Objective. Myoelectric prostheses use electromyographic (EMG) signals to control movement of prosthetic joints. Clinically available myoelectric control strategies do not allow simultaneous movement of multiple degrees of freedom (DOFs); however, the use of implantable devices that record intramuscular EMG signals could overcome this constraint. The objective of this study was to evaluate the real-time simultaneous control of three DOFs (wrist rotation, wrist flexion/extension, and hand open/close) using intramuscular EMG. Approach. We evaluated task performance of five able-bodied subjects in a virtual environment using two control strategies with fine-wire EMG: (i) parallel dual-site differential control, which enabled simultaneous control of three DOFs and (ii) pattern recognition control, which required sequential control of DOFs. Main results. Over the course of the experiment, subjects using parallel dual-site control demonstrated increased use of simultaneous control and improved performance in a Fitts' Law test. By the end of the experiment, performance using parallel dual-site control was significantly better (up to a 25% increase in throughput) than when using sequential pattern recognition control for tasks requiring multiple DOFs. The learning trends with parallel dual-site control suggested that further improvements in performance metrics were possible. Subjects occasionally experienced difficulty in performing isolated single-DOF movements with parallel dual-site control but were able to accomplish related Fitts' Law tasks with high levels of path efficiency. Significance. These results suggest that intramuscular EMG, used in a parallel dual-site configuration, can provide simultaneous control of a multi-DOF prosthetic wrist and hand and may outperform current methods that enforce sequential control.
One of the hottest topics in rehabilitation robotics is that of proper control of prosthetic devices. Despite decades of research, the state of the art is dramatically behind the expectations. To shed light on this issue, in June, 2013 the first international workshop on Present and future of non-invasive peripheral nervous system (PNS)-Machine Interfaces (MI; PMI) was convened, hosted by the International Conference on Rehabilitation Robotics. The keyword PMI has been selected to denote human-machine interfaces targeted at the limb-deficient, mainly upper-limb amputees, dealing with signals gathered from the PNS in a non-invasive way, that is, from the surface of the residuum. The workshop was intended to provide an overview of the state of the art and future perspectives of such interfaces; this paper represents is a collection of opinions expressed by each and every researcher/group involved in it.
Fine-wire intramuscular electrodes were used to obtain EMG signals from six extrinsic hand muscles associated with the thumb, index, and middle fingers. Subjects' EMG activity was used to control a virtual three-DOF hand as they conformed the hand to a sequence of hand postures testing two controllers: direct EMG control and pattern recognition control. Subjects tested two conditions using each controller: starting the hand from a pre-defined neutral posture before each new posture and starting the hand from the previous posture in the sequence. Subjects demonstrated their ability to simultaneously, yet individually, move all three DOFs during the direct EMG control trials, however results showed subjects did not often utilize this feature. Performance metrics such as failure rate and completion time showed no significant difference between the two controllers.
Upper limb transplantation is a life-enhancing rather than life-saving procedure. Little research has investigated how individuals with upper limb amputations perceive the benefits and risks of this complex procedure. To address this knowledge gap, the authors conducted qualitative research with individuals with upper limb amputations to understand their perspectives.
Appropriately responding to mechanical perturbations during gait is critical to maintain balance and avoid falls. Tripping perturbation onset during swing phase is strongly related to the use of different recovery strategies; however, it is insufficient to fully explain how strategies are chosen. The dynamic interactions between the foot and the obstacle may further explain observed recovery strategies but the relationship between such contextual elements and strategy selection has not been explored. In this study, we investigated whether perturbation onset, duration and side could explain strategy selection for all of swing phase. We hypothesized that perturbations of longer duration would elicit lowering and delayed-lowering strategies earlier in swing phase than shorter perturbations. We developed a custom device to trip subjects multiple times while they walked on a treadmill. Seven young, healthy subjects were tripped on the left or right side at 10% to 80% of swing phase for 150 ms, 250 ms or 350 ms. Strategies were characterized by foot motion post-perturbation and identified by an automated algorithm. A multinomial logistic model was used to investigate the effect of perturbation onset, side, and the interaction between duration and onset on recovery strategy selection. Side perturbed did not affect strategy selection. Perturbation duration interacted with onset, limiting the use of elevating strategies to earlier in swing phase with longer perturbations. The choice between delayed-lowering and lowering strategies was not affected by perturbation duration. Although these variables did not fully explain strategy selection, they improved the prediction of strategy used in response to tripping perturbations throughout swing phase.
We present a case study of a novel variation of the targeted sensory reinnervation technique that provides additional control over sensory restoration after transhumeral amputation. The use of intraoperative somatosensory evoked potentials on individual fascicles of the median and ulnar nerves allowed us to specifically target sensory fascicles to reroute to target cutaneous nerves at a distance away from anticipated motor sites in a transhumeral amputee. This resulted in restored hand maps of the median and ulnar nerve in discrete spatially separated areas. In addition, the subject was able to use native and reinnervated muscle sites to control a robotic arm while simultaneously sensing touch and force feedback from the robotic gripper in a physiologically correct manner. This proof of principle study is the first to demonstrate the ability to have simultaneous dual flow of information (motor and sensory) within the residual limb. In working towards clinical deployment of a sensory integrated prosthetic device, this surgical method addresses the important issue of restoring a usable access point to provide natural hand sensation after upper limb amputation.
Human joint impedance is the dynamic relationship between the differential change in the position of a perturbed joint and the corresponding response torque; it is a fundamental property that governs how humans interact with their environments. It is critical to characterize ankle impedance during the stance phase of walking to elucidate how ankle impedance is regulated during locomotion, as well as provide the foundation for future development of natural, biomimetic powered prostheses and their control systems. In this study, ankle impedance was estimated using a model consisting of stiffness, damping and inertia. Ankle torque was well described by the model, accounting for 98 ±1.2% of the variance. When averaged across subjects, the stiffness component of impedance was found to increase linearly from 1.5 to 6.5 Nm/rad/kg between 20% and 70% of stance phase. The damping component was found to be statistically greater than zero only for the estimate at 70% of stance phase, with a value of 0.03 Nms/rad/kg. The slope of the ankle's torque-angle curve-known as the quasi-stiffness-was not statistically different from the ankle stiffness values, and showed remarkable similarity. Finally, using the estimated impedance, the specifications for a biomimetic powered ankle prosthesis were introduced that would accurately emulate human ankle impedance during locomotion.
