Quantifying Performance of Bipedal Standing with Multi-channel EMG

Spinal cord stimulation has enabled humans with motor complete spinal cord injury (SCI) to independently stand and recover some lost autonomic function. Quantifying the quality of bipedal standing under spinal stimulation is important for spinal rehabilitation therapies and for new strategies that seek to combine spinal stimulation and rehabilitative robots (such as exoskeletons) in real time feedback. To study the potential for automated electromyography (EMG) analysis in SCI, we evaluated the standing quality of paralyzed patients undergoing electrical spinal cord stimulation using both video and multi-channel surface EMG recordings during spinal stimulation therapy sessions. The quality of standing under different stimulation settings was quantified manually by experienced clinicians. By correlating features of the recorded EMG activity with the expert evaluations, we show that multi-channel EMG recording can provide accurate, fast, and robust estimation for the quality of bipedal standing in spinally stimulated SCI patients. Moreover, our analysis shows that the total number of EMG channels needed to effectively predict standing quality can be reduced while maintaining high estimation accuracy, which provides more flexibility for rehabilitation robotic systems to incorporate EMG recordings

Within-socket Myoelectric Prediction of Continuous Ankle Kinematics for Control of a Powered Transtibial Prosthesis

Objective. Powered robotic prostheses create a need for natural-feeling user interfaces and robust control schemes. Here, we examined the ability of a nonlinear autoregressive model to continuously map the kinematics of a transtibial prosthesis and electromyographic (EMG) activity recorded within socket to the future estimates of the prosthetic ankle angle in three transtibial amputees. Approach. Model performance was examined across subjects during level treadmill ambulation as a function of the size of the EMG sampling window and the temporal \u27prediction\u27 interval between the EMG/kinematic input and the model\u27s estimate of future ankle angle to characterize the trade-off between model error, sampling window and prediction interval. Main results. Across subjects, deviations in the estimated ankle angle from the actual movement were robust to variations in the EMG sampling window and increased systematically with prediction interval. For prediction intervals up to 150 ms, the average error in the model estimate of ankle angle across the gait cycle was less than 6°. EMG contributions to the model prediction varied across subjects but were consistently localized to the transitions to/from single to double limb support and captured variations from the typical ankle kinematics during level walking. Significance. The use of an autoregressive modeling approach to continuously predict joint kinematics using natural residual muscle activity provides opportunities for direct (transparent) control of a prosthetic joint by the user. The model\u27s predictive capability could prove particularly useful for overcoming delays in signal processing and actuation of the prosthesis, providing a more biomimetic ankle response

Psychophysiological correlates of peritraumatic dissociative responses in survivors of life-threatening cardiac events

The psychophysiological startle response pattern associated with peritraumatic dissociation (DISS) was studied in 103 survivors of a life-threatening cardiac event (mean age 61.0 years, SD 13.95). Mean time period since the cardiac event was 37 (79 IQD) months. All patients underwent a psychodiagnostic evaluation (including the Peritraumatic Dissociative Experiences Questionnaire) and a psychophysiological startle experience which comprised the delivery of 15 acoustic startle trials. Magnitude and habituation to trials were measured by means of electromyogram (EMG) and skin conductance responses (SCR). Thirty-two (31%) subjects were indexed as patients with a clinically significant level of DISS symptoms. High-level DISS was associated with a higher magnitude of SCR (ANOVA for repeated measures p = 0.017) and EMG (p = 0.055) and an impaired habituation (SCR slope p = 0.064; EMG slope p = 0.005) in comparison to subjects with no or low DISS. In a subgroup analysis, high-level DISS patients with severe post-traumatic stress disorder (PTSD; n = 11) in comparison to high-level DISS patients without subsequent PTSD (n = 19) exhibited higher EMG amplitudes during all trials (repeated measures analysis of variance IF = 5.511, p = 0.026). The results demonstrate exaggerated startle responses in SCR and EMG measures - an abnormal defensive response to high-intensity stimuli which indicates a steady state of increased arousal. DISS patients without PTSD exhibited balanced autonomic responses to the startle trials. DISS may, therefore, unfold malignant properties only in combination with persistent physiological hyperarousability. Copyright (C) 2002 S. Karger AG, Basel

Changes in muscular activity while imagining weight lifting using stimulus or response propositions

Investigating emotional imagery, Lang (1977, 1979) proposed a dichotomy between stimulus and response propositions. In this study, Lang’s model is applied to movement images of lifting of 4.5 and 9 kg weights. Twenty-two male and 17 female students participated in the study. During the imaginary lifting of the weights, the electromyographical activity (EMG) of both biceps brachii muscles were assessed. Imagery ability was measured with the Movement Imagery Questionnaire (MIQ) and another self-report rating scale. When response propositions were emphasized in the script, imaginary weight lifting resulted in greater muscle activity than when stimulus propositions were emphasized. During imagined lifting, EMG activity of the active arm was greater than that of the passive arm. In addition, in the active arm, a significant difference in EMG activity was found between 9 kg and 4.5 kg. It was concluded that Lang’s model is also applicable to emotionally neutral movement imagery.</jats:p

