Assessing the manufacturable 32-channel cochlear electrode array: evaluation results for clinical trials

Reliability evaluation results of a manufacturable 32-channel cochlear electrode array are reported in this paper. Applying automated laser micro-machining process and a layer-by-layer silicone deposition scheme, authors developed the manufacturing methods of the electrode array for fine patterning and mass production. The developed electrode array has been verified through the requirements specified by the ISO Standard 14708-7. And the insertion trauma of the electrode array has been evaluated based on human temporal bone studies. According to the specified requirements, the electrode array was assessed through elongation & insulation, flexural, and fatigue tests. In addition, Temporal bone study was performed using eight fresh-frozen cadaver temporal bones with the electrode arrays inserted via the round window. Following soaking in saline condition, the impedances between conducting wires of the electrode array were measured over 100 kΩ (the pass/fail criterion). After each required test, it was shown that the electrode array maintained the electrical continuity and insulation condition. The average insertion angle of the electrode array inside the scala tympani was 399.7°. The human temporal bone studies exhibited atraumatic insertion rate of 60.3% (grade 0 or 1). The reliability of the manufacturable electrode array is successfully verified in mechanical, electrical, and histological aspects. Following the completion of a 32-channel cochlear implant system, the performance and stability of the 32-channel electrode array will be evaluated in clinical trials.

Uncovering and leveraging the return of voluntary motor programs after paralysis using a bi-cortical neuroprosthesis

Rehabilitative and neuroprosthetic approaches after spinal cord injury (SCI) aim to reestablish voluntary control of movement. Promoting recovery requires a mechanistic understanding of the return of volition over action, but the relationship between re-emerging cortical commands and the return of locomotion is not well established. We introduced a neuroprosthesis delivering targeted bi-cortical stimulation in a clinically relevant contusive SCI model. In healthy and SCI cats, we controlled hindlimb locomotor output by tuning stimulation timing, duration, amplitude, and site. In intact cats, we unveiled a large repertoire of motor programs. After SCI, the evoked hindlimb lifts were highly stereotyped, yet effective in modulating gait and alleviating bilateral foot drag. Results suggest that the neural substrate underpinning motor recovery had traded-off selectivity for efficacy. Longitudinal tests revealed that the return of locomotion after SCI was correlated with recovery of the descending drive, which advocates for rehabilitation interventions directed at the cortical target.

[New perspectives in orthopedics : Developments through neurotechnology and metaverse]

The combination of neurotechnology and metaverse holds high potentials for orthopedics, as it offers a broad spectrum of possibilities to overcome the limits of traditional medical care. The vision of a medical metaverse providing the infrastructure as a link for innovative technologies opens up new opportunities for therapy, medical collaborations and practical, personalized training for aspiring physicians. However, risks and challenges, such as security and privacy, health-related issues, acceptance by patients and doctors, as well as technical hurdles and access to the technologies, remain. Hence, future research and development is paramount. Nonetheless, due to technological progress, the exploration of new research areas, and the improved availability of the technologies paired with cost reduction, the prospects for neurotechnology and metaverse in orthopedics are promising.

Human-machine interface for two-dimensional steering control with the auricular muscles

Human-machine interfaces (HMIs) can be used to decode a user's motor intention to control an external device. People that suffer from motor disabilities, such as spinal cord injury, can benefit from the uses of these interfaces. While many solutions can be found in this direction, there is still room for improvement both from a decoding, hardware, and subject-motor learning perspective. Here we show, in a series of experiments with non-disabled participants, a novel decoding and training paradigm allowing naïve participants to use their auricular muscles (AM) to control two degrees of freedom with a virtual cursor. AMs are particularly interesting because they are vestigial muscles and are often preserved after neurological diseases. Our method relies on the use of surface electromyographic records and the use of contraction levels of both AMs to modulate the velocity and direction of a cursor in a two-dimensional paradigm. We used a locking mechanism to fix the current position of each axis separately to enable the user to stop the cursor at a certain location. A five-session training procedure (20-30 min per session) with a 2D center-out task was performed by five volunteers. All participants increased their success rate (Initial: 52.78 ± 5.56%; Final: 72.22 ± 6.67%; median ± median absolute deviation) and their trajectory performances throughout the training. We implemented a dual task with visual distractors to assess the mental challenge of controlling while executing another task; our results suggest that the participants could perform the task in cognitively demanding conditions (success rate of 66.67 ± 5.56%). Finally, using the Nasa Task Load Index questionnaire, we found that participants reported lower mental demand and effort in the last two sessions. To summarize, all subjects could learn to control the movement of a cursor with two degrees of freedom using their AM, with a low impact on the cognitive load. Our study is a first step in developing AM-based decoders for HMIs for people with motor disabilities, such as spinal cord injury.