Postamputation neuroma pain can prevent comfortable prosthesis wear in patients with limb amputations, and currently available treatments are not consistently effective. Targeted muscle reinnervation (TMR) is a decade-old technique that employs a series of novel nerve transfers to permit intuitive control of upper-limb prostheses. Clinical experience suggests that it may also serve as an effective therapy for postamputation neuroma pain; however, this has not been explicitly studied.
Community mobility of individuals following lower limb amputation is highly variable and has a great impact on their quality of life. Currently, clinical assessments of ambulatory ability and motivation influence prosthetic prescription. However, these outcome measures do not effectively quantify community mobility (ie, mobility outside of the clinic) of individuals with an amputation. Advances in global positioning systems (GPSs) and other wearable step-monitoring devices allow for objective, quantifiable measurement of community mobility. This case report will examine the combined use of a GPS unit and a step activity monitor to quantify community mobility and social interaction of an individual with transfemoral amputation due to dysvascular disease.
The clinical application of robotic technology to powered prosthetic knees and ankles is limited by the lack of a robust control strategy. We found that the use of electromyographic (EMG) signals from natively innervated and surgically reinnervated residual thigh muscles in a patient who had undergone knee amputation improved control of a robotic leg prosthesis. EMG signals were decoded with a pattern-recognition algorithm and combined with data from sensors on the prosthesis to interpret the patients intended movements. This provided robust and intuitive control of ambulation--with seamless transitions between walking on level ground, stairs, and ramps--and of the ability to reposition the leg while the patient was seated.
Mechanical and neurological couplings exist between musculotendon units of the human hand and digits. Studies have begun to understand how these muscles interact when accomplishing everyday tasks, but there are still unanswered questions regarding the control limitations of individual muscles. Using intramuscular electromyographic (EMG) electrodes, this study examined subjects ability to individually initiate and sustain three levels of normalized muscular activity in the index and middle finger muscle compartments of extensor digitorum communis (EDC), flexor digitorum profundus (FDP), and flexor digitorum superficialis (FDS), as well as the extrinsic thumb muscles abductor pollicis longus (APL), extensor pollicis brevis (EPB), extensor pollicis longus (EPL), and flexor pollicis longus (FPL). The index and middle finger compartments each sustained activations with significantly different levels of coactivity from the other finger muscle compartments. The middle finger compartment of EDC was the exception. Only two extrinsic thumb muscles, EPL and FPL, were capable of sustaining individual activations from the other thumb muscles, at all tested activity levels. Activation of APL was achieved at 20 and 30% MVC activity levels with significantly different levels of coactivity. Activation of EPB elicited coactivity levels from EPL and APL that were not significantly different. These results suggest that most finger muscle compartments receive unique motor commands, but of the four thumb muscles, only EPL and FPL were capable of individually activating. This work is encouraging for the neural control of prosthetic limbs because these muscles and compartments may potentially serve as additional user inputs to command prostheses.
Lower limb prostheses have traditionally been mechanically passive devices without electronic control systems. Microprocessor-controlled passive and powered devices have recently received much interest from the clinical and research communities. The control systems for these devices typically use finite-state controllers to interpret data measured from mechanical sensors embedded within the prosthesis. In this paper we investigated a control system that relied on information extracted from myoelectric signals to control a lower limb prosthesis while amputee patients were seated. Sagittal plane motions of the knee and ankle can be accurately (>90%) recognized and controlled in both a virtual environment and on an actuated transfemoral prosthesis using only myoelectric signals measured from nine residual thigh muscles. Patients also demonstrated accurate (~90%) control of both the femoral and tibial rotation degrees of freedom within the virtual environment. A channel subset investigation was completed and the results showed that only five residual thigh muscles are required to achieve accurate control. This research is the first step in our long-term goal of implementing myoelectric control of lower limb prostheses during both weight-bearing and non-weight-bearing activities for individuals with transfemoral amputation.
The mechanical properties of human joints (i.e., impedance) are constantly modulated to precisely govern human interaction with the environment. The estimation of these properties requires the displacement of the joint from its intended motion and a subsequent analysis to determine the relationship between the imposed perturbation and the resultant joint torque. There has been much investigation into the estimation of upper-extremity joint impedance during dynamic activities, yet the estimation of ankle impedance during walking has remained a challenge. This estimation is important for understanding how the mechanical properties of the human ankle are modulated during locomotion, and how those properties can be replicated in artificial prostheses designed to restore natural movement control. Here, we introduce a mechatronic platform designed to address the challenge of estimating the stiffness component of ankle impedance during walking, where stiffness denotes the static component of impedance. The system consists of a single degree of freedom mechatronic platform that is capable of perturbing the ankle during the stance phase of walking and measuring the response torque. Additionally, we estimate the platforms intrinsic inertial impedance using parallel linear filters and present a set of methods for estimating the impedance of the ankle from walking data. The methods were validated by comparing the experimentally determined estimates for the stiffness of a prosthetic foot to those measured from an independent testing machine. The parallel filters accurately estimated the mechatronic platforms inertial impedance, accounting for 96% of the variance, when averaged across channels and trials. Furthermore, our measurement system was found to yield reliable estimates of stiffness, which had an average error of only 5.4% (standard deviation: 0.7%) when measured at three time points within the stance phase of locomotion, and compared to the independently determined stiffness values of the prosthetic foot. The mechatronic system and methods proposed in this study are capable of accurately estimating ankle stiffness during the foot-flat region of stance phase. Future work will focus on the implementation of this validated system in estimating human ankle impedance during the stance phase of walking.
