Publications
788 results found
Dideriksen JL, Negro F, Falla D, et al., 2018, Coherence of the surface EMG and common synaptic input to motor neurons, Frontiers in Human Neuroscience, Vol: 12, ISSN: 1662-5161
Coherence between electromyographic (EMG) signals is often used to infer the common synaptic input to populations of motor neurons. This analysis, however, may be limited due to the filtering effect of the motor unit action potential waveforms. This study investigated the ability of surface EMG–EMG coherence to predict common synaptic input to motor neurons. Surface and intramuscular EMG were recorded from two locations of the tibialis anterior muscle during steady ankle dorsiflexions at 5 and 10% of the maximal force in 10 healthy individuals. The intramuscular EMG signals were decomposed to identify single motor unit spike trains. For each trial, the strength of the common input in different frequency bands was estimated from the coherence between two cumulative spike trains, generated from sets of single motor unit spike trains (reference measure). These coherence values were compared with those obtained from the coherence between the surface EMG signals (raw, rectified, and high-passed filtered at 250 Hz before rectification) using linear regression. Overall, the high-pass filtering of the EMG prior to rectification did not substantially change the results with respect to rectification only. For both signals, the correlation of EMG coherence with motor unit coherence was strong at 5% MVC (r2 > 0.8; p < 0.01), but only for frequencies > 5 Hz. At 10% MVC, the correlation between EMG and motor unit coherence was only significant for frequencies > 15 Hz (r2 > 0.8; p < 0.01). However, when using raw EMG for coherence analysis, the only significant relation with motor unit coherence was observed for the bandwidth 5–15 Hz (r2 > 0.68; p = 0.04). In all cases, there was no association between motor unit and EMG coherence for frequencies < 5 Hz (r2 ≤ 0.2; p ≥ 0.51). In addition, a substantial error in the best linear fit between motor unit and EMG coherence was always present. In conclusion, high-frequency (>5 Hz) common synapt
Yavuz US, Negro F, Diedrichs R, et al., 2018, Reciprocal inhibition between motor neurons of the tibialis anterior and triceps surae in humans, Journal of Neurophysiology, Vol: 119, Pages: 1699-1706, ISSN: 0022-3077
Motor neurons innervating antagonist muscles receive reciprocal inhibitory afferent inputs to facilitate the joint movement in the two directions. The present study investigates the mutual transmission of reciprocal inhibitory afferent inputs between the tibialis anterior (TA) and triceps surae (soleus and medial gastrocnemius) motor units. We assessed this mutual mechanism in large populations of motor units for building a statistical distribution of the inhibition amplitudes during standardized input to the motor neuron pools to minimize the effect of modulatory pathways. Single motor unit activities were identified using high-density surface electromyography (HDsEMG) recorded from the TA, soleus (Sol), and medial gastrocnemius (GM) muscles during isometric dorsi- and plantarflexion. Reciprocal inhibition on the antagonist muscle was elicited by electrical stimulation of the tibial (TN) or common peroneal nerves (CPN). The probability density distributions of reflex strength for each muscle were estimated to examine the strength of mutual transmission of reciprocal inhibitory input. The results showed that the strength of reciprocal inhibition in the TA motor units was fourfold greater than for the GM and the Sol motor units. This suggests an asymmetric transmission of reciprocal inhibition between ankle extensor and flexor muscles. This asymmetry cannot be explained by differences in motor unit type composition between the investigated muscles since we sampled low-threshold motor units in all cases. Therefore, the differences observed for the strength of inhibition are presumably due to a differential reciprocal spindle afferent input and the relative contribution of nonreciprocal inhibitory pathways.
De Nunzio AM, Yavuz US, Martinez-Valdes E, et al., 2018, Electro-tactile stimulation of the posterior neck induces body anteropulsion during upright stance., Exp Brain Res, Vol: 236, Pages: 1471-1478
Sensory information conveyed along afferent fibers from muscle and joint proprioceptors play an important role in the control of posture and gait in humans. In particular, proprioceptive information from the neck is fundamental in supplying the central nervous system with information about the orientation and movement of the head relative to the rest of the body. The previous studies have confirmed that proprioceptive afferences originating from the neck region, evoked via muscle vibration, lead to strong body