Raised electrical uterine activity and shortened cervical length could predict preterm delivery in a low-risk population

PURPOSE: To compare diagnostic accuracy of sonographic cervical length (CL) measurement and uterine electric activity assessed by electromyography (EMG) in second trimester regarding prediction of preterm delivery (PTD). ----- METHODS: Prospective study of 308 low-risk women. Shortened CL was defined as ≤25 mm (≤5th centile), while raised EMG activity was defined as the presence of ≥20 action potentials in 20 min of assessment (≥95th centile). Outcome measures were diagnostic accuracy of both tests alone or in combination for prediction of PTD and early PTD (≤34 weeks). ----- RESULTS: The incidence of PTD was 23/308 (7.4%) while the incidence of early PTD was 9/308 (2.9%). Shortened CL and raised EMG activity were significantly related to PTD [prevalence-weighted likelihood ratio (pw-LR) 1.9, 95% CI 1.0-3.5 vs. 9.5, 95% CI 2.5-35.7], but not to early PTD (pw-LR 0.4, 95% CI 0.2-0.8 vs. 0.6, 95% CI 0.3-1.7). Significant predictive value for early PTD was found only if both tests were combined (pw-LR 4, 95% CI 1.3-14.3). ----- CONCLUSION: Shortened CL and raised EMG activity in second trimester have significant diagnostic accuracy regarding prediction of PTD in a low-risk population. However, in order to be useful as a predictor for early PTD both tests must be positive

Advances in surface EMG signal simulation with analytical and numerical descriptions of the volume conductor

Surface electromyographic (EMG) signal modeling is important for signal interpretation, testing of processing algorithms, detection system design, and didactic purposes. Various surface EMG signal models have been proposed in the literature. In this study we focus on 1) the proposal of a method for modeling surface EMG signals by either analytical or numerical descriptions of the volume conductor for space-invariant systems, and 2) the development of advanced models of the volume conductor by numerical approaches, accurately describing not only the volume conductor geometry, as mainly done in the past, but also the conductivity tensor of the muscle tissue. For volume conductors that are space-invariant in the direction of source propagation, the surface potentials generated by any source can be computed by one-dimensional convolutions, once the volume conductor transfer function is derived (analytically or numerically). Conversely, more complex volume conductors require a complete numerical approach. In a numerical approach, the conductivity tensor of the muscle tissue should be matched with the fiber orientation. In some cases (e.g., multi-pinnate muscles) accurate description of the conductivity tensor may be very complex. A method for relating the conductivity tensor of the muscle tissue, to be used in a numerical approach, to the curve describing the muscle fibers is presented and applied to representatively investigate a bi-pinnate muscle with rectilinear and curvilinear fibers. The study thus propose an approach for surface EMG signal simulation in space invariant systems as well as new models of the volume conductor using numerical methods

An EMG Gesture Recognition System with Flexible High-Density Sensors and Brain-Inspired High-Dimensional Classifier

EMG-based gesture recognition shows promise for human-machine interaction. Systems are often afflicted by signal and electrode variability which degrades performance over time. We present an end-to-end system combating this variability using a large-area, high-density sensor array and a robust classification algorithm. EMG electrodes are fabricated on a flexible substrate and interfaced to a custom wireless device for 64-channel signal acquisition and streaming. We use brain-inspired high-dimensional (HD) computing for processing EMG features in one-shot learning. The HD algorithm is tolerant to noise and electrode misplacement and can quickly learn from few gestures without gradient descent or back-propagation. We achieve an average classification accuracy of 96.64% for five gestures, with only 7% degradation when training and testing across different days. Our system maintains this accuracy when trained with only three trials of gestures; it also demonstrates comparable accuracy with the state-of-the-art when trained with one trial

Three is a crowd - inefficient communication in the multi-player electronic mail game

In a two-player stag hunt with asymmetric information, players may lock each other into requiring a large number of confirmations and confirmations of confirmations from one another before eventually acting. This intuition has been formalized in the electronic mail game (EMG). The literature provides extensions on the EMG that eliminate inefficient equilibria, suggesting that no formal rules are needed to prevent players from playing inefficiently. The present paper investigates whether these results extend to the multi-player EMG. We show that standard equilibrium refinements cannot eliminate inefficient equilibria. While two players are predicted to play efficiently, many players need formal rules telling them when who talks to whom.Multi-Player Electronic Mail Game, Collective Action, Communication Networks