Previous studies have postulated that the amount of brain reorganization following peripheral injuries may be correlated with negative symptoms or consequences. However, it is unknown whether restoring effective limb function may then be associated with further changes in the expression of this reorganization. Recently, targeted reinnervation (TR), a surgical technique that restores a direct neural connection from amputated sensorimotor nerves to new peripheral targets such as muscle, has been successfully applied to upper-limb amputees. It has been shown to be effective in restoring both peripheral motor and sensory functions via the reinnervated nerves as soon as a few months after the surgery. However, it was unclear whether TR could also restore normal cortical motor representations for control of the missing limb. To answer this question, we used high-density electroencephalography (EEG) to localize cortical activity related to cued motor tasks generated by the intact and missing limb. Using a case study of 3 upper-limb amputees, 2 of whom went through pre and post-TR experiments, we present unique quantitative evidence for the re-mapping of motor representations for the missing limb closer to their original locations following TR. This provides evidence that an effective restoration of peripheral function from TR can be linked to the return of more normal cortical expression for the missing limb. Therefore, cortical mapping may be used as a potential guide for monitoring rehabilitation following peripheral injuries.
Pattern recognition of myoelectric signals for prosthesis control has been extensively studied in research settings and is close to clinical implementation. These systems are capable of intuitively controlling the next generation of dexterous prosthetic hands. However, pattern recognition systems perform poorly in the presence of electrode shift, defined as movement of surface electrodes with respect to the underlying muscles. This paper focused on investigating the optimal interelectrode distance, channel configuration, and electromyography feature sets for myoelectric pattern recognition in the presence of electrode shift. Increasing interelectrode distance from 2 to 4 cm improved pattern recognition system performance in terms of classification error and controllability (p < 0.01). Additionally, for a constant number of channels, an electrode configuration that included electrodes oriented both longitudinally and perpendicularly with respect to muscle fibers improved robustness in the presence of electrode shift (p < 0.05). We investigated the effect of the number of recording channels with and without electrode shift and found that four to six channels were sufficient for pattern recognition control. Finally, we investigated different feature sets for pattern recognition control using a linear discriminant analysis classifier and found that an autoregressive set significantly (p < 0.01) reduced sensitivity to electrode shift compared to a traditional time-domain feature set.
Surgical treatment of neuromas involves excision of neuromas proximally to the level of grossly "normal" fascicles; however, proximal changes at the axonal level may have both functional and therapeutic implications with regard to amputated nerves. In order to better understand the retrograde "zone of injury" that occurs after nerve transection, we investigated the gross and histologic changes in transected nerves using a rabbit forelimb amputation model.
Electromyography (EMG) pattern recognition offers the potential for improved control of multifunction myoelectric prostheses. However, it is unclear whether this technology can be successfully used by congenital amputees.
We explored a new method for simple and accurate control of shoulder movement for externally powered shoulder disarticulation prostheses with a two-axis joystick. We tested 10 subjects with intact shoulders and arms to determine the average amount of shoulder motion and force available to control an electronic input device. We then applied this information to two different input strategies to examine their effectiveness: (1) a traditional rocker potentiometer and a pair of force-sensing resistors and (2) a two-axis joystick. Three nondisabled subjects and two subjects with shoulder disarticulation amputations attempted to control an experimental externally powered shoulder using both control strategies. Two powered arms were tested, one with powered flexion/extension and humeral rotation and one with powered flexion/extension and adduction/abduction. Overwhelmingly, the subjects preferred the joystick control, because it was more intuitively linked with their shoulder movement. Additionally, two motions (one in each axis) could be controlled simultaneously. This pilot study provides valuable insight into an effective means of controlling high-level, externally powered prostheses with a two-axis joystick.
The ease with which persons with upper-limb amputations can control their powered prostheses is largely determined by the efficacy of the user command interface. One needs to understand the abilities of the human operator regarding the different available options. Electromyography (EMG) is widely used to control powered upper-limb prostheses. It is an indirect estimator of muscle force and may be expected to limit the control capabilities of the prosthesis user. This study compared EMG control with force control, an interface that is used in everyday interactions with the environment. We used both methods to perform a position-tracking task. Direct-position control of the wrist provided an upper bound for human-operator capabilities. The results demonstrated that an EMG control interface is as effective as force control for the position-tracking task. We also examined the effects of gain and tracking frequency on EMG control to explore the limits of this control interface. We found that information transmission rates for myoelectric control were best at higher tracking frequencies than at the frequencies previously reported for position control. The results may be useful for the design of prostheses and prosthetic controllers.
Despite high classification accuracies (~95%) of myoelectric control systems based on pattern recognition, how well offline measures translate to real-time closed-loop control is unclear. Recently, a real-time virtual test analyzed how well subjects completed arm motions using a multiple-degree of freedom (DOF) classifier. Although this test provided real-time performance metrics, the required task was oversimplified: motion speeds were normalized and unintended movements were ignored. We included these considerations in a new, more challenging virtual test called the Target Achievement Control Test (TAC Test). Five subjects with transradial amputation attempted to move a virtual arm into a target posture using myoelectric pattern recognition, performing the test with various classifier (1- vs 3-DOF) and task complexities (one vs three required motions per posture). We found no significant difference in classification accuracy between the 1- and 3-DOF classifiers (97.2% +/- 2.0% and 94.1% +/- 3.1%, respectively; p = 0.14). Subjects completed 31% fewer trials in significantly more time using the 3-DOF classifier and took 3.6 +/- 0.8 times longer to reach a three-motion posture compared with a one-motion posture. These results highlight the need for closed-loop performance measures and demonstrate that the TAC Test is a useful and more challenging tool to test real-time pattern-recognition performance.
