disorders, including stroke, spinal cord injury, peripheral nerve injury, brain injury and more.

Bioelectronic medicine: Preclinical insights and clinical advances

The nervous system maintains homeostasis and health. Homeostatic disruptions underlying the pathobiology of many diseases can be controlled by bioelectronic devices targeting CNS and peripheral neural circuits. New insights into the regulatory functions of the nervous system and technological developments in bioelectronics drive progress in the emerging field of bioelectronic medicine. Here, we provide an overview of key aspects of preclinical research, translation, and clinical advances in bioelectronic medicine.

A fully implantable wireless bidirectional neuromodulation system for mice

Novel research in the field of bioelectronic medicine requires neuromodulation systems that pair high-performance neurostimulation and bio-signal acquisition hardware with advanced signal processing and control algorithms. Although mice are the most commonly used animal in medical research, the size, weight, and power requirements of such bioelectronic systems either preclude use in mice or impose significant constraints on experimental design. Here, a fully-implantable recording and stimulation neuromodulation system suitable for use in mice is presented, measuring 2.2 cm3 and weighing 2.8 g. The bidirectional wireless interface allows simultaneous readout of multiple physiological signals and complete control over stimulation parameters, and a wirelessly rechargeable battery provides a lifetime of up to 5 days on a single charge. The device was implanted to deliver vagus nerve stimulation (n = 12 animals) and a functional neural interface (capable of inducing acute bradycardia) was demonstrated with lifetimes exceeding three weeks. The design utilizes only commercially-available electrical components and 3D-printed packaging, with the goal of facilitating widespread adoption and accelerating discovery and translation of future bioelectronic therapeutics.

Closed-loop automated reaching apparatus (CLARA) for interrogating complex motor behaviors

Objective.Closed-loop neuromodulation technology is a rapidly expanding category of therapeutics for a broad range of indications. Development of these innovative neurological devices requires high-throughput systems for closed-loop stimulation of model organisms, while monitoring physiological signals and complex, naturalistic behaviors. To address this need, we developed CLARA, a closed-loop automated reaching apparatus.Approach.Using breakthroughs in computer vision, CLARA integrates fully-automated, markerless kinematic tracking of multiple features to classify animal behavior and precisely deliver neural stimulation based on behavioral outcomes. CLARA is compatible with advanced neurophysiological tools, enabling the testing of neurostimulation devices and identification of novel neurological biomarkers.Results.The CLARA system tracks unconstrained skilled reach behavior in 3D at 150 Hz without physical markers. The system fully automates trial initiation and pellet delivery and is capable of accurately delivering stimulation in response to trial outcome with short latency. Kinematic data from the CLARA system provided novel insights into the dynamics of reach consistency over the course of learning, suggesting that learning selectively improves reach failures but does not alter the kinematics of successful reaches. Additionally, using the closed-loop capabilities of CLARA, we demonstrate that vagus nerve stimulation (VNS) improves skilled reach performance and increases reach trajectory consistency in healthy animals.Significance.The CLARA system is the first mouse behavior apparatus that uses markerless pose tracking to provide real-time closed-loop stimulation in response to the outcome of an unconstrained motor task. Additionally, we demonstrate that the CLARA system was essential for our investigating the role of closed-loop VNS stimulation on motor performance in healthy animals. This approach has high translational relevance for developing neurostimulation technology based on complex human behavior.

Toward nanobioelectronic medicine: Unlocking new applications using nanotechnology

Bioelectronic medicine aims to interface electronic technology with biological components and design more effective therapeutic and diagnostic tools. Advances in nanotechnology have moved the field forward improving the seamless interaction between biological and electronic components. In the lab many of these nanobioelectronic devices have the potential to improve current treatment approaches, including those for cancer, cardiovascular disorders, and disease underpinned by malfunctions in neuronal electrical communication. While promising, many of these devices and technologies require further development before they can be successfully applied in a clinical setting. Here, we highlight recent work which is close to achieving this goal, including discussion of nanoparticles, carbon nanotubes, and nanowires for medical applications. We also look forward toward the next decade to determine how current developments in nanotechnology could shape the growing field of bioelectronic medicine. This article is categorized under: Therapeutic Approaches and Drug Discovery > Emerging Technologies Nanotechnology Approaches to Biology > Nanoscale Systems in Biology Diagnostic Tools > Biosensing.

Determining grasp selection from arm trajectories via deep learning to enable functional hand movement in tetraplegia

Background

Cervical spinal cord injury severely affects grasping ability of its survivors. Fortunately, many individuals with tetraplegia retain residual arm movements that allow them to reach for objects. We propose a wearable technology that utilizes arm movement trajectory information and deep learning methods to determine grasp selection. Furthermore, we combined this approach with neuromuscular stimulation to determine if self-driven functional hand movement could be enabled in spinal cord injury participants.

Methods

Two cervical SCI participants performed arbitrary and natural reaching movements toward target objects in three-dimensional space, which were recorded using an inertial sensor worn on their wrist. Time series classifiers were trained to recognize the trajectories using either a Dynamic Time Warping (DTW) algorithm or a Long Short-Term Memory (LSTM) recurrent neural network. As an initial proof-of-concept, we demonstrate real-time classification of the arbitrary movements using DTW only (due to its implementation simplicity), which when used in combination with a high density neuromuscular stimulation sleeve with textile electrodes, enabled participants to perform functional grasping.

Results

Participants were able to consistently perform arbitrary two-dimensional and three-dimensional arm movements which could be classified with high accuracy. Furthermore, it was found that natural reaching trajectories for two different target objects (requiring two different grasp types) were distinct and also discriminable with high accuracy. In offline comparisons, LSTM (mean accuracies 99%) performed significantly better than DTW (mean accuracies 86 and 83%) for both arbitrary and natural reaching movements, respectively. Type I and II errors occurred more frequently for DTW (up to 60 and 15%, respectively), whereas it stayed under 5% for LSTM. Also, DTW achieved online accuracy of 79%.

Conclusions

We demonstrate the feasibility of utilizing arm trajectory information to determine grasp selection using a wearable inertial sensor along with DTW and deep learning methods. Importantly, this technology can be successfully used to control neuromuscular stimulation and restore functional independence to individuals living with paralysis.

Trial registration

NCT, NCT03385005. Registered September 26, 2017.