Search

It is crucial to increase the independence of severely disabled individuals. Assistive robotics can aid in the desired activities of daily living, including tasks requiring remote performance e.g. grasping remote objects, turning switches on/off, and opening/closing doors. The robot control is compromised by the lack of efficient interfaces for individuals with disabilities and the lack of depth perception. This paper addresses these challenges by presenting the development and evaluation of efficient tongue-based robot interfaces and low-level robot control schemes targeting tele-robotic control through a 2D display. Ten able-bodied participants were successful in completing ten rounds of controlling a JACO robot to perform a pouring water task, using five different control methods, under 2D or 3D visual feedback. The tool-frame based tongue interface layout, L2_TF (with emulated joystick, mode switch button and a “GO” button) improved the 2D visual guided control of the JACO robot compared with the other tongue control methods. The mean trajectory length of completing the task using L2_TF was 3% longer compared with the standard joystick when controlling through 2D. The trajectory length for reaching and grabbing a bottle was shortest for L2_TF compared with all other control methods, including the joystick. The iTongue control layouts performed well in gripping time, showing no significant difference between 2D and 3D. The transition from 2D to 3D resulted in a mean decrease of 27.7% for task completion time across all interfaces. L2_TF and the joystick had the strongest and most similar robustness to the transition between 3D and 2D. [ABSTRACT FROM AUTHOR]

High level spinal cord injury drastically reduces the quality of life of the injured person. Various systems attempted to interface the still intact or residual abilities following injury in various monomodal or multimodal designs to compensate for the highly affected mobility. An intra-oral inductive tongue computer interface (ITCI) has been designed to provide real-time discrete and proportional control for computers and assistive devices and to meet specific requirements for individuals with tetraplegia. Operation of the ITCI for wheelchair control was demonstrated with two participants with tetraplegia in a short-term training study. Additionally, two non-disabled individuals participated in the study. For each participant, the ability to drive a Permobil C500 with the ITCI was compared to that when driving the wheelchair with joystick (mouth-stick in one case) along two different lanes of 39 m, by reporting the speed along the lanes and the number of obstacles hit. The lanes consisted of 90°, 360°, and complex maneuver segments linked by linear segments. The ITCI featured a mouthpiece encapsulating two pads of inductive sensors, driving electronics, and battery. The mouthpiece was attached to the palate of the participant’s oral cavity with dental retainers. A piercing-like activation unit was attached to the tongue. Data were transmitted wirelessly to a central unit that controlled the wheelchair through wired interface. Among all participants, mean speeds along lane A or B reached maximal values between 0.42 and 0.74 m/s when driving with the ITCI, representing 41 to 71% of that obtained when driving with the joystick. [ABSTRACT FROM AUTHOR]

Individuals with tetraplegia have a challenging life due to a lack of independence and autonomy. Assistive robots have the potential to assist with the activities of daily living and thus improve the quality of life. However, an efficient and reliable control interface for severely disabled individuals is still missing. An intraoral tongue-computer interface (ITCI) for people with tetraplegia has previously been introduced and tested for controlling a robotic manipulator in a study deploying discrete tongue robot mapping. To improve the efficiency of the interface, the current study proposed the use of virtual buttons based on the ITCI and evaluated them in combination with a joystick-like control implementation, enabling continuous control commands. Twelve able-bodied volunteers participated in a three-day experiment. They controlled an assistive robotic manipulator through the tongue to perform two tasks: Pouring water in a cup (PW) and picking up a roll of tape (PUT). Four different tongue-robot mapping methods were compared. The results showed that using continuous commands reduced the task completion time by 16% and the number of commands of the PUT test by 20% compared with discrete commands. The highest success rate for completing the tasks was 77.8% for the PUT test and 100% for the PW test, both achieved by the control methods with continuous commands. Thus, the study demonstrated that incorporating continuous commands can improve the performance of the ITCI system for controlling robotic manipulators. [ABSTRACT FROM AUTHOR]

