Publications by authors named "Dideriksen J"

EMG feedback improves force control of a myoelectric hand prosthesis by conveying the magnitude of the myoelectric signal back to the users via tactile stimulation. The present study aimed to test if this method can be used by a participant with a high-level amputation, and whose muscle used for prosthesis control (pectoralis major) was not intuitively related to hand function. Vibrotactile feedback was delivered to the participant's torso, while the control was tested using EMG from three different muscles.

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Closed-loop myoelectric prostheses, which combine supplementary sensory feedback and electromyography (EMG) based control, hold the potential to narrow the divide between natural and bionic hands. The use of these devices, however, requires dedicated training. Therefore, it is crucial to develop methods that quantify how users acquire skilled control over their prostheses to effectively monitor skill progression and inform the development of interfaces that optimize this process.

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Background: Closing the control loop in myoelectric prostheses by providing artificial somatosensory feedback is recognized as an important goal. However, designing a feedback interface that is effective in realistic conditions is still a challenge. Namely, in some situations, feedback can be redundant, as the information it provides can be readily obtained through hearing or vision (e.

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Bidirectional human-machine interfaces involve commands from the central nervous system to an external device and feedback characterizing device state. Such feedback may be elicited by electrical stimulation of somatosensory nerves, where a task-relevant variable is encoded in stimulation amplitude or frequency. Recently, concurrent modulation in amplitude and frequency (multimodal encoding) was proposed.

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State-of-the-art myoelectric hand prostheses provide multi-functional control but lack somatosensory feedback. To accommodate the full functionality of a dexterous prosthesis, the artificial sensory feedback needs to convey several degrees of freedom (DoF) simultaneously. However, this is a challenge with current methods as they are characterized by a low information bandwidth.

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Catechol--methyltransferase (COMT) is a key enzyme in the metabolism of catecholamines. Substrates of the enzyme include neurotransmitters such as dopamine and epinephrine, and therefore, COMT plays a central role in neurobiology. Since COMT also metabolizes catecholamine drugs such as L-DOPA, variation in COMT activity could affect pharmacokinetics and drug availability.

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Changes in the discharge characteristics of motor units as well as in the maximum force-producing capacity of the muscle are observed following training, aging, and fatiguability. The ability to measure the adaptations in the neuromuscular properties underlying these changes experimentally, however, is limited. In this study we used a computational model to systematically investigate the effects of various neural and muscular adaptations on motor unit recruitment thresholds, average motor unit discharge rates in submaximal contractions, and maximum force.

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Closing the prosthesis control loop by providing artificial somatosensory feedback can improve utility and user experience. Additionally, closed-loop control should be more robust with respect to disturbance, but this might depend on the type of feedback provided. Thus, the present study investigates and compares the performance of EMG and force feedback in the presence of control disturbances.

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Just-noticeable difference (JND), indicating the ability to accurately identify small differences in stimulation parameters, can be used to choose more sensitive stimulation methods as well as to calibrate tactile feedback in closed-loop human-machine interfacing. The JND is typically estimated using a forced-choice-discrimination task, in which two stimuli with different intensities are delivered separated by a brief pause. In the applications of tactile feedback, however, the stimulation parameters are typically modulated continuously.

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. Closed-loop prosthesis interfaces, which combine electromyography (EMG)-based control with supplementary feedback, represent a promising direction for developing the next generation of bionic limbs. However, we still lack an understanding of how users utilize these interfaces and how to evaluate competing solutions.

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Electrotactile stimulation has been commonly used in human-machine interfaces to provide feedback to the user, thereby closing the control loop and improving performance. The encoding approach, which defines the mapping of the feedback information into stimulation profiles, is a critical component of an electrotactile interface. Ideally, the encoding will provide a high-fidelity representation of the feedback variable while being easy to perceive and interpret by the subject.

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Approximate entropy of isometric force is a popular measure to characterize behavioral changes across muscle contraction conditions. The degree to which force entropy characterizes the randomness of the motor control strategy, however, is not known. In this study, we used a computational model to investigate the correlation between approximate entropy of the synaptic input to a motor neuron pool, the neural drive to muscle (cumulative spike train; CST), and the force.

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Although maximal force increases following short-term isometric strength training, the rate of force development (RFD) may remain relatively unaffected. The underlying neural and muscular mechanisms during rapid contractions after strength training are largely unknown. Since strength training increases the neural drive to muscles, it may be hypothesized that there are distinct neural or muscular adaptations determining the change in RFD independently of an increase in maximal force.