Peripheral nerve stimulation enables somatosensory feedback while suppressing phantom limb pain in transradial amputees

To simultaneously treat phantom limb pain (PLP) and restore somatic sensations using peripheral nerve stimulation (PNS), two bilateral transradial amputees were implanted with stimulating electrodes in the proximity of the medial, ulnar and radial nerves. Application of PNS evoked tactile and proprioceptive sensations in the phantom hand. Both patients learned to determine the shape of invisible objects by scanning a computer tablet with a stylus while receiving feedback based on PNS or transcutaneous electrical nerve stimulation (TENS). Оne patient learned to use PNS as feedback from the prosthetic hand that grasped objects of different sizes. PNS abolished PLP completely in one patient and reduced it by 40-70% in the other. We suggest incorporating PNS and/or TENS in active tasks to reduce PLP and restore sensations in amputees.

A Custom Interface for the Joint Operation of Med Associates and Tucker-Davis Technologies Hardware in a Rodent Behavioral Model

BACKGROUND

Rodent behavioral models with an electrophysiological component may require the joint operation of hardware from Med Associates, Inc. (St. Albans, VT) and Tucker-Davis Technologies (TDT; Alachua, FL). Although these manufacturers do produce supplemental hardware for interfacing with each other, investing in such hardware may be untenable for research groups with limited funds who wish to use equipment already in their possession.

NEW METHOD

We designed a printed circuit board (PCB) in KiCad and had it fabricated by Advanced Circuits (Aurora, CO), with components sourced from Digi-Key (Thief River Falls, MN). The PCB provided 8 channels of bidirectional communication for the transmission of signals between Med Asssociates' SG-716B SmartCtrl connection panel and TDT's RZ5D base station. This setup enabled the coordinated operation of programs running separately on each set of hardware.

RESULTS

The custom-built PCB facilitated the joint operation of Med Associates and TDT hardware in a go/no-go detection task involving rats with electrical implants in their sciatic nerves.

COMPARISON WITH EXISTING METHODS

Conventional methods for interfacing Med Associates and Tucker-Davis Technologies rely on the purchase of pre-built hardware whose costs can add up to thousands of dollars. The present method offers a viable alternative that is easily implemented and considerably less expensive (below $200).

CONCLUSION

The present approach provides an inexpensive yet effective alternative to far more costly interfacing solutions offered by Med Associates and Tucker-Davis Technologies.

Control and Ownership of Neuroprosthetic Speech

Implantable brain-computer interfaces (BCIs) are being developed to restore speech capacity for those who are unable to speak. Patients with locked-in syndrome or amyotrophic lateral sclerosis could be able to use covert speech – vividly imagining saying something without actual vocalisation – to trigger neural controlled systems capable of synthesising speech. User control has been identified as particularly pressing for this type of BCI. The incorporation of machine learning and statistical language models into the decoding process introduces a contribution to (or ‘shaping of’) the output that is beyond the user’s control. Whilst this type of ‘shared control’ of BCI action is not unique to speech BCIs, the automated shaping of what a user ‘says’ has a particularly acute ethical dimension, which may differ from parallel concerns surrounding automation in movement BCIs. This paper provides an analysis of the control afforded to the user of a speech BCI of the sort under development, as well as the relationships between accuracy, control, and the user’s ownership of the speech produced. Through comparing speech BCIs with BCIs for movement, we argue that, whilst goal selection is the more significant locus of control for the user of a movement BCI, control over process will be more significant for the user of the speech BCI. The design of the speech BCI may therefore have to trade off some possible efficiency gains afforded by automation in order to preserve sufficient guidance control necessary for users to express themselves in ways they prefer. We consider the implications for the speech BCI user’s responsibility for produced outputs and their ownership of token outputs. We argue that these are distinct assessments. Ownership of synthetic speech concerns whether the content of the output sufficiently represents the user, rather than their morally relevant, causal role in producing that output.

Generating artificial sensations with spinal cord stimulation in primates and rodents

For patients who have lost sensory function due to a neurological injury such as spinal cord injury (SCI), stroke, or amputation, spinal cord stimulation (SCS) may provide a mechanism for restoring somatic sensations via an intuitive, non-visual pathway. Inspired by this vision, here we trained rhesus monkeys and rats to detect and discriminate patterns of epidural SCS. Thereafter, we constructed psychometric curves describing the relationship between different SCS parameters and the animal's ability to detect SCS and/or changes in its characteristics. We found that the stimulus detection threshold decreased with higher frequency, longer pulse-width, and increasing duration of SCS. Moreover, we found that monkeys were able to discriminate temporally- and spatially-varying patterns (i.e. variations in frequency and location) of SCS delivered through multiple electrodes. Additionally, sensory discrimination of SCS-induced sensations in rats obeyed Weber's law of just-noticeable differences. These findings suggest that by varying SCS intensity, temporal pattern, and location different sensory experiences can be evoked. As such, we posit that SCS can provide intuitive sensory feedback in neuroprosthetic devices.

Activities of daily living with bionic arm improved by combination training and latching filter in prosthesis control comparison

BACKGROUND

Advanced prostheses can restore function and improve quality of life for individuals with amputations. Unfortunately, most commercial control strategies do not fully utilize the rich control information from residual nerves and musculature. Continuous decoders can provide more intuitive prosthesis control using multi-channel neural or electromyographic recordings. Three components influence continuous decoder performance: the data used to train the algorithm, the algorithm, and smoothing filters on the algorithm's output. Individual groups often focus on a single decoder, so very few studies compare different decoders using otherwise similar experimental conditions.

