The future of upper extremity rehabilitation robotics: research and practice

The loss of upper limb motor function can have a devastating effect on people’s lives. To restore upper limb control and functionality, researchers and clinicians have developed interfaces to interact directly with the human body’s motor system. In this invited review, we aim to provide details on the peripheral nerve interfaces and brain‐machine interfaces that have been developed in the past 30 years for upper extremity control, and we highlight the challenges that still remain to transition the technology into the clinical market. The findings show that peripheral nerve interfaces and brain‐machine interfaces have many similar characteristics that enable them to be concurrently developed. Decoding neural information from both interfaces may lead to novel physiological models that may one day fully restore upper limb motor function for a growing patient population.Peer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/155489/1/mus26860_am.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/155489/2/mus26860.pd

Design and testing of a 96-channel neural interface module for the Networked Neuroprosthesis system

Abstract Background The loss of motor functions resulting from spinal cord injury can have devastating implications on the quality of one’s life. Functional electrical stimulation has been used to help restore mobility, however, current functional electrical stimulation (FES) systems require residual movements to control stimulation patterns, which may be unintuitive and not useful for individuals with higher level cervical injuries. Brain machine interfaces (BMI) offer a promising approach for controlling such systems; however, they currently still require transcutaneous leads connecting indwelling electrodes to external recording devices. While several wireless BMI systems have been designed, high signal bandwidth requirements limit clinical translation. Case Western Reserve University has developed an implantable, modular FES system, the Networked Neuroprosthesis (NNP), to perform combinations of myoelectric recording and neural stimulation for controlling motor functions. However, currently the existing module capabilities are not sufficient for intracortical recordings. Methods Here we designed and tested a 1 × 4 cm, 96-channel neural recording module prototype to fit within the specifications to mate with the NNP. The neural recording module extracts power between 0.3–1 kHz, instead of transmitting the raw, high bandwidth neural data to decrease power requirements. Results The module consumed 33.6 mW while sampling 96 channels at approximately 2 kSps. We also investigated the relationship between average spiking band power and neural spike rate, which produced a maximum correlation of R = 0.8656 (Monkey N) and R = 0.8023 (Monkey W). Conclusion Our experimental results show that we can record and transmit 96 channels at 2ksps within the power restrictions of the NNP system and successfully communicate over the NNP network. We believe this device can be used as an extension to the NNP to produce a clinically viable, fully implantable, intracortically-controlled FES system and advance the field of bioelectronic medicine.https://deepblue.lib.umich.edu/bitstream/2027.42/147921/1/42234_2019_Article_19.pd

Cortical Decoding of Individual Finger Group Motions Using ReFIT Kalman Filter

Objective: To date, many brain-machine interface (BMI) studies have developed decoding algorithms for neuroprostheses that provide users with precise control of upper arm reaches with some limited grasping capabilities. However, comparatively few have focused on quantifying the performance of precise finger control. Here we expand upon this work by investigating online control of individual finger groups.Approach: We have developed a novel training manipulandum for non-human primate (NHP) studies to isolate the movements of two specific finger groups: index and middle-ring-pinkie (MRP) fingers. We use this device in combination with the ReFIT (Recalibrated Feedback Intention-Trained) Kalman filter to decode the position of each finger group during a single degree of freedom task in two rhesus macaques with Utah arrays in motor cortex. The ReFIT Kalman filter uses a two-stage training approach that improves online control of upper arm tasks with substantial reductions in orbiting time, thus making it a logical first choice for precise finger control.Results: Both animals were able to reliably acquire fingertip targets with both index and MRP fingers, which they did in blocks of finger group specific trials. Decoding from motor signals online, the ReFIT Kalman filter reliably outperformed the standard Kalman filter, measured by bit rate, across all tested finger groups and movements by 31.0 and 35.2%. These decoders were robust when the manipulandum was removed during online control. While index finger movements and middle-ring-pinkie finger movements could be differentiated from each other with 81.7% accuracy across both subjects, the linear Kalman filter was not sufficient for decoding both finger groups together due to significant unwanted movement in the stationary finger, potentially due to co-contraction.Significance: To our knowledge, this is the first systematic and biomimetic separation of digits for continuous online decoding in a NHP as well as the first demonstration of the ReFIT Kalman filter improving the performance of precise finger decoding. These results suggest that novel nonlinear approaches, apparently not necessary for center out reaches or gross hand motions, may be necessary to achieve independent and precise control of individual fingers

Perturbative QCD Calculations of Total Cross Sections and Decay Widths in Hard Inclusive Processes