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Electro- and vibro-tactile stimulation are commonly employed for feedback in closed-loop human-machine interfacing. Although these feedback systems have been extensively investigated individually, they are rarely objectively compared. In this study, two state-of-the-art stimulation units (concentric electrode and C2-tactor) similar in shape and size were compared in psychometric and online control tests.

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Supplemental sensory feedback for myoelectric prostheses can provide both psychosocial and functional benefits during prosthesis control. However, the impact of feedback depends on multiple factors and there is insufficient understanding about the fundamental role of such feedback in prosthesis use. The framework of human motor control enables us to systematically investigate the user-prosthesis control loop.

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The implementation of somatosensory feedback in upper limb myoelectric prostheses is an important step towards the restoration of lost sensory-motor functions. EMG feedback is a recently proposed method for closing the control loop wherein the myoelectric signal that drives the prosthesis is also used to generate the feedback provided to the user. Therefore, the characteristics of the myoelectric signal (variability and sensitivity) are likely to significantly affect the ability of the subject to utilize this feedback for online control of the prosthesis.

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. Coactivation of gamma and alpha motor neuron activity ensures that muscle spindle responsiveness is maintained during muscle contractions. However, some evidence suggests that the activity of gamma motor neurons is phase-advanced with respect to that of alpha motor neurons during manual control tasks.

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Background: Despite important advancements in control and mechatronics of myoelectric prostheses, the communication between the user and his/her bionic limb is still unidirectional, as these systems do not provide somatosensory feedback. Electrotactile stimulation is an attractive technology to close the control loop since it allows flexible modulation of multiple parameters and compact interface design via multi-pad electrodes. However, the stimulation interferes with the recording of myoelectric signals and this can be detrimental to control.

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Aims: Atrioventricular block (AVB) of unknown aetiology is rare in the young, and outcome in these patients is unknown. We aimed to assess long-term morbidity and mortality in young patients with AVB of unknown aetiology.

Methods And Results: We identified all Danish patients younger than 50 years receiving a first pacemaker due to AVB between January 1996 and December 2015.

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We investigated changes in motor unit (MU) behavior and vasti-muscle contractile properties during sustained submaximal fatiguing contractions with a new time-domain tracking technique to understand the mechanisms responsible for task failure. Sixteen participants performed a nonfatiguing 15-s isometric knee extension at 50% of the maximum voluntary (MVC) torque, followed by a 30% MVC sustained contraction until exhaustion. Two grids of 64 surface electromyography electrodes were placed over vastus medialis and lateralis.

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Objective: Artificial proprioceptive feedback from a myoelectric prosthesis is an important aspect in enhancing embodiment and user satisfaction, possibly lowering the demand for visual attention while controlling a prosthesis in everyday tasks. Contemporary myoelectric prostheses are advanced mechatronic systems with multiple degrees of freedom, and therefore, to communicate the prosthesis state, the feedback interface needs to transmit several variables simultaneously. In the present study, two different configurations for conveying proprioceptive information of wrist rotation and hand aperture through multichannel electrotactile stimulation were developed and evaluated during online myoelectric control.

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Sensory substitution by electrotactile stimulation has been widely investigated for improving the functionality of human-machine interfaces. Few studies, however, have objectively compared different ways in which such systems can be implemented. In this study, we compare encoding of a feedback variable in stimulation pulse width or stimulation frequency during a closed-loop control task.

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The ability to produce rapid forces requires quick motor unit recruitment, high motor unit discharge rates, and fast motor unit force twitches. The relative importance of these parameters for maximum rate of force development (RFD), however, is poorly understood. In this study, we systematically investigated these relationships using a computational model of motor unit pool activity and force.

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The rectified surface EMG signal is commonly used as an estimator of the neural drive to muscles and therefore to infer sources of synaptic input to motor neurons. Loss of EMG amplitude due to the overlap of motor unit action potentials (amplitude cancellation), however, may distort the spectrum of the rectified EMG and thereby its correlation with the neural drive. In this study, we investigated the impact of amplitude cancelation on this correlation using analytical derivations and a computational model of motor neuron activity, force, and the EMG signal.

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Spike-triggered averaging is a commonly used technique for the estimation of motor unit twitches during voluntary contractions, although the obtained twitch estimates are known to be inaccurate in several conditions. Nevertheless, it is commonly assumed that a careful selection of the triggers may reduce the inaccuracy. This study aimed to analyze the impact of trigger selection criteria and thereby to identify the minimum estimation errors using a computational neuromuscular model.

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