METHODS

We completed a two-phase, head-to-head comparison of 12 continuous decoders using activities of daily living. In phase one, we compared two training types and a smoothing filter with three algorithms (modified Kalman filter, multi-layer perceptron, and convolutional neural network) in a clothespin relocation task. We compared training types that included only individual digit and wrist movements vs. combination movements (e.g., simultaneous grasp and wrist flexion). We also compared raw vs. nonlinearly smoothed algorithm outputs. In phase two, we compared the three algorithms in fragile egg, zipping, pouring, and folding tasks using the combination training and smoothing found beneficial in phase one. In both phases, we collected objective, performance-based (e.g., success rate), and subjective, user-focused (e.g., preference) measures.

RESULTS

Phase one showed that combination training improved prosthesis control accuracy and speed, and that the nonlinear smoothing improved accuracy but generally reduced speed. Phase one importantly showed simultaneous movements were used in the task, and that the modified Kalman filter and multi-layer perceptron predicted more simultaneous movements than the convolutional neural network. In phase two, user-focused metrics favored the convolutional neural network and modified Kalman filter, whereas performance-based metrics were generally similar among all algorithms.

CONCLUSIONS

These results confirm that state-of-the-art algorithms, whether linear or nonlinear in nature, functionally benefit from training on more complex data and from output smoothing. These studies will be used to select a decoder for a long-term take-home trial with implanted neuromyoelectric devices. Overall, clinical considerations may favor the mKF as it is similar in performance, faster to train, and computationally less expensive than neural networks.

Brain Recording, Mind-Reading, and Neurotechnology: Ethical Issues from Consumer Devices to Brain-Based Speech Decoding

Brain reading technologies are rapidly being developed in a number of neuroscience fields. These technologies can record, process, and decode neural signals. This has been described as 'mind reading technology' in some instances, especially in popular media. Should the public at large, be concerned about this kind of technology? Can it really read minds? Concerns about mind-reading might include the thought that, in having one's mind open to view, the possibility for free deliberation, and for self-conception, are eroded where one isn't at liberty to privately mull things over. Themes including privacy, cognitive liberty, and self-conception and expression appear to be areas of vital ethical concern. Overall, this article explores whether brain reading technologies are really mind reading technologies. If they are, ethical ways to deal with them must be developed. If they are not, researchers and technology developers need to find ways to describe them more accurately, in order to dispel unwarranted concerns and address appropriately those that are warranted.

Advances in neuroprosthetic management of foot drop: a review

This paper reviews the technological advances and clinical results obtained in the neuroprosthetic management of foot drop. Functional electrical stimulation has been widely applied owing to its corrective abilities in patients suffering from a stroke, multiple sclerosis, or spinal cord injury among other pathologies. This review aims at identifying the progress made in this area over the last two decades, addressing two main questions: What is the status of neuroprosthetic technology in terms of architecture, sensorization, and control algorithms?. What is the current evidence on its functional and clinical efficacy? The results reveal the importance of systems capable of self-adjustment and the need for closed-loop control systems to adequately modulate assistance in individual conditions. Other advanced strategies, such as combining variable and constant frequency pulses, could also play an important role in reducing fatigue and obtaining better therapeutic results. The field not only would benefit from a deeper understanding of the kinematic, kinetic and neuromuscular implications and effects of more promising assistance strategies, but also there is a clear lack of long-term clinical studies addressing the therapeutic potential of these systems. This review paper provides an overview of current system design and control architectures choices with regard to their clinical effectiveness. Shortcomings and recommendations for future directions are identified.

Local field potentials for BCI control

The gold standard in brain-computer interface (BCI) modalities is multi single-unit recordings in the primary motor cortex. It yields the fastest and most elegant control (i.e., most degrees of freedom and bitrate). Unfortunately, single-unit electrodes are prone to encapsulation, which limit their single-unit recording life. However, encapsulation does not significantly affect intracortical local field potentials (LFPs). LFPs and single-unit activity were recorded from the motor cortices of three monkeys (Macaca fascicularis) while they performed a standard 3D center-out reaching task and a 3D circle-drawing task. The high frequency (HF) (60-200 Hz) spectral amplitudes of a subset of the LFPs were found to be directionally tuned much like single units. In fact, stable isolation of single units on the same electrode increased the likelihood that the HF-LFP would be significantly cosine tuned to hand direction. The presence of significantly tuned single units further increased the likelihood of a tuned HF-LFP, suggesting that this band of HF-LFP activity is at least partially generated by local neuronal action potential currents (i.e., single-unit activity). Given that encapsulation makes recording single units over a long period of time difficult, these results suggest that HF-LFPs may be a more stable and efficient method of monitoring neural activity for BCI applications.

Ethics and the emergence of brain-computer interface medicine

Brain-computer interface (BCI) technology will usher in profound changes to the practice of medicine. BCI devices, broadly defined as those capable of reading brain activity and translating this into operation of a device, will offer patients and clinicians new ways to address impairments of communication, movement, sensation, and mental health. These new capabilities will bring new responsibilities and raise a diverse set of ethical challenges. One way to understand and begin to address these challenges is to view them in terms of the goals of medicine. In this chapter, different ways in which BCI technology may subserve the goals of medicine is explored. This is followed by articulation of additional goals particularly relevant to BCI technology: neural diversity, neural privacy, agency, and authenticity. The goals of medicine provide a useful ethical framework for the introduction of BCI devices into medicine.