Recovery of the upper extremity (UE) and hand function is considered the highest priority for people with tetraplegia, because these functions closely integrate with their activities of daily living. Spinal cord transcutaneous stimulation (scTS) has great potential to facilitate functional restoration of paralyzed limbs by neuro-modulating the excitability of the spinal network. Recently, this approach has been demonstrated effective in improving UE function in people with motor complete and incomplete cervical SCI. However, the research thus far is limited by the lack of a comprehensive assessment of functional improvement and neurological recovery throughout the intervention. The goal of this study was to investigate whether scTS can also facilitate UE functional restoration in an individual with motor and sensory complete tetraplegia. A 38-year-old male with a C5 level, ASIA Impairment Scale-A SCI (15 years post-injury, left hand dominant pre- and post-injury), received 18 sessions (60 minutes/session) of scTS combined with task-specific hand training over the course of 8 weeks. The total score of the Graded Redefined Assessment of Strength, Sensibility, and Prehension significantly improved from 72/232 to 96/232 at post-intervention, and maintained ranging from 82/232 to 86/232 during the three months follow-up without any further treatment. The bilateral handgrip force improved by 283.4% (left) and 30.7% (right), respectively at post-intervention. These strength gains were sustained at 233.5% -250% (left) and 11.5%-73.1% (right) during the follow-up evaluation visits. Neuromuscular Recovery Scale demonstrated dramatic and long-lasting improvements following the completion of the intervention. Changes of spinal motor evoked potentials from pre- to post-intervention indicated an increased level of spinal network excitability. The present data offer preliminary evidence that the novel scTS intervention combined with hand training can enhance UE functional use in people with motor and sensory complete SCI. [ABSTRACT FROM AUTHOR]

People with tetraplegia resulting from spinal cord injury experience debilitating hand impairments that may lead to lifelong dependence on others to perform activities of daily living. Wearable robotic devices that actively support hand function during daily living tasks could bring great benefits to this population. In this work, the performance of a textile-based soft robotic glove controlled by the user with a button was evaluated in thirteen participants with tetraplegia. Performance outcomes included activities of daily living using the Jebsen Taylor Hand Function Test, active range of motion of the fingers, and grasp strength for power and pinch grasps. In the Jebsen Test, participants showed significant improvements in performance of activities of daily living with glove assistance, completing a median of 50% more tasks than in their baseline attempt without the glove. Significant improvements were also found for power and pinch grasp forces and active range of motion of the fingers with the glove assistance. Participants with lower baseline motor function received greater benefits from glove assistance. This work demonstrates the effectiveness of a user-controlled textile-based soft robotic glove to improve activity of daily living abilities in individuals with hand impairments resulting from spinal cord injury. [ABSTRACT FROM AUTHOR]

Functional electrical stimulation (FES) is a promising solution for restoring functional motion to individuals with paralysis, but the potential for achieving any desired full-arm reaching motion has not been realized. We present a combined feedforward-feedback controller capable of automatically calculating and applying the necessary muscle stimulations to hold the wrist of an individual with high tetraplegia in a desired static position. We used the controller to hold a complete arm configuration to maintain a series of static wrist positions. The average distance to the target wrist position, or accuracy, was 2.9 cm. The precision is defined as the radius of the 95% confidence ellipsoid for the final positions of a set of trials with the same muscle stimulations and starting position. The average precision was 3.7 cm. The control architecture used in this study to hold static positions has the potential to control arbitrary reaching motions. [ABSTRACT FROM AUTHOR]

This paper introduces a new human-machine interface for individuals with tetraplegia. We investigated the feasibility of piloting an assistive device by processing supra-lesional muscle responses online. The ability to voluntarily contract a set of selected muscles was assessed in five spinal cord-injured subjects through electromyographic (EMG) analysis. Two subjects were also asked to use the EMG interface to control palmar and lateral grasping of a robot hand. The use of different muscles and control modalities was also assessed. These preliminary results open the way to new interface solutions for high-level spinal cord-injured patients. [ABSTRACT FROM PUBLISHER]