In order to provide natural, biomimetic control to recently developed powered ankle prostheses, we must characterize the impedance of the ankle during ambulation tasks. To this end, a platform robot was developed that can apply an angular perturbation to the ankle during ambulation and simultaneously acquire ground reaction force data. In this study, we detail the design of the platform robot and characterize the impedance of the ankle during quiet standing. Subjects were perturbed by a 3° dorsiflexive ramp perturbation with a length of 150 ms. The impedance was defined parametrically, using a second order model to map joint angle to the torque response. The torque was determined using the inverted pendulum assumption, and impedance was identified by the least squares best estimate, yielding an average damping coefficient of 0.03 ± 0.01 Nms/° and an average stiffness coefficient of 3.1 ± 1.2 Nm/°. The estimates obtained by the proposed platform robot compare favorably to those published in the literature. Future work will investigate the impedance of the ankle during ambulation for powered prosthesis controller development.
In control subjects, trips during the early and late swing phase of walking elicit elevating and lowering strategies, respectively. However, the transition between these recovery strategies during mid-swing is unclear. A better understanding of this transition would provide insight into what factors cause individuals to choose one strategy over another. Three control subjects walked on a treadmill while attached to a custom-made tripping device. Perturbations of various lengths (ranging from 50 ms to 350 ms) were applied throughout the swing phase of gait. The results suggest that as perturbation length increased, the transition from elevating to lowering strategies occurred at earlier perturbation onsets. The transition period varied linearly with perturbation length. Perturbation lengths of 150 ms to 250 ms more closely replicated strategy selection in trips induced by real obstacles. Perturbations that are longer in duration force the transition from an elevating to a lowering strategy to occur at an earlier percentage of swing. These results show that perturbation length affects recovery strategy selection in response to trips.
This case study demonstrates the ability of sensory cortical representations to remap following arm amputation and subsequent targeted reinnervation (TR). Previous human studies have demonstrated functional plasticity in the primary sensory cortex months or years after amputation of the upper arm, forearm, the hand or a single finger, or after subsequent replantation. Targeted reinnervation, a surgical procedure that re-routes inactive, residual sensorimotor nerves previously responsible for innervating the missing limb to alternative muscle groups and skin areas [1-3], has shown the ability to restore a subjects sensation in the reinnervated skin areas. Whether this new technique causes analogous cortical remapping in a similar timeframe as following hand replantation is still unknown. In order to answer this question, high-density electroencephalography was used to study whether the original sensory cortical territory was regained after TR. Before TR, we found that the cortical response to sensory electrical stimulation in the residual limb showed a diffuse bilateral pattern without a clear focus in either the time or spatial domain, Two years after TR, the sensory map of the reinnervated median nerve shifted back to a close-to-normal, predominantly contralateral pattern. The overall trend of TR-induced sensory remapping is similar to previous reports related to hand replantation but occurs over a slower timeframe. This relatively slower progress after TR as compared to after hand replantation could be because TR is performed months or even years after amputation, while hand replantation was performed immediately after the injury. This work provides new evidence for long term plasticity in the human brain.
Limb transplantation and targeted reinnervation are complimentary but very different approaches for restoring function to an upper limb amputee. This article reviews the advantages and limitations of both of these procedures, and highlights the reconstructive obstacles in the treatment of upper limb amputees.
Myoelectric pattern recognition systems for prosthesis control are often studied in controlled laboratory settings, but obstacles remain to be addressed before they are clinically viable. One important obstacle is the difficulty of maintaining system usability with socket misalignment. Misalignment inevitably occurs during prosthesis donning and doffing, producing a shift in electrode contact locations. We investigated how the size of the electrode detection surface and the placement of electrode poles (electrode orientation) affected system robustness with electrode shift. Electrodes oriented parallel to muscle fibers outperformed electrodes oriented perpendicular to muscle fibers in both shift and no-shift conditions (p < 0.01). Another finding was the significant difference (p < 0.01) in performance for the direction of electrode shift. Shifts perpendicular to the muscle fibers reduced classification accuracy and real-time controllability much more than shifts parallel to the muscle fibers. Increasing the size of the electrode detection surface was found to help reduce classification accuracy sensitivity to electrode shifts in a direction perpendicular to the muscle fibers but did not improve the real-time controllability of the pattern recognition system. One clinically important result was that a combination of longitudinal and transverse electrodes yielded high controllability with and without electrode shift using only four physical electrode pole locations.
Real-time pattern recognition control is frequently affected by misclassifications. This study investigated the use of a decision-based velocity ramp that attenuated movement speed after a change in classifier decision. The goal was to improve prosthesis positioning by minimizing the effect of unintended movements. Non-amputee and amputee subjects controlled a prosthesis in real-time using pattern recognition. While performing a target achievement test in a virtual environment, subjects had a significantly higher completion rate (p < 0.05) and a more direct path (p < 0.05) to the target with the velocity ramp than without it. Using a physical prosthesis, subjects stacked a greater average number of 1 cubes (p < 0.05) in three minutes with the velocity ramp than without it (76% more blocks for non-amputees; 89% more blocks for amputees). Real-time control using the velocity ramp also showed significant performance improvements above using majority vote. Eighty-three percent of subjects preferred to control the prosthesis using the velocity ramp. These results suggest that using a decision-based velocity ramp with pattern recognition may improve user performance. Since the velocity ramp is a post-processing step, it has the potential to be used with a variety of classifiers for many applications.
In this review, we focus on environmental cleanup and provide a background and overview of current practice; research findings; societal issues; potential environment, health, and safety implications; and future directions for nanoremediation. We also discuss nanoscale zero-valent iron in detail. We searched the Web of Science for research studies and accessed recent publicly available reports from the U.S. Environmental Protection Agency and other agencies and organizations that addressed the applications and implications associated with nanoremediation techniques. We also conducted personal interviews with practitioners about specific site remediations. We aggregated information from 45 sites, a representative portion of the total projects under way, to show nanomaterials used, types of pollutants addressed, and organizations responsible for each site. Nanoremediation has the potential not only to reduce the overall costs of cleaning up large-scale contaminated sites but also to reduce cleanup time, eliminate the need for treatment and disposal of contaminated soil, and reduce some contaminant concentrations to near zero--all in situ.