Stable, three degree-of-freedom myoelectric prosthetic control via chronic bipolar intramuscular electrodes: a case study

Background

Modern prosthetic hands are typically controlled using skin surface electromyographic signals (EMG) from remaining muscles in the residual limb. However, surface electrode performance is limited by changes in skin impedance over time, day-to-day variations in electrode placement, and relative motion between the electrodes and underlying muscles during movement: these limitations require frequent retraining of controllers. In the presented study, we used chronically implanted intramuscular electrodes to minimize these effects and thus create a more robust prosthetic controller.

Methods

A study participant with a transradial amputation was chronically implanted with 8 intramuscular EMG electrodes. A K Nearest Neighbor (KNN) regression velocity controller was trained to predict intended joint movement direction using EMG data collected during a single training session. The resulting KNN was evaluated over 12 weeks and in multiple arm posture configurations, with the participant controlling a 3 Degree-of-Freedom (DOF) virtual reality (VR) hand to match target VR hand postures. The performance of this EMG-based controller was compared to a position-based controller that used movement measured from the participant’s opposite (intact) hand. Surface EMG was also collected for signal quality comparisons.

Results

Signals from the implanted intramuscular electrodes exhibited less crosstalk between the various channels and had a higher Signal-to-Noise Ratio than surface electrode signals. The performance of the intramuscular EMG-based KNN controller in the VR control task showed no degradation over time, and was stable over the 6 different arm postures. Both the EMG-based KNN controller and the intact hand-based controller had 100% hand posture matching success rates, but the intact hand-based controller was slightly superior in regards to speed (trial time used) and directness of the VR hand control (path efficiency).

Conclusions

Chronically implanted intramuscular electrodes provide negligible crosstalk, high SNR, and substantial VR control performance, including the ability to use a fixed controller over 12 weeks and under different arm positions. This approach can thus be a highly effective platform for advanced, multi-DOF prosthetic control.

Intuitive neuromyoelectric control of a dexterous bionic arm using a modified Kalman filter

BACKGROUND

Multi-articulate prostheses are capable of performing dexterous hand movements. However, clinically available control strategies fail to provide users with intuitive, independent and proportional control over multiple degrees of freedom (DOFs) in real-time.

NEW METHOD

We detail the use of a modified Kalman filter (MKF) to provide intuitive, independent and proportional control over six-DOF prostheses such as the DEKA "LUKE" arm. Input features include neural firing rates recorded from Utah Slanted Electrode Arrays and mean absolute value of intramuscular electromyographic (EMG) recordings. Ad-hoc modifications include thresholds and non-unity gains on the output of a Kalman filter.

RESULTS

We demonstrate that both neural and EMG data can be combined effectively. We also highlight that modifications can be optimized to significantly improve performance relative to an unmodified Kalman filter. Thresholds significantly reduced unintended movement and promoted more independent control of the different DOFs. Gains were significantly greater than one and served to ease movement initiation. Optimal modifications can be determined quickly offline and translate to functional improvements online. Using a portable take-home system, participants performed various activities of daily living.

COMPARISON WITH EXISTING METHODS

In contrast to pattern recognition, the MKF allows users to continuously modulate their force output, which is critical for fine dexterity. The MKF is also computationally efficient and can be trained in less than five minutes.

CONCLUSIONS

The MKF can be used to explore the functional and psychological benefits associated with long-term, at-home control of dexterous prosthetic hands.

Concepts in Neural Stimulation: Electrical and Optical Modulation of the Auditory Pathways

Understanding the mechanisms of neural stimulation is necessary to improve the management of sensory disorders. Neurons can be artificially stimulated using electrical current, or with newer stimulation modalities, including optogenetics. Electrical stimulation forms the basis for all neuroprosthetic devices that are used clinically. Off-target stimulation and poor implant performance remain concerns for patients with electrically based neuroprosthetic devices. Optogenetic techniques may improve cranial nerve stimulation strategies used by various neuroprostheses and result in better patient outcomes. This article reviews the fundamentals of neural stimulation and provides an overview of recent major advancements in light-based neuromodulation."

The use of intracranial recordings to decode human language: Challenges and opportunities

Decoding speech from intracranial recordings serves two main purposes: understanding the neural correlates of speech processing and decoding speech features for targeting speech neuroprosthetic devices. Intracranial recordings have high spatial and temporal resolution, and thus offer a unique opportunity to investigate and decode the electrophysiological dynamics underlying speech processing. In this review article, we describe current approaches to decoding different features of speech perception and production - such as spectrotemporal, phonetic, phonotactic, semantic, and articulatory components - using intracranial recordings. A specific section is devoted to the decoding of imagined speech, and potential applications to speech prosthetic devices. We outline the challenges in decoding human language, as well as the opportunities in scientific and neuroengineering applications.