Multimodal Tongue Drive System (mTDS) is a highly integrated wireless assistive technology (AT) in the form of a lightweight wearable headset that utilizes three remaining key control and communication abilities in people with severe physical disabilities, such as tetraplegia, to provide them with effective access to computers: 1) tongue motion for discrete/switch-based control (e.g., clicking), 2) head tracking for proportional control (e.g., mouse pointer movements), and 3) speech recognition for typing, all available simultaneously. The mTDS architecture is presented here with new sensor signal processing algorithm for head tracking. To evaluate the device performance, it was compared against keyboard-and-mouse (KnM) combination, the gold standard in computer input methods, by 15 able-bodied participants, who used both mTDS and KnM to generate and sent an email with randomly selected content, under a 5-minute time constraint. In four repetitions, in the last trial, it took participants only 1.8 times longer to complete the email task, on average, using the mTDS versus KnM at 82.4% typing accuracy. Mean task completion time and typing accuracy improved 24.6% and 18.8% from first to fourth trial using mTDS. Multimodal simultaneous discrete and proportional control input options of mTDS, plus rapid typing, is expected to provide more effective computer access to people with severe physical disabilities. [ABSTRACT FROM PUBLISHER]

For severely paralyzed individuals, alternative computer interfaces are becoming increasingly essential for everyday life as social and vocational activities are facilitated by information technology and as the environment becomes more automatic and remotely controllable. Tongue computer interfaces have proven to be desirable by the users partly due to their high degree of aesthetic acceptability, but so far the mature systems have shown a relatively low error-free text typing efficiency. This paper evaluated the intra-oral inductive tongue computer interface (ITCI) in its intended use: Error-free text typing in a generally available text editing system, Word. Individuals with tetraplegia and able bodied individuals used the ITCI for typing using a MATLAB interface and for Word typing for 4 to 5 experimental days, and the results showed an average error-free text typing rate in Word of 11.6 correct characters/min across all participants and of 15.5 correct characters/min for participants familiar with tongue piercings. Improvements in typing rates between the sessions suggest that typing ratescan be improved further through long-term use of the ITCI. [ABSTRACT FROM PUBLISHER]

In this study, we consider a non-invasive body-machine interface that captures body motions still available to people with spinal cord injury (SCI) and maps them into a set of signals for controlling a computer user interface while engaging in a sustained level of mobility and exercise. We compare the effectiveness of two decoding algorithms that transform a high-dimensional body-signal vector into a lower dimensional control vector on six subjects with high-level SCI and eight controls. One algorithm is based on a static map from current body signals to the current value of the control vector set through principal component analysis (PCA), the other on dynamic mapping a segment of body signals to the value and the temporal derivatives of the control vector set through a Kalman filter. SCI and control participants performed straighter and smoother cursor movements with the Kalman algorithm during center-out reaching, but their movements were faster and more precise when using PCA. All participants were able to use the BMI’s continuous, two-dimensional control to type on a virtual keyboard and play pong, and performance with both algorithms was comparable. However, seven of eight control participants preferred PCA as their method of virtual wheelchair control. The unsupervised PCA algorithm was easier to train and seemed sufficient to achieve a higher degree of learnability and perceived ease of use. [ABSTRACT FROM AUTHOR]

For individuals with high spinal cord injury (SCI), restoring missing grasping function is a high priority. Neuroprostheses based on functional electrical stimulation (FES) can partly compensate the loss of upper extremity function in people suffering from tetraplegia. With noninvasive, multichannel neuroprostheses a pinch and power grasp can be accomplished for everyday use. Hybrid systems combining FES with active orthoses hold promise for restoring a completely lost arm function. Novel control interfaces are needed to make full use of the many degrees of freedom of complex hybrid neuroprostheses. Motor imagery (MI)-based brain–computer interfaces (BCIs) are an emerging technology that may serve as a valuable adjunct to traditional control interfaces for neuroprosthetic control. Shared control and context-specific autonomy are most effective for reducing the users' workload. The modularity of upper extremity neuroprostheses as well as their associated control interfaces enable customization of the systems to adapt to the impairment and needs of each individual end user. This work provides an overview of the application of noninvasive hybrid BCI-controlled upper extremity neuroprostheses in individuals with high SCI with a strong focus on the results from the European Integrated Project Tools for Brain-Computer Interaction and will describe the challenges and promises for the future. [ABSTRACT FROM PUBLISHER]