Current treatment of upper limb amputation restores some degree of functional ability, but this ability falls far below the standard set by the natural arm. Although acceptance rates can be high when patients are highly motivated and receive proper training and care, current prostheses often fail to meet the daily needs of amputees and frequently are abandoned. Recent advancements in science and technology have led to promising methods of accessing neural information for communication or control. Researchers have explored invasive and noninvasive methods of connecting with muscles, nerves, or the brain to provide increased functionality for patients experiencing disease or injury, including amputation. These techniques offer hope of more natural and intuitive prosthesis control, and therefore increased quality of life for amputees. In this review, we discuss the current state of the art of neural interfaces, particularly those that may find application within the prosthetics field.
Existing prosthetic limbs do not provide amputees with cutaneous feedback. Tactile feedback is essential to intuitive control of a prosthetic limb and it is now clear that the sense of body self-identification is also linked to cutaneous touch. Here we have created an artificial sense of touch for a prosthetic limb by coupling a pressure sensor on the hand through a robotic stimulator to surgically redirected cutaneous sensory nerves (targeted reinnervation) that once served the lost limb. We hypothesize that providing physiologically relevant cutaneous touch feedback may help an amputee incorporate an artificial limb into his or her self image. To investigate this we used a robotic touch interface coupled with a prosthetic limb and tested it with two targeted reinnervation amputees in a series of experiments fashioned after the Rubber Hand Illusion. Results from both subjective (self-reported) and objective (physiological) measures of embodiment (questionnaires, psychophysical temporal order judgements and residual limb temperature measurements) indicate that returning physiologically appropriate cutaneous feedback from a prosthetic limb drives a perceptual shift towards embodiment of the device for these amputees. Measurements provide evidence that the illusion created is vivid. We suggest that this may help amputees to more effectively incorporate an artificial limb into their self image, providing the possibility that a prosthesis becomes not only a tool, but also an integrated body part.
Pattern recognition-based control of myoelectric prostheses has shown great promise in research environments, but has not been optimized for use in a clinical setting. To explore the relationship between classification error, controller delay, and real-time controllability, 13 able-bodied subjects were trained to operate a virtual upper-limb prosthesis using pattern recognition of electromyogram (EMG) signals. Classification error and controller delay were varied by training different classifiers with a variety of analysis window lengths ranging from 50 to 550 ms and either two or four EMG input channels. Offline analysis showed that classification error decreased with longer window lengths (p < 0.01 ). Real-time controllability was evaluated with the target achievement control (TAC) test, which prompted users to maneuver the virtual prosthesis into various target postures. The results indicated that user performance improved with lower classification error (p < 0.01 ) and was reduced with longer controller delay (p < 0.01 ), as determined by the window length. Therefore, both of these effects should be considered when choosing a window length; it may be beneficial to increase the window length if this results in a reduced classification error, despite the corresponding increase in controller delay. For the system employed in this study, the optimal window length was found to be between 150 and 250 ms, which is within acceptable controller delays for conventional multistate amplitude controllers.
The lack of proprioceptive feedback is a serious deficiency of current prosthetic control systems. The Osseo-Magnetic Link (OML) is a novel humeral or wrist rotation control system that could preserve proprioception. It utilizes a magnet implanted within the residual bone and sensors mounted in the prosthetic socket to detect magnetic field vectors and determine the bones orientation. This allows the use of volitional bone rotation to control a prosthetic rotator. We evaluated the performance of the OML using a physical model of a transhumeral residual limb. A small Neodymium-Iron-Boron magnet was placed in a model humerus, inside a model upper arm. Four three-axis Hall-effect sensors were mounted on a ring 3 cm distal to the magnet. An optimization algorithm based on Newtons method determined the position and orientation of the magnet within the model humerus under various conditions, including bone translations, interference, and magnet misalignment. The orientation of the model humerus was determined within 3° for rotations centered in the arm; an additional 6° error was found for translations 20 mm from center. Adjustments in sensor placement may reduce these errors. The results demonstrate that the OML is a feasible solution for providing prosthesis rotation control while preserving rotational proprioception.
Prosthetic limbs are difficult to control and do not provide sensory feedback. Targeted reinnervation was developed as a neural-machine interface for amputees to address these issues. In targeted reinnervation, amputated nerves are redirected to proximal muscles and skin, creating nerve interfaces for prosthesis control and sensory feedback. Touching the reinnervated skin causes sensation to be projected to the missing limb. Here we use electrophysiological brain recording in the Sprague Dawley rat to investigate the changes to somatosensory cortex (S1) following amputation and nerve redirection with the intent to provide insight into the sensory phenomena observed in human targeted reinnervation amputees. Recordings revealed that redirected nerves established an expanded representation in S1, which may help to explain the projected sensations that encompass large areas of the hand in targeted reinnervation amputees. These results also provide evidence that the reinnervated target skin could serve as a line of communication from a prosthesis to cortical hand processing regions. S1 border regions were simultaneously responsive to reinnervated input and also vibrissae, lower lip, and hindfoot, suggesting competition for deactivated cortical territory. Electrically evoked potential latencies from reinnervated skin to cortex suggest direct connection of the redirected afferents to the forepaw processing region of S1. Latencies also provide evidence that the widespread reactivation of S1 cortex may arise from central anatomical interconnectivity. Targeted reinnervation offers the opportunity to examine the cortical plasticity effects when behaviorally important sensory afferents are redirected from their original location to a new skin surface on a different part of the body.
Significant progress has been made towards the clinical application of human-machine interfaces (HMIs) based on electromyographic (EMG) pattern recognition for various rehabilitation purposes. Making this technology practical and available to patients with motor deficits requires overcoming real-world challenges, such as physical and physiological changes, that result in variations in EMG signals and systems that are unreliable for long-term use. In this study, we aimed to address these challenges by (1) investigating the stability of time-domain EMG features during changes in the EMG signals and (2) identifying the feature sets that would provide the most robust EMG pattern recognition.