A summary of the current understanding of methods of analytical higher order perturbative computations of total cross sections and decay widths in Quantum Chromodynamics is presented. As examples, the total cross section in electron positron annihilation, the hadronic decay rates of the tau lepton and Higgs boson up to O(\alpha_s^2) and O(\alpha_s^3) are considered. The evaluation of the four-loop QED \beta - function at an intermediate step of the calculation is briefly described. The problem of renormalization group ambiguity of perturbative results is considered and some of the existing prescriptions are discussed. The problem of estimation of theoretical uncertainty in perturbative calculations is briefly discussed.Comment: 83 pages, LaTeX, Reviews of Modern Physics style, 14 figures plus figural equations (not included). Hard copy available upon request at [email protected]. To be published in Reviews of Modern Physic

Evolution and Phylogenetic Analysis of Full-Length VP3 Genes of Eastern Mediterranean Bluetongue Virus Isolates

Bluetongue virus (BTV) is the ‘type’ species of the genus Orbivirus within the family Reoviridae. The BTV genome is composed of ten linear segments of double-stranded RNA (dsRNA), each of which codes for one of ten distinct viral proteins. Previous phylogenetic comparisons have evaluated variations in genome segment 3 (Seg-3) nucleotide sequence as way to identify the geographical origin (different topotypes) of BTV isolates. The full-length nucleotide sequence of genome Seg-3 was determined for thirty BTV isolates recovered in the eastern Mediterranean region, the Balkans and other geographic areas (Spain, India, Malaysia and Africa). These data were compared, based on molecular variability, positive-selection-analysis and maximum-likelihood phylogenetic reconstructions (using appropriate substitution models) to 24 previously published sequences, revealing their evolutionary relationships. These analyses indicate that negative selection is a major force in the evolution of BTV, restricting nucleotide variability, reducing the evolutionary rate of Seg-3 and potentially of other regions of the BTV genome. Phylogenetic analysis of the BTV-4 strains isolated over a relatively long time interval (1979–2000), in a single geographic area (Greece), showed a low level of nucleotide diversity, indicating that the virus can circulate almost unchanged for many years. These analyses also show that the recent incursions into south-eastern Europe were caused by BTV strains belonging to two different major-lineages: representing an ‘eastern’ (BTV-9, -16 and -1) and a ‘western’ (BTV-4) group/topotype. Epidemiological and phylogenetic analyses indicate that these viruses originated from a geographic area to the east and southeast of Greece (including Cyprus and the Middle East), which appears to represent an important ecological niche for the virus that is likely to represent a continuing source of future BTV incursions into Europe

Marketing as a means to transformative social conflict resolution: lessons from transitioning war economies and the Colombian coffee marketing system

Social conflicts are ubiquitous to the human condition and occur throughout markets, marketing processes, and marketing systems.When unchecked or unmitigated, social conflict can have devastating consequences for consumers, marketers, and societies, especially when conflict escalates to war. In this article, the authors offer a systemic analysis of the Colombian war economy, with its conflicted shadow and coping markets, to show how a growing network of fair-trade coffee actors has played a key role in transitioning the country’s war economy into a peace economy. They particularly draw attention to the sources of conflict in this market and highlight four transition mechanisms — i.e., empowerment, communication, community building and regulation — through which marketers can contribute to peacemaking and thus produce mutually beneficial outcomes for consumers and society. The article concludes with a discussion of implications for marketing theory, practice, and public policy

An Energy-Efficient Spiking Neural Network for Finger Velocity Decoding for Implantable Brain-Machine Interface

Brain-machine interfaces (BMIs) are promising for motor rehabilitation and mobility augmentation. High-accuracy and low-power algorithms are required to achieve implantable BMI systems. In this paper, we propose a novel spiking neural network (SNN) decoder for implantable BMI regression tasks. The SNN is trained with enhanced spatio-temporal backpropagation to fully leverage its ability in handling temporal problems. The proposed SNN decoder achieves the same level of correlation coefficient as the state-of-the-art ANN decoder in offline finger velocity decoding tasks, while it requires only 6.8% of the computation operations and 9.4% of the memory access

The impact of task context on predicting finger movements in a brain-machine interface

A key factor in the clinical translation of brain-machine interfaces (BMIs) for restoring hand motor function will be their robustness to changes in a task. With functional electrical stimulation (FES) for example, the patient’s own hand will be used to produce a wide range of forces in otherwise similar movements. To investigate the impact of task changes on BMI performance, we trained two rhesus macaques to control a virtual hand with their physical hand while we added springs to each finger group (index or middle-ring-small) or altered their wrist posture. Using simultaneously recorded intracortical neural activity, finger positions, and electromyography, we found that decoders trained in one context did not generalize well to other contexts, leading to significant increases in prediction error, especially for muscle activations. However, with respect to online BMI control of the virtual hand, changing either the decoder training task context or the hand’s physical context during online control had little effect on online performance. We explain this dichotomy by showing that the structure of neural population activity remained similar in new contexts, which could allow for fast adjustment online. Additionally, we found that neural activity shifted trajectories proportional to the required muscle activation in new contexts. This shift in neural activity possibly explains biases to off-context kinematic predictions and suggests a feature that could help predict different magnitude muscle activations while producing similar kinematics