Microneurography as a tool to develop decoding algorithms for peripheral neuro-controlled hand prostheses

BACKGROUND

The usability of dexterous hand prostheses is still hampered by the lack of natural and effective control strategies. A decoding strategy based on the processing of descending efferent neural signals recorded using peripheral neural interfaces could be a solution to such limitation. Unfortunately, this choice is still restrained by the reduced knowledge of the dynamics of human efferent signals recorded from the nerves and associated to hand movements.

FINDINGS

To address this issue, in this work we acquired neural efferent activities from healthy subjects performing hand-related tasks using ultrasound-guided microneurography, a minimally invasive technique, which employs needles, inserted percutaneously, to record from nerve fibers. These signals allowed us to identify neural features correlated with force and velocity of finger movements that were used to decode motor intentions. We developed computational models, which confirmed the potential translatability of these results showing how these neural features hold in absence of feedback and when implantable intrafascicular recording, rather than microneurography, is performed.

CONCLUSIONS

Our results are a proof of principle that microneurography could be used as a useful tool to assist the development of more effective hand prostheses.

EMG and ENG-envelope pattern recognition for prosthetic hand control

BACKGROUND

This paper proposes a new approach for neural control of hand prostheses, grounded on pattern recognition applied to the envelope of neural signals (eENG).

NEW METHOD

The ENG envelope was computed by taking into account the amplitude and the occurrence of the spike in the neural recording. A pattern recognition algorithm applied on muscular signals was defined as a reference and a comparative analysis with traditionally adopted Spike Sorting Algorithms (SSA) for neural signals has been carried out. Method validation was divided in two parts: firstly, neural signals recorded from one amputee subject through intraneural electrodes were offline analyzed to discriminate between the two performed gestures; secondly, algorithm performance decay with the increase of the number of classes was studied through synthetic data.

RESULTS

An accuracy of 98.26% with real data was reached with the pattern recognition applied to eENG. SSA reached an accuracy of 70%. Increasing the number of classes worsens the accuracy of this algorithm. Additionally, computational time for the pattern recognition applied to eENG is very low (32.6 μs for each sample in the data window analyzed).

COMPARISON WITH EXISTING METHOD

The eENG was proved to be more reliable in decoding the user intention than the SSA algorithm and it is computationally efficient.

CONCLUSIONS

It was demonstrated that it is possible to apply the well-known techniques of EMG pattern recognition to a conveniently processed neural signal and can pave the way to the application of neural gesture decoding in upper limb prosthetics.

Sensory percepts induced by microwire array and DBS microstimulation in human sensory thalamus

BACKGROUND

Microstimulation in human sensory thalamus (ventrocaudal, VC) results in focal sensory percepts in the hand and arm which may provide an alternative target site (to somatosensory cortex) for the input of prosthetic sensory information. Sensory feedback to facilitate motor function may require simultaneous or timed responses across separate digits to recreate perceptions of slip as well as encoding of intensity variations in pressure or touch.

OBJECTIVES

To determine the feasibility of evoking sensory percepts on separate digits with variable intensity through either a microwire array or deep brain stimulation (DBS) electrode, recreating "natural" and scalable percepts relating to the arm and hand.

METHODS

We compared microstimulation within ventrocaudal sensory thalamus through either a 16-channel microwire array (∼400 kΩ per channel) or a 4-channel DBS electrode (∼1.2 kΩ per contact) for percept location, size, intensity, and quality sensation, during thalamic DBS electrode placement in patients with essential tremor.

RESULTS

Percepts in small hand or finger regions were evoked by microstimulation through individual microwires and in 5/6 patients sensation on different digits could be perceived from stimulation through separate microwires. Microstimulation through DBS electrode contacts evoked sensations over larger areas in 5/5 patients, and the apparent intensity of the perceived response could be modulated with stimulation amplitude. The perceived naturalness of the sensation depended both on the pattern of stimulation as well as intensity of the stimulation.

CONCLUSIONS

Producing consistent evoked perceptions across separate digits within sensory thalamus is a feasible concept and a compact alternative to somatosensory cortex microstimulation for prosthetic sensory feedback. This approach will require a multi-element low impedance electrode with a sufficient stimulation range to evoke variable intensities of perception and a predictable spread of contacts to engage separate digits.

Laboratory and clinical reliability of conformally coated subretinal implants

Despite recent developments and new treatments in ophthalmology there is nothing available to cure retinal degenerations like Retinitis Pigmentosa (RP) yet. One of the most advanced approaches to treat people that have gone blind due to RP is to replace the function of the degenerated photoreceptors by a microelectronic neuroprosthetic device. Basically, this subretinal active implant transforms the incoming light into electric pulses to stimulate the remaining cells of the retina. The functional time of such devices is a crucial aspect. In this paper the laboratory and clinical reliability of the two active subretinal implants Alpha IMS and Alpha AMS is presented. Based on clinical data the median operating life of the Alpha AMS is estimated to be 3.3 years with a one-sided lower 75 % confidence level of 2.0 years. This data shows a significant improvement of the device lifetime compared to the previous device Alpha IMS which shows a median lifetime of 0.6 years with a lower confidence bound (75 %) of 0.5 years. The results are in good agreement with laboratory data from accelerated aging tests of the implant components, showing an estimated median lifetime for Alpha IMS components of 0.7 years compared to the improved lifetime of Alpha AMS of 4.7 years.