As medicine moves toward being able to predict what you will die from and when, nanomedicine is expected to enhance human capabilities and properties and promises the ability of health care professionals to diagnose, treat, and share medical information nearly instantaneously. It promises to deliver drugs directly to the source of the disease, i.e. tumor. This article examines the literature surrounding ethics associated with nanomedicine, and asks whether these ethical issues are new and unique. While opinions differ, this review concludes that none of the ethical questions surrounding nanomedicine are new or unique, and would hold true for any new medical device or medicine that was being evaluated. The real issue becomes public acceptance of nanomedicine and how much risk society is willing to accept with a new technology before it is proven effective and safe. While ethical foresight can prove effective in forecasting potential problems, in reality, ethics may not be capable of evaluating such a technology that has yet proven effective in all it has promised. Copyright (c) 2010 John Wiley & Sons, Inc.For further resources related to this article, please visit the WIREs website.
The forelimb amputee poses many reconstructive challenges in the clinical setting, and there is a paucity of established surgical models for study. To further elucidate the pathogenic process in amputation neuroma formation, we created a reproducible, well-tolerated rabbit forelimb amputation model.
We evaluated real-time myoelectric pattern recognition control of a virtual arm by transradial amputees. Five unilateral patients performed 10 wrist and hand movements using their amputated and intact arms. In order to demonstrate the value of information from intrinsic hand muscles, this data was included in EMG recordings from the intact arm. With both arms, motions were selected in approximately 0.2 s on average, and completed in less than 1.25 s. Approximately 99% of wrist movements were completed using either arm; however, the completion rate of hand movements was significantly lower for the amputated arm (53.9% +/- 14.2%) than for the intact arm ( 69.4% +/- 13.1%). For the amputated arm, average classification accuracy for only 6 movements-including a single hand grasp-was 93.1% +/- 4.1%, compared to 84.4% +/- 7.2% for all 10 movements. Use of 6 optimally-placed electrodes only reduced this accuracy to 91.5% +/- 4.9%. These results suggest that muscles in the residual forearm produce sufficient myoelectric information for real-time wrist control, but not for performing multiple hand grasps. The outcomes of this study could aid the development of a practical multifunctional myoelectric prosthesis for transradial amputees, and suggest that increased EMG information-such as made available through targeted muscle reinnervation-could improve control of these prostheses.
Pattern recognition myoelectric control in combination with targeted muscle reinnervation (TMR) may provide better real-time control of upper limb prostheses. Current pattern recognition algorithms can classify movements with an off-line accuracy of approximately 95%. When amputees use these systems to control prostheses, motion misclassifications may hinder their performance. This study investigated the use of a decision based velocity profile that limited movement speed when there was a change in classifier decision. The goal of this velocity ramp was to improve prosthesis positioning by minimizing the effect of unintended movements. Two patients who had undergone TMR surgery controlled either a virtual or physical prosthesis. They completed a Target Achievement Control Test where they commanded a virtual prosthesis into a target posture. Participants showed improved performance metrics of 34% increase in completion rate and 13% faster overall time with the velocity ramp compared to without the velocity ramp. One participant controlled a physical prosthesis and in three minutes was able to create a tower of 1" cubes seven blocks tall with the velocity ramp compared to a tower of only two blocks tall in the control condition. These results suggest that using a pattern recognition system with a decision based velocity profile may improve user performance.
Electromyogram (EMG) pattern recognition approach has been investigated widely with able-bodied subjects for control of multifunctional prostheses and verified with high performance in identifying different movements. However, it remains unclear whether transradial amputees can achieve similar performance. In this study, we investigated the performance of EMG pattern recognition control of multifunctional transradial prostheses in five subjects with unilateral below-elbow amputation. Testing results on both residual and intact arms showed that the average classification error (21%) of amputated arms for ten motion classes (four wrist movements, six hand grasps) and a no movement class over all five subjects was about 15% higher than that of intact arms. For six basic motion classes (wrist flexion/extension, wrist pronation/supination, and hand open/close), the average classification error over all five subjects was about 7% from residual arms, which was similar to the result from intact arms (6%). Only six optimal electrode channels might be needed to provide an excellent myoelectric control system for the six basic movements. These results suggest that the muscles in the residual forearm may produce sufficient myoelectric information to allow the six basic motion control, but insufficient information for more hand functions with fine finger movements.
Targeted muscle reinnervation (TMR) is a surgical intervention to improve the control of myoelectric prostheses in high-level upper-limb amputation. This article briefly describes the procedure and presents the protocol for postoperative, preprosthetic care. We also recommend a guide to patient training using standard-of-care prosthetic devices controlled by up to four intuitive, independent, and isolated myoelectric signals. We discuss the advantages of this new control paradigm and methods for optimizing clinical outcomes for patients with high-level upper-limb amputations. This material is based on more than 6 years of experience treating patients with TMR in a research setting. Detailed results of this research are reported elsewhere.
Artificial limbs allow amputees to manipulate objects, but the loss of a limb severs the sensory link between a subject and objects they touch. A novel surgical technique we term targeted reinnervation (TR) allows severed cutaneous nerves to reinnervate skin on a different portion of the body. This technique provides a physiologically appropriate portal to the sensory pathways of the missing limb through the reinnervated skin. This study quantified the ability of three amputee subjects who had undergone TR surgery on the chest (two subjects) and upper arm (one subject) to discriminate changes in graded force on their reinnervated skin over a range of 1-4 N using a stochastic staircase approach. These values were compared to those from sites on their intact contralateral skin and index fingers, and from the chests and index fingers of a control population (n = 10) . Webers ratio (WR) was used to examine the subjects abilities to discriminate between a baseline force and subsequent forces of different magnitudes. WRs of 0.22, 0.25, and 0.12 were measured on the reinnervated skin of the three TR subjects, whereas WRs of 0.25, 0.23, and 0.12 were measured on their contralateral skin. TR subjects did not have substantially different WRs on their reinnervated versus their contralateral normal side and did not appear to exhibit a trend towards impaired sensation. No significant difference was found between the WR of the chest and index finger of the control subjects, which ranged between 0.09 and 0.21. WR of reinnervated skin for TR subjects were within the 95% confidence interval of the control group. These data suggest that subjects with targeted reinnervation have unimpaired ability to discriminate gradations in force.