Rapid developments in neural interface technology are making it possible to record increasingly large signal sets of neural activity. Various factors such as asymmetrical information distribution and across-channel redundancy may, however, limit the benefit of high-dimensional signal sets, and the increased computational complexity may not yield corresponding improvement in system performance. High-dimensional system models may also lead to overfitting and lack of generalizability. To address these issues, we present a generalized modulation depth measure using the state-space framework that quantifies the tuning of a neural signal channel to relevant behavioral covariates. For a dynamical system, we develop computationally efficient procedures for estimating modulation depth from multivariate data. We show that this measure can be used to rank neural signals and select an optimal channel subset for inclusion in the neural decoding algorithm. We present a scheme for choosing the optimal subset based on model order selection criteria. We apply this method to neuronal ensemble spike-rate decoding in neural interfaces, using our framework to relate motor cortical activity with intended movement kinematics. With offline analysis of intracortical motor imagery data obtained from individuals with tetraplegia using the BrainGate neural interface, we demonstrate that our variable selection scheme is useful for identifying and ranking the most information-rich neural signals. We demonstrate that our approach offers several orders of magnitude lower complexity but virtually identical decoding performance compared to greedy search and other selection schemes. Our statistical analysis shows that the modulation depth of human motor cortical single-unit signals is well characterized by the generalized Pareto distribution. Our variable selection scheme has wide applicability in problems involving multisensor signal modeling and estimation in biomedical engineering systems. [ABSTRACT FROM PUBLISHER]

Combining electrophysiological and hemodynamic features is a novel approach for improving current performance of brain switches based on sensorimotor rhythms (SMR). This study was conducted with a dual purpose: to test the feasibility of using a combined electroencephalogram/functional near-infrared spectroscopy (EEG-fNIRS) SMR-based brain switch in patients with tetraplegia, and to examine the performance difference between motor imagery and motor attempt for this user group. A general improvement was found when using both EEG and fNIRS features for classification as compared to using the single-modality EEG classifier, with average classification rates of 79% for attempted movement and 70% for imagined movement. For the control group, rates of 87% and 79% were obtained, respectively, where the “attempted movement” condition was replaced with “actual movement.” A combined EEG-fNIRS system might be especially beneficial for users who lack sufficient control of current EEG-based brain switches. The average classification performance in the patient group for attempted movement was significantly higher than for imagined movement using the EEG-only as well as the combined classifier, arguing for the case of a paradigm shift in current brain switch research. [ABSTRACT FROM AUTHOR]

Intracortical brain-computer interfaces (iBCIs) decode intended movement from neural activity for the control of external devices such as a robotic arm. Standard approaches include a calibration phase to estimate decoding parameters. During iBCI operation, the statistical properties of the neural activity can depart from those observed during calibration, sometimes hindering a user's ability to control the iBCI. To address this problem, we adaptively correct the offset terms within a Kalman filter decoder via penalized maximum likelihood estimation. The approach can handle rapid shifts in neural signal behavior (on the order of seconds) and requires no knowledge of the intended movement. The algorithm, called multiple offset correction algorithm (MOCA), was tested using simulated neural activity and evaluated retrospectively using data collected from two people with tetraplegia operating an iBCI. In 19 clinical research test cases, where a nonadaptive Kalman filter yielded relatively high decoding errors, MOCA significantly reduced these errors (10.6 ±10.1%; p <; 0.05, pairwise t-test). MOCA did not significantly change the error in the remaining 23 cases where a nonadaptive Kalman filter already performed well. These results suggest that MOCA provides more robust decoding than the standard Kalman filter for iBCIs. [ABSTRACT FROM AUTHOR]