Transfer characteristics of subretinal visual implants: corneally recorded implant responses

PURPOSE

The subretinal Alpha IMS visual implant is a CE-approved medical device for restoration of visual functions in blind patients with end-stage outer retina degeneration. We present a method to test the function of the implant objectively in vivo using standard electroretinographic equipment and to assess the devices' parameter range for an optimal perception.

METHODS

Subretinal implant Alpha IMS (Retina Implant AG, Reutlingen, Germany) consists of 1500 photodiode-amplifier-electrode units and is implanted surgically into the subretinal space in blind retinitis pigmentosa patients. The voltages that regulate the amplifiers' sensitivity (V _gl) and gain (V _bias), related to the perception of contrast and brightness, respectively, are adjusted manually on a handheld power supply device. Corneally recorded implant responses (CRIR) to full-field illumination with long duration flashes in various implant settings for brightness gain (V _bias) and amplifiers' sensitivity (V _gl) are measured using electroretinographic setup with a Ganzfeld bowl in a protocol of increasing stimulus luminances up to 1000 cd/m².

RESULTS

CRIRs are a meaningful tool for assessing the transfer characteristic curves of the electronic implant in vivo monitoring the implants' voltage output as a function of log luminance in a sigmoidal shape. Changing the amplifiers' sensitivity (V _gl) shifts the curve left or right along the log luminance axis. Adjustment of the gain (V _bias) changes the maximal output. Contrast perception is only possible within the luminance range of the increasing slope of the function.

CONCLUSIONS

The technical function of subretinal visual implants can be measured objectively using a standard electroretinographic setup. CRIRs help the patient to optimise the perception by adjusting the gain and luminance range of the device and are a useful tool for clinicians to objectively assess the function of subretinal visual implants in vivo.

Neuroprosthetics in amputee and brain injury rehabilitation

The goals of rehabilitation medicine programs are to promote health, restore functional impairments and improve quality of life. The field of neuroprosthetics has evolved over the last decade given an improved understanding of neuroscience and the incorporation of advanced biotechnology and neuroengineering in the rehabilitation setting to develop adaptable applications to help facilitate recovery for individuals with amputations and brain injury. These applications may include a simple cognitive prosthetics aid for impaired memory in brain-injured individuals to myoelectric prosthetics arms with artificial proprioceptive feedback for those with upper extremity amputations. The integration of neuroprosthetics into the existing framework of current rehabilitation approaches not only improves quality-of-care and outcomes but help broadens current rehabilitation treatment paradigms. Although, we are in the infancy of the understanding the true benefit of neuroprosthetics and its clinical applications in the rehabilitation setting there is tremendous amount of promise for future research and development of tools to help facilitate recovery and improve quality of life in individuals with disabilities.

FES-induced co-activation of antagonist muscles for upper limb control and disturbance rejection

Control systems for human movement based on Functional Electrical Stimulation (FES) have shown to provide excellent performance in different experimental setups. Nevertheless, there is still a limited number of such applications available today on worldwide markets, indicating poor performance in real settings, particularly for upper limb rehabilitation and assistance. Based on these premises, in this paper we explore the use of an alternative control strategy based on co-activation of antagonist muscles using FES. Although co-contraction may accelerate fatigue when compared to single-muscle activation, knowledge from motor control indicate it may be useful for some applications. We have performed a simulation and experimental study designed to evaluate whether controllers that integrate such features can modulate joint impedance and, by doing so, improving performance with respect to disturbance rejection. The simulation results, obtained using a novel model including proprioceptive feedback and anatomical data, indicate that both stiffness and damping components of joint impedance may be modulated by using FES-induced co-activation of antagonist muscles. Preliminary experimental trials were conducted on four healthy subjects using surface electrodes. While the simulation investigation predicted a maximum 494% increase in joint stiffness for wrist flexion/extension, experiments provided an average elbow stiffness increase of 138% using lower stimulation intensity. Closed-loop experiments in which disturbances were applied have demonstrated that improved behavior may be obtained, but increased joint stiffness and other issues related to simultaneous stimulation of antagonist muscles may indeed produce greater errors.

Comparison of Twitch Responses During Current- or Voltage-Controlled Transcutaneous Neuromuscular Electrical Stimulation

Neuromuscular electrical stimulation (NMES) is an established method for functional restoration of muscle function, rehabilitation, and diagnostics. In this work, NMES was applied with surface electrodes placed on the anterior thigh to identify the main differences between current-controlled (CC) and voltage-controlled (VC) modes. Measurements of the evoked knee extension force and the myoelectric signal of quadriceps and hamstrings were taken during stimulation with different amplitudes, pulse widths, and stimulation techniques. The stimulation pulses were rectangular and symmetric biphasic for both stimulation modes. The electrode-tissue impedance influences the differences between CC and VC stimulation. The main difference is that for CC stimulation, variation of pulse width and amplitude influences the amount of nerve depolarization, whereas VC stimulation is only dependent on amplitude variations for pulse widths longer than 150 μs. An important remark is that these findings are strongly dependent on the characteristics of the electrode-skin interface. In our case, we used large stimulation electrodes placed on the anterior thigh, which cause higher capacitive effects. The controllability, voltage compliance, and charge characteristics of each stimulation technique should be considered during the stimulators design. For applications that require the activation of a large amount of nerve fibers, VC is a more suitable option. In contrast, if the application requires a high controllability, then CC should be chosen prior to VC.