Targeted reinnervation in upper extremity transhumeral amputees can improve control and dexterity of myoelectric prostheses. The operation as described previously required a long residual limb and the presence of a brachialis muscle.
Targeted muscle reinnervation has been introduced as an effective neural machine interface. In the case of a shoulder disarticulation patient, an effective site for a nerve transfer involves the pectoralis muscles, as these perform little useful function with a missing limb. Consequently, the myoelectric signals measured from the reinnervated muscles may be corrupted by a large amount of ECG interference. This paper investigates the effect of ECG upon the accuracy of a pattern-classification-based scheme for myoelectric control of powered upper limb prostheses. The results suggest that ECG interference, at levels typically encountered in a clinical measurement, has little effect upon classification accuracy, but can affect the estimate of myoelectric activity used to convey the velocity of motion (commonly referred to as proportional control). High-pass filtering at approximately 100 Hz appears to effectively mitigate the effect of ECG interference.
Ecosystems that have low mercury (Hg) concentrations (i.e., not enriched or impacted by geologic or anthropogenic processes) cover most of the terrestrial surface area of the earth yet their role as a net source or sink for atmospheric Hg is uncertain. Here we use empirical data to develop a rule-based model implemented within a geographic information system framework to estimate the spatial and temporal patterns of Hg flux for semiarid deserts, grasslands, and deciduous forests representing 45% of the continental United States. This exercise provides an indication of whether these ecosystems are a net source or sink for atmospheric Hg as well as a basis for recommendation of data to collect in future field sampling campaigns. Results indicated that soil alone was a small net source of atmospheric Hg and that emitted Hg could be accounted for based on Hg input by wet deposition. When foliar assimilation and wet deposition are added to the area estimate of soil Hg flux these biomes are a sink for atmospheric Hg.
The combination of targeted muscle reinnervation (TMR) and pattern classification of electromyography (EMG) has shown great promise for multifunctional myoelectric prosthesis control. In this study, we hypothesized that surface EMG recordings with high spatial resolution over reinnervated muscles could capture focal muscle activity and improve the classification accuracy of identifying intended movements. To test this hypothesis, TMR subjects with transhumeral or shoulder disarticulation amputations were recruited. Spatial filters such as single differential filters, double differential filters, and various two-dimensional, high-order spatial filters were used, and the classification accuracies for fifteen different movements were calculated. Compared with monopolar recordings, spatially localized EMG signals produced increased accuracy in identifying the TMR patients movement intents, especially for hand movements. When the number of EMG signals was constrained to 12, the double differential filters gave 5-15% higher classification accuracies than the filters with lower spatial resolution, but resulted in comparable accuracies to the filters with higher spatial resolution. These results suggest that double differential EMG recordings may further improve the TMR-based neural interface for robust, multifunctional control of artificial arms.
Pattern recognition is a useful tool for deciphering movement intent from myoelectric signals. Recognition paradigms must adapt with the user in order to be clinically viable over time. Most existing paradigms are static, although two forms of adaptation have received limited attention. Supervised adaptation can achieve high accuracy since the intended class is known, but at the cost of repeated cumbersome training sessions. Unsupervised adaptation attempts to achieve high accuracy without knowledge of the intended class, thus achieving adaptation that is not cumbersome to the user, but at the cost of reduced accuracy. This study reports a novel adaptive experiment on eight subjects that allowed repeated measures post-hoc comparison of four supervised and three unsupervised adaptation paradigms. All supervised adaptation paradigms reduced error over time by at least 26% compared to the nonadapting classifier. Most unsupervised adaptation paradigms provided smaller reductions in error, due to frequent uncertainty of the correct class. One method that selected high-confidence samples showed the most practical implementation, although the other methods warrant future investigation. Supervised adaptation should be considered for incorporation into any clinically viable pattern recognition controller, and unsupervised adaptation should receive renewed interest in order to provide transparent adaptation.
Recent advances in the design of prosthetic arms have helped upper limb amputees achieve greater levels of function. However, control of upper limb prostheses is limited by the lack of sensory feedback to the user. Targeted reinnervation, a novel surgical technique for amputees, offers the potential for returning this lost sensation. During targeted reinnervation surgery, truncated nerves are directed to reinnervate new muscle and skin sites. Contractions of reinnervated muscles generate electrical signals that are used to control prosthetic arms. In addition, stimulation of reinnervated skin is perceived on the missing limb. Vibration detection thresholds were measured at four frequencies on the reinnervated chest skin of three shoulder-level amputees following targeted reinnervation surgery. Thresholds were also measured on the contralateral chest and arm skin of these amputees, as well as on the chest and arm skin of a control population. Vibrations applied to reinnervated skin were perceived at various locations on the missing arm and hand. Thresholds for the reinnervated chest skin were generally within the range of values measured on the chests of the control population. For the two unilateral amputees, these thresholds were similar to measures on their contralateral chests, but greater than measures on their contralateral hands. Targeted reinnervation appears to result in near-normal vibration-detection ability with respect to the target tissue, suggesting the functional reinnervation of mechanoreceptors by the reinnervating afferents. The functional limb sensation following targeted reinnervation could be used to provide prosthesis users with a sense of touch.
