Electromyography (EMG) is a popular human-machine interface for hand gesture control of assistive and rehabilitative technology. EMG can be used to estimate motor intent even when an individual cannot physically move due to weakness or paralysis. EMG is traditionally recorded from the extrinsic hand muscles located in the forearm. However, the wrist has become an increasingly attractive recording location for commercial applications as EMG sensors can be integrated into wrist-worn wearables (e.g., watches, bracelets). Here we explored the impact that recording EMG from the wrist, instead of the forearm, has on stroke patients with upper-limb hemiparesis. We show that EMG signal-to-noise ratio is significantly worse at the paretic wrist relative to the paretic forearm and non-paretic wrist. Despite this, we also show that the ability to classify hand gestures from EMG was significantly better at the paretic wrist relative to the paretic forearm. Our results also provide guidance as to the ideal gestures for each recording location. Namely, single-digit gestures appeared easiest to classify from both forearm and wrist EMG on the paretic side. These results suggest commercialization of wrist-worn EMG would benefit stroke patients by providing more accurate EMG control in a more widely adopted wearable formfactor.
Bypass sockets allow researchers to perform tests of prosthetic systems from the prosthetic user's perspective. We designed a modular upper-limb bypass socket with 3D-printed components that can be easily modified for use with a variety of terminal devices. Our bypass socket preserves access to forearm musculature and the hand, which are necessary for surface electromyography and to provide substituted sensory feedback. Our bypass socket allows a sufficient range of motion to complete tasks in the frontal working area, as measured on non-amputee participants. We examined the performance of non-amputee participants using the bypass socket on the original and modified Box and Block Tests. Participants moved 11.3 +/- 2.7 and 11.7 +/- 2.4 blocks in the original and modified Box and Block Tests (mean +/- SD), respectively, within the range of reported scores using amputee participants. Range-of-motion for users wearing the bypass socket meets or exceeds most reported range-of-motion requirements for activities of daily living. The bypass socket was originally designed with a freely rotating wrist; we found that adding elastic resistance to user wrist rotation while wearing the bypass socket had no significant effect on motor decode performance. We have open-sourced the design files and an assembly manual for the bypass socket. We anticipate that the bypass socket will be a useful tool to evaluate and develop sensorized myoelectric prosthesis technology.
Objective: This paper aims to demonstrate functional discriminability among restored hand sensations with different locations, qualities, and intensities that are evoked by microelectrode stimulation of residual afferent fibers in human amputees. Methods: We implanted a Utah Slanted Electrode Array (USEA) in the median and ulnar residual arm nerves of three transradial amputees and delivered stimulation via different electrodes and at different frequencies to produce various locations, qualities, and intensities of sensation on the missing hand. Blind discrimination trials were performed to determine how well subjects could discriminate among these restored sensations. Results: Subjects discriminated among restored sensory percepts with varying cutaneous and proprioceptive locations, qualities, and intensities in blind trials, including discrimination among up to 10 different location-intensity combinations (15/30 successes, p < 0.0005). Variations in the site of stimulation within the nerve, via electrode selection, enabled discrimination among up to 5 locations and qualities (35/35 successes, p < 0.0001). Variations in the stimulation frequency enabled discrimination among 4 different intensities at the same location (13/20 successes, p < 0.005). One subject discriminated among simultaneous, alternating, and isolated stimulation of two different USEA electrodes, as may be desired during multi-sensor closed-loop prosthesis use (20/25 successes, p < 0.001). Conclusion: USEA stimulation enables encoding of a diversity of functionally discriminable sensations with different locations, qualities, and intensities. Significance: These percepts provide a potentially rich source of sensory feedback that may enhance performance and embodiment during multi-sensor, closed-loop prosthesis use.