The adaptive drop foot stimulator - Multivariable learning control of foot pitch and roll motion in paretic gait

Many stroke patients suffer from the drop foot syndrome, which is characterized by a limited ability to lift (the lateral and/or medial edge of) the foot and leads to a pathological gait. In this contribution, we consider the treatment of this syndrome via functional electrical stimulation (FES) of the peroneal nerve during the swing phase of the paretic foot. A novel three-electrodes setup allows us to manipulate the recruitment of m. tibialis anterior and m. fibularis longus via two independent FES channels without violating the zero-net-current requirement of FES. We characterize the domain of admissible stimulation intensities that results from the nonlinearities in patients' stimulation intensity tolerance. To compensate most of the cross-couplings between the FES intensities and the foot motion, we apply a nonlinear controller output mapping. Gait phase transitions as well as foot pitch and roll angles are assessed in realtime by means of an Inertial Measurement Unit (IMU). A decentralized Iterative Learning Control (ILC) scheme is used to adjust the stimulation to the current needs of the individual patient. We evaluate the effectiveness of this approach in experimental trials with drop foot patients walking on a treadmill and on level ground. Starting from conventional stimulation parameters, the controller automatically determines individual stimulation parameters and thus achieves physiological foot pitch and roll angle trajectories within at most two strides.

Implantable neurotechnologies: bidirectional neural interfaces--applications and VLSI circuit implementations

A bidirectional neural interface is a device that transfers information into and out of the nervous system. This class of devices has potential to improve treatment and therapy in several patient populations. Progress in very large-scale integration has advanced the design of complex integrated circuits. System-on-chip devices are capable of recording neural electrical activity and altering natural activity with electrical stimulation. Often, these devices include wireless powering and telemetry functions. This review presents the state of the art of bidirectional circuits as applied to neuroprosthetic, neurorepair, and neurotherapeutic systems.

Towards real-time communication between in vivo neurophysiological data sources and simulator-based brain biomimetic models

Development of more sophisticated implantable brain-machine interface (BMI) will require both interpretation of the neurophysiological data being measured and subsequent determination of signals to be delivered back to the brain. Computational models are the heart of the machine of BMI and therefore an essential tool in both of these processes. One approach is to utilize brain biomimetic models (BMMs) to develop and instantiate these algorithms. These then must be connected as hybrid systems in order to interface the BMM with in vivo data acquisition devices and prosthetic devices. The combined system then provides a test bed for neuroprosthetic rehabilitative solutions and medical devices for the repair and enhancement of damaged brain. We propose here a computer network-based design for this purpose, detailing its internal modules and data flows. We describe a prototype implementation of the design, enabling interaction between the Plexon Multichannel Acquisition Processor (MAP) server, a commercial tool to collect signals from microelectrodes implanted in a live subject and a BMM, a NEURON-based model of sensorimotor cortex capable of controlling a virtual arm. The prototype implementation supports an online mode for real-time simulations, as well as an offline mode for data analysis and simulations without real-time constraints, and provides binning operations to discretize continuous input to the BMM and filtering operations for dealing with noise. Evaluation demonstrated that the implementation successfully delivered monkey spiking activity to the BMM through LAN environments, respecting real-time constraints.

Proceedings of the Seventh International Workshop on Advances in Electrocorticography

The Seventh International Workshop on Advances in Electrocorticography (ECoG) convened in Washington, DC, on November 13-14, 2014. Electrocorticography-based research continues to proliferate widely across basic science and clinical disciplines. The 2014 workshop highlighted advances in neurolinguistics, brain-computer interface, functional mapping, and seizure termination facilitated by advances in the recording and analysis of the ECoG signal. The following proceedings document summarizes the content of this successful multidisciplinary gathering.

Subretinal Visual Implant Alpha IMS--Clinical trial interim report

A subretinal visual implant (Alpha IMS, Retina Implant AG, Reutlingen, Germany) was implanted in 29 blind participants with outer retinal degeneration in an international multicenter clinical trial. Primary efficacy endpoints of the study protocol were a significant improvement of activities of daily living and mobility to be assessed by activities of daily living tasks, recognition tasks, mobility, or a combination thereof. Secondary efficacy endpoints were a significant improvement of visual acuity/light perception and/or object recognition (clinicaltrials.gov, NCT01024803). During up to 12 months observation time twenty-one participants (72%) reached the primary endpoints, of which thirteen participants (45%) reported restoration of visual function which they use in daily life. Additionally, detection, localization, and identification of objects were significantly better with the implant power switched on in the first 3 months. Twenty-five participants (86%) reached the secondary endpoints. Measurable grating acuity was up to 3.3 cycles per degree, visual acuities using standardized Landolt C-rings were 20/2000, 20/2000, 20/606 and 20/546. Maximal correct motion perception ranged from 3 to 35 degrees per second. These results show that subretinal implants can restore very-low-vision or low vision in blind (light perception or less) patients with end-stage hereditary retinal degenerations.