Targeted reinnervation is a new neural-machine interface that has been developed to help improve the function of new-generation prosthetic limbs. Targeted reinnervation is a surgical procedure that takes the nerves that once innervated a severed limb and redirects them to proximal muscle and skin sites. The sensory afferents of the redirected nerves reinnervate the skin overlying the transfer site. This creates a sensory expression of the missing limb in the amputees reinnervated skin. When these individuals are touched on this reinnervated skin they feel as though they are being touched on their missing limb. Targeted reinnervation takes nerves that once served the hand, a skin region of high functional importance, and redirects them to less functionally relevant skin areas adjacent to the amputation site. In an effort to better understand the sensory capacity of the reinnervated target skin following this procedure, we examined grating orientation thresholds and point localization thresholds on two amputees who had undergone the targeted reinnervation surgery. Grating orientation thresholds and point localization thresholds were also measured on the contralateral normal skin of the targeted reinnervation amputees and on analogous sites in able-bodied controls. Grating orientation thresholds for the reinnervated skin of the targeted reinnervation amputees were found to be similar to normal ranges for both the amputees contralateral skin and also for the control population. Point localization thresholds for these amputees were found to be lower for their reinnervated skin than for their contralateral skin. Reinnervated point localization thresholds values were also lower in comparison to homologous chest sites on the control population. Mechanisms appear to be in place to maximize re-established touch input in targeted reinnervation amputees. It seems that sound sensory function is provided to the denervated skin of the residual limb when connected to afferent pathways once serving highly functionally relevant regions of the brain. This suggests that tactile interface devices could be used to give a physiologically appropriate sense of touch to a prosthetic limb, which would likely help with better functional utilization of the prosthetic device and possibly help to more effectively integrate the device with the users self-image.
Although industrial sectors involving semiconductors; memory and storage technologies; display, optical, and photonic technologies; energy; biotechnology; and health care produce the most products that contain nanomaterials, nanotechnology is also used as an environmental technology to protect the environment through pollution prevention, treatment, and cleanup. In this review, we focus on environmental cleanup and provide a background and overview of current practice; research findings; societal issues; potential environment, health, and safety implications; and future directions for nanoremediation. We do not present an exhaustive review of chemistry/engineering methods of the technology but rather an introduction and summary of the applications of nanotechnology in remediation. We also discuss nanoscale zerovalent iron in detail.
This study investigated the use of surface electromyography (EMG) combined with pattern recognition (PR) to identify user locomotion modes. Due to the nonstationary characteristics of leg EMG signals during locomotion, a new phase-dependent EMG PR strategy was proposed for classifying the users locomotion modes. The variables of the system were studied for accurate classification and timely system response. The developed PR system was tested on EMG data collected from eight able-bodied subjects and two subjects with long transfemoral (TF) amputations while they were walking on different terrains or paths. The results showed reliable classification for the seven tested modes. For eight able-bodied subjects, the average classification errors in the four defined phases using ten electrodes located over the muscles above the knee (simulating EMG from the residual limb of a TF amputee) were 12.4% +/- 5.0%, 6.0% +/- 4.7%, 7.5% +/- 5.1%, and 5.2% +/- 3.7%, respectively. Comparable results were also observed in our pilot study on the subjects with TF amputations. The outcome of this investigation could promote the future design of neural-controlled artificial legs.
Improving the function of prosthetic arms remains a challenge, because access to the neural-control information for the arm is lost during amputation. A surgical technique called targeted muscle reinnervation (TMR) transfers residual arm nerves to alternative muscle sites. After reinnervation, these target muscles produce electromyogram (EMG) signals on the surface of the skin that can be measured and used to control prosthetic arms.
A targeted muscle reinnervation (TMR) model was created using a pedicled rabbit rectus abdominis (RA) flap to receive the input from previously amputated forelimb neuromas. We hypothesize that a segmental muscle flap can undergo TMR and that it is possible to differentiate the signal from 3 independent nerves. In addition, by virtue of the nerve coaptation, the morphology of the previous amputation neuroma would become more like that of an in-continuity neuroma.
Osseointegrated implants (OI)s for transfemoral prosthetic attachment offer amputees an alternative to the traditional socket attachment. Potential benefits include a natural transfer of loads directly to the skeleton via the percutaneous abutment, relief of pain and discomfort of residual limb soft tissues by eliminating sockets, increased sensory feedback, and improved function. Despite the benefits, the skin-implant interface remains a critical limitation, as it is highly prone to bacterial infection. One approach to improve clinical outcomes is to minimize stress concentrations at the skin-implant interface due to shear loading, reducing soft tissue breakdown and subsequent risk of infection. We hypothesized that broadening the bone base at the distal end of the femur would provide added surface area for skin adhesion and reduce stresses at the skin-implant interface. We tested this hypothesis using finite element models of an OI in a residual limb. Results showed a dramatic decrease in stress reduction, with up to ~90% decrease in stresses at the skin-implant interface as cortical bone thickness increased from 2 to 8 mm. The findings in this study suggests that surgical techniques could stabilize the skin-implant interface, thus enhancing a skin-to-bone seal around the percutaneous device and minimizing infection.
Pattern recognition of the electromyogram (EMG) has been demonstrated in the laboratory to be a successful alternative to conventional control methods for myoelectric prostheses. Pattern recognition control is dependent upon both machine and user learning; the user learns to generate distinct classes of muscle activity while the machine learns to interpret them. With experience, users may learn to generate distinct classes by reducing intraclass variability or by increasing interclass distance. The goal of this study was to identify which of these strategies best explained differences in EMG patterns between subjects with and without experience using pattern recognition control. We compared classification errors of novice nonamputee subjects with experienced nonamputee subjects. We found that after brief exposure to the control method, classification error in novices was reduced, although not to the level of experienced subjects. While the level of intraclass variability in novices was similar to that of the experienced subjects, they did not achieve the same level of interclass distance. These differences can be used to guide the development of much needed rehabilitation methods to train subjects to use pattern recognition devices. In particular we recommend training protocols that emphasize increasing the interclass distance.
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