The Kalman filter is commonly used in neural interface systems to decode neural activity and estimate the desired movement kinematics. We analyze a low-complexity Kalman filter implementation in which the filter gain is approximated by its steady-state form, computed offline before real-time decoding commences. We evaluate its performance using human motor cortical spike train data obtained from an intracortical recording array as part of an ongoing pilot clinical trial. We demonstrate that the standard Kalman filter gain converges to within 95% of the steady-state filter gain in 1.5\pm 0.5~s~(mean \pm s.d.). The difference in the intended movement velocity decoded by the two filters vanishes within 5 s, with a correlation coefficient of 0.99 between the two decoded velocities over the session length. We also find that the steady-state Kalman filter reduces the computational load (algorithm execution time) for decoding the firing rates of 25\pm 3 single units by a factor of 7.0\pm 0.9. We expect that the gain in computational efficiency will be much higher in systems with larger neural ensembles. The steady-state filter can thus provide substantial runtime efficiency at little cost in terms of estimation accuracy. This far more efficient neural decoding approach will facilitate the practical implementation of future large-dimensional, multisignal neural interface systems. [ABSTRACT FROM PUBLISHER]

We characterized features of magnetoencephalographic (MEG) and electroencephalographic (EEG) signals generated in the sensorimotor cortex of three tetraplegics attempting index finger movements. Single MEG and EEG trials were classified offline into two classes using two different classifiers, a batch trained classifier and a dynamic classifier. Classification accuracies obtained with dynamic classifier were better, at 75%, 89%, and 91% in different subjects, when features were in the 0.5–3.0-Hz frequency band. Classification accuracies of EEG and MEG did not differ. [ABSTRACT FROM AUTHOR]

The authors have evaluated the ability of a time-delayed artificial neural network (TDANN) to predict shoulder and elbow motions using only electromyographic (EMG) signals recorded from six shoulder and elbow muscles as inputs, both in able-bodied subjects and in subjects with tetraplegia arising from C5 spinal cord injury. For able-bodied subjects, all four joint angles (elbow flexion-extension and shoulder-horizontal flexion-extension, elevation depression, and internal-external rotation) were predicted with average root-mean-square (rms) errors of less than 20° during movements of widely different complexities performed at different speeds and with different hand loads. The corresponding angular velocities and angular accelerations were predicted with even lower relative errors. For individuals with C5 tetraplegia, the absolute rms errors of the joint angles, velocities, and accelerations were actually smaller than for able-bodied subjects, but the relative errors were similar when the smaller movement ranges of the C5 subjects were taken into account. These results indicate that the EMG signals from shoulder and elbow muscles contain a significant amount of information about arm movement kinematics that could be exploited to develop advanced control systems for augmenting or restoring shoulder and elbow movements to individuals with tetraplegia using functional neuromuscular stimulation of paralyzed muscles [ABSTRACT FROM PUBLISHER]

Grasp and release has been provided to both upper extremities of subjects with tetraplegia using percutaneous and fully implanted stimulation. This is to determine quantitatively the performance of these subjects in three bimanual tests using two handed stimulation. Their performance here is compared with two separate cases: the same tests using single handed stimulation assisted by a nonstimulated hand and using two unstimulated hands. It was found that bilateral stimulation significantly improved the efficacy of performing the bimanual tests assessed over that using unilateral stimulation assisted by the nonstimulated hand (in two of three tests) or no stimulation (three of three tests). These results show quantitative evidence of the benefits of providing bilateral stimulation for the completion of bimanual tasks for persons with tetraplegia who are appropriate candidates for stimulated grasp. These benefits were observed especially in cases where the ability of the subject in completing the task using unilateral stimulation was not strong [ABSTRACT FROM PUBLISHER]

Paralyzed muscle fatigue is the eventual depression of force due to either prolonged or repetitive electrical stimulation of motor units. The robustness and safety of future functional electrical stimulation (FES) systems will rely on their ability to detect the onset of muscle fatigue. The relative degree of muscle activation can be estimated by monitoring the M-wave. The aim of this study was to test a proposed method of quantitative fatigue assessment that detects muscle force output and its corresponding M-wave measured concurrently. The detection of force and M-wave concurrently allows any reduction in muscle force output to be attributed to either changes in the fatigue state of the stimulated muscle or changes in the degree of stimulus activation of that muscle. The fatigue assessment scheme can thereby accommodate the corresponding changes in muscle force caused by an alteration in the stimulation intensity during fatigue. The Extensor Digitorum Communis (EDC), Extensor Pollicis Longus (EPL), and Flexor Pollicis Longus (FPL) muscles of two C5/C6 tetraplegic men were studied. Stimulation recruitment tests over the pulsewidth range from 0 to 200 μs, were performed at intervals during 20 min of maximal stimulation (200 μs). Muscle force correlated to the M-wave parameter, second phase area, with mean correlation coefficients of greater than 0.82, when the muscle was in either a nonfatigued or fatiguing state. After the initial force, likely to be primarily due to the fast glycolytic (FG) motor units, had declined the M-wave demonstrated only minor changes throughout the fatigue of muscle force during 20 min of constant maximal stimulation. The second phase area and root-mean-square (rms) of the M-wave reflected muscle activation during modulated stimulation and also remained relatively constant during the fatigue-related force decline when the muscle was stimulated at a constant intensity. This detection of M-wave parameters satisfies the defined requirement for a myoelectric parameter that indicates electrical activation, but is relatively invariant to muscular fatigue [ABSTRACT FROM PUBLISHER]

Electrical stimulation has been applied to the paralyzed muscles of both hands of two persons with tetraplegia using percutneous acid implantable electrodes. Two separate methods of user control were being investigated. The first monitored the myoelectric signals from the user's own sternocleidomastoid muscles and the second monitored wrist joint angle. These signals were used as commands to modify the stimulated grasps. The hands were instrumented to detect the degree of hand closure and grip force and the users matched these to specific target parameters using the controller during tracking tasks. Performance in these tracking tasks was measured quantitatively. Wrist control was found to be less sensitive to the direction of hand opening/closing required than the myoelectric control. The user's performance with the myoelectric control demonstrated sensitivity to the target size and the speed of hand movement in response to the command control. The wrist controller required less training than the myoelectric controller for users to become proficient in its use. Based on these results, the wrist controller and the myoelectric controller both provide successful control of bilateral hand grasp and release. Of the two controllers, the wrist controller is likely to provide the greater ease of use, although it is only available to the population of users with active wrist extension [ABSTRACT FROM PUBLISHER]

Functional electrical stimulation (FES) of abdominal muscles as a method of enhancing ventilation was explored in six neurologically intact subjects and five subjects with spinal cord injury (SCI) who had levels of injury between C4 and C7. Pulmonary ventilation was augmented in both groups predominantly due to an increase in tidal volume. The average increase in tidal volume during FES for the neurologically intact group was 350 ml, while in the SCI group it was 220 ml. The FES caused active volume decreases in both the lower thorax and upper abdomen, which together appear to be the mechanism behind the increases seen in tidal volume. Therefore, the proposed method might be useful in future clinical practice. The results indicate that FES of abdominal muscles should be more thoroughly explored as a potential technique of ventilatory support in SCI. The results also point to the necessity for further studies of maintaining the condition of the chest wall in the pulmonary rehabilitation of individuals with tetraplegia [ABSTRACT FROM PUBLISHER]

The actions of the dorsal interosseous, volar interosseous, and lumbrical muscles were investigated using applied electrical stimulation and recording the moments that were generated across the metacarpophalangeal joint in flexion/extension and abduction/adduction, the proximal interphalangeal joint in flexion/extension, and the distal interphalangeal joint in flexion/extension. These measurements were made isometrically at various joint angles and levels of stimulation with both able bodied subjects and persons who had sustained tetraplegia. It was determined that the dorsal interossei, including the first, were strong abductors of the fingers and generated a significant moment in metacarpophalangeal (MP) joint flexion and interphalangeal (IP) joint extension. The volar interossei were the primary adductors of the fingers, as well as providing a significant moment in MP joint flexion and IP joint extension. The lumbrical muscles were found to be MP joint flexors and IP joint extensors, although the moments that were generated were on average 70% lower than the interossei. The role of the lumbricals as finger abductors or adductors could not be determined from the data. This information on the actions and moment generating capabilities of the intrinsic muscles led to the incorporation of the interossei into electrically induced hand grasp provided by an implanted neuroprosthesis. The evaluation of the intrinsic muscles in the neuroprosthesis was accomplished by recording the moment generating capabilities of these muscles across each of the joints of the finger. These muscles were capable of generating moments that were 80-90% of the average attained by the able bodied subjects, and have provided a substantial improvement to the electrically induced hand grasp [ABSTRACT FROM PUBLISHER]