Proceedings of the Fifth International Workshop on Advances in Electrocorticography

The Fifth International Workshop on Advances in Electrocorticography convened in San Diego, CA, on November 7-8, 2013. Advancements in methodology, implementation, and commercialization across both research and in the interval year since the last workshop were the focus of the gathering. Electrocorticography (ECoG) is now firmly established as a preferred signal source for advanced research in functional, cognitive, and neuroprosthetic domains. Published output in ECoG fields has increased tenfold in the past decade. These proceedings attempt to summarize the state of the art.

Restoring tactile and proprioceptive sensation through a brain interface

Somatosensation plays a critical role in the dexterous manipulation of objects, in emotional communication, and in the embodiment of our limbs. For upper-limb neuroprostheses to be adopted by prospective users, prosthetic limbs will thus need to provide sensory information about the position of the limb in space and about objects grasped in the hand. One approach to restoring touch and proprioception consists of electrically stimulating neurons in somatosensory cortex in the hopes of eliciting meaningful sensations to support the dexterous use of the hands, promote their embodiment, and perhaps even restore the affective dimension of touch. In this review, we discuss the importance of touch and proprioception in everyday life, then describe approaches to providing artificial somatosensory feedback through intracortical microstimulation (ICMS). We explore the importance of biomimicry--the elicitation of naturalistic patterns of neuronal activation--and that of adaptation--the brain's ability to adapt to novel sensory input, and argue that both biomimicry and adaptation will play a critical role in the artificial restoration of somatosensation. We also propose that the documented re-organization that occurs after injury does not pose a significant obstacle to brain interfaces. While still at an early stage of development, sensory restoration is a critical step in transitioning upper-limb neuroprostheses from the laboratory to the clinic.

Decoding fingertip trajectory from electrocorticographic signals in humans

Seeking to apply brain-machine interface technology in neuroprosthetics, a number of methods for predicting trajectory of the elbow and wrist have been proposed and have shown remarkable results. Recently, the prediction of hand trajectory and classification of hand gestures or grasping types have attracted considerable attention. However, trajectory prediction for precise finger motion has remained a challenge. We proposed a method for the prediction of fingertip motions from electrocorticographic signals in human cortex. A patient performed extension/flexion tasks with three fingers. Average Pearson's correlation coefficients and normalized root-mean-square errors between decoded and actual trajectories were 0.83-0.90 and 0.24-0.48, respectively. To confirm generalizability to other users, we applied our method to the BCI Competition IV open data sets. Our method showed that the prediction accuracy of fingertip trajectory could be equivalent to that of other results in the competition.

Proceedings of the Fourth International Workshop on Advances in Electrocorticography

The Fourth International Workshop on Advances in Electrocorticography (ECoG) convened in New Orleans, LA, on October 11-12, 2012. The proceedings of the workshop serves as an accurate record of the most contemporary clinical and experimental work on brain surface recording and represents the insights of a unique multidisciplinary ensemble of expert clinicians and scientists. Presentations covered a broad range of topics, including innovations in passive functional mapping, increased understanding of pathologic high-frequency oscillations, evolving sensor technologies, a human trial of ECoG-driven brain-machine interface, as well as fresh insights into brain electrical stimulation.

Corticospinal neuroprostheses to restore locomotion after spinal cord injury

In this conceptual review, we highlight our strategy for, and progress in the development of corticospinal neuroprostheses for restoring locomotor functions and promoting neural repair after thoracic spinal cord injury in experimental animal models. We specifically focus on recent developments in recording and stimulating neural interfaces, decoding algorithms, extraction of real-time feedback information, and closed-loop control systems. Each of these complex neurotechnologies plays a significant role for the design of corticospinal neuroprostheses. Even more challenging is the coordinated integration of such multifaceted technologies into effective and practical neuroprosthetic systems to improve movement execution, and augment neural plasticity after injury. In this review we address our progress in rodent animal models to explore the viability of a technology-intensive strategy for recovery and repair of the damaged nervous system. The technical, practical, and regulatory hurdles that lie ahead along the path toward clinical applications are enormous - and their resolution is uncertain at this stage. However, it is imperative that the discoveries and technological developments being made across the field of neuroprosthetics do not stay in the lab, but instead reach clinical fruition at the fastest pace possible.

Sleep, neuroengineering and dynamics

Modeling of consciousness-related phenomena and neuroengineering are fields that are rapidly growing together. We review recent approaches and developments and point out some promising directions of future research: Understanding the dynamics of consciousness states and associated oscillations, pathological oscillations as well as their treatment by stimulation, neuroprosthetics and brain-computer-interface approaches, and stimulation approaches that probe, influence and strengthen memory consolidation. In all these fields, computational models connect theory, neurophysiology and neuroengineering research and pave a way towards medical applications.