In modern Electrical Engineering degree programs, MATLAB is often one of the first coding experiences a student is exposed to.Most introductory robotics courses that combine hardware and software require students to understand C (typically learned during junior year) or require part of the course to teach coding syntax.In order to introduce robotics and cyber-physical systems earlier in the curriculum, we have developed an interface to allow students to remotely control a wireless microcontroller (e.g., Arduino MKR 1010) using MATLAB.This interface comprises two halves: 1) a MATLAB class that abstracts UDP commands transmitted over Wi-Fi, and 2) a custom C++ library for receiving, parsing, and responding to commands over UDP, as well as streaming data back to the client.The interface leverages students' existing knowledge of MATLAB and bypasses the need for C programming, allowing students to get early exposure to hardware-software integration, signal processing, edge computing, end-to-end platform development, and systems engineering.Our interface facilitates data observation, recording, manipulation, and analysis.Students have access to live data streams, real-time plots of sensor values, and the ability to use the command window to run and test individual commands outside of scripts.We deployed this system in an introductory class where students perform various mechatronic lab exercises and complete a final project where their robot navigates a maze then collects and classifies objects using sensor data and neural networks.We surveyed two semesters of students at the end of the course, and students reported that using this interface enhanced their learning experience despite varied responses about the difficulty of implementation.With the growing importance of data science in electrical engineering, tools like our interface play a crucial role in exposing students to cutting-edge robotics and cyber-physical systems earlier in the degree program.Our interface has been made available on GitHub for any who wishes to implement it.
Significant advancements and refinement of neurological imaging modalities can enable new understanding in nervous system organization. One recent example, diffusible iodine-based contrast-enhanced computed tomography (diceCT), is an iodine staining and X-ray μCT-imaging technique that allows for the differentiation of myelinated from unmyelinated nervous tissues at finer scales of spatial resolution than standard three-dimensional (3D) brain-imaging tools allow. DiceCT is versatile, capable of imaging specimens across several orders of magnitude in size. It enables large and complex structures such as human brains to be studied alongside those of less complex nervous systems (e.g., fish, frogs, rodents, birds). One key feature is that the staining agent can be removed, allowing the subsequent application of acetate, fluorescent, and immunofluorescent histology following diceCT imaging. Nevertheless, the relative novelty of diceCT as a neuroanatomical visualization tool also demands ground-truthing by determining its practical reliably for distinguishing precise boundaries between brain structures. For example, some adjacent, tissue-level neuroanatomical features are poorly differentiated due to staining similarity or inherently obscure boundaries (such as the thalamus, which houses many small white-matter tracts). To address this, we compare 3D orientation-matched image stacks of diceCT juvenile Sprague Dawley rat brains to the Paxinos and Watson atlas, a gold-standard rat-brain reference. Visual identification of brain structures was attempted for all brain regions. Cardinal boundaries for each structure's dorsal, ventral, medial, and lateral edges were scored as distinguishable or non-distinguishable. Right/left staining asymmetries were also scored. We used this outline to compare and contrast the neuroanatomical structures identified by diceCT with those described by Paxinos and Watson. Preliminary results indicate that 42% of all scored structures were visible via most (e.g., 3-4) of their cardinal boundaries, whereas 25% of atlas structures showed no distinguishable boundaries using diceCT. Overall, diceCT rat-brain sections align well with standard histological sections, and visibility of neuroanatomical features is similar to tissue-based, 3D magnetic resonance imaging atlases of comparable resolution.
Abstract This paper describes a portable, prosthetic control system for at-home use of an advanced bionic arm. The system uses a modified Kalman filter to provide 6 degree-of-freedom, real-time, proportional control. We describe (a) how the system trains motor control algorithms for use with an advanced bionic arm, and (b) the system’s ability to record an unprecedented and comprehensive dataset of EMG, hand positions and force sensor values. Intact participants and a transradial amputee used the system to perform activities-of-daily-living, including bi-manual tasks, in the lab and at home. This technology enables at-home dexterous bionic arm use, and provides a high-temporal resolution description of daily use—essential information to determine clinical relevance and improve future research for advanced bionic arms.
We quantified prosthesis embodiment and phantom pain reduction associated with motor control and sensory feedback from a prosthetic hand in one human with a long-term transradial amputation. Microelectrode arrays were implanted in the residual median and ulnar arm nerves and intramuscular electromyography recording leads were implanted in residual limb muscles to enable sensory feedback and motor control. Objective measures (proprioceptive drift) and subjective measures (survey answers) were used to assess prosthesis embodiment. For both measures, there was a significant level of embodiment of the physical prosthetic limb after open-loop motor control of the prosthesis (i.e., without sensory feedback), open-loop sensation from the prosthesis (i.e., without motor control), and closed-loop control of the prosthesis (i.e., motor control with sensory feedback). There was also a statistically significant reduction in reported phantom pain after experimental sessions that included open-loop nerve microstimulation, open-loop prosthesis motor control, or closed-loop prosthesis motor control. The closed-loop condition provided no additional significant improvements in phantom pain reduction or prosthesis embodiment relative to the open-loop sensory condition or the open-loop motor condition. This study represents the first long-term (14-month), systematic report of phantom pain reduction and prosthesis embodiment in a human amputee across a variety of prosthesis use cases.
A family of processors developed at NRL [R. A. Wagstaff, ‘‘The WISPR Filter: A method for exploiting fluctuations to achieve improved sonar signal processor performance,’’ (submitted to J. Acoust. Soc. Am.)] have been shown in data analyses to yield gains in signal-to-noise ratios, and detect weak signals buried in noise. These processors take advantage of the notion that signals from submerged sources (especially those which undergo relatively fewer interactions with the surface) are relatively steady though they may be weak, but ambient noise has greater fluctuations. Simulations using synthetic data have been done to verify the validity of the above premises, and to assess the performance of the family of filters collectively called ‘‘WISPR’’ under several environments. The simulations are also compared with analyses of experimental data. The results of the simulations and the experimental analyses will be discussed. [Work supported by ONR.]
Multiarticulate bionic arms are now capable of mimicking the endogenous movements of the human hand. 3D-printing has reduced the cost of prosthetic hands themselves, but there is currently no low-cost alternative to dexterous electromyographic (EMG) control systems. To address this need, we developed an inexpensive (~$675) and portable EMG control system by integrating low-cost microcontrollers with a six-channel surface EMG (sEMG) acquisition device. Using this low-cost control system, we quantify, in a pilot study, the performance of a common EMG-based control algorithm-the modified Kalman filter (MKF)-when computational resources and electrode count are limited. We also demonstrate the ability to provide proportional and independent control of various six-degree-of-freedom prosthetic hands in real-time using the MKF. We found no significant differences in the signal-to-noise ratio (SNR) of the low-cost control system and that of a high-end research-grade system (paired t-tests). We also found no significant difference in the Root Mean Squared Errors (RMSEs) of predicted hand movements for the low-cost control system and that of the research-grade system when using only six sEMG electrodes. We then demonstrate that the SNR of the low-cost control system is statistically no worse than 44% of the SNR of the research-grade system (equivalence tests). Likewise, we demonstrate that RMSEs were typically a few percent better than, and statistically not more than 6% worse than, RMSEs of a research-grade system. This held true even when controlling up to six degrees of freedom on a prosthetic hand. Despite minimal computational resources and only six sEMG electrodes, the system performs satisfactorily and highlights the practicality and efficiency of the modified Kalman filter for dexterous EMG-based control. Successful deployment of this low-cost control system constitutes an important step towards the commercialization and wide-spread availability of dexterous bionic hands.
Electrical stimulation of residual nerves can be used to provide amputees with intuitive sensory feedback. An important aspect of this artificial sensory feedback is the ability to convey the magnitude of tactile stimuli. Using classical psychophysical methods, we quantified the just-noticeable differences for electrocutaneous stimulation pulse frequency in both intact participants and one transradial amputee. For the transradial amputee, we also quantified the just-noticeable difference of intraneural microstimulation pulse frequency via chronically implanted Utah Slanted Electrode Arrays. We demonstrate that intensity discrimination is similar across conditions: intraneural microstimulation of the residual nerves, electrocutaneous stimulation of the reinnervated skin on the residual limb, and electrocutaneous stimulation of intact hands. We also show that intensity discrimination performance is significantly better at lower pulse frequencies than at higher ones - a finding that's unique to electrocutaneous and intraneural stimulation and suggests that supplemental sensory cues may be present at lower pulse frequencies. These results can help guide the implementation of artificial sensory feedback for sensorized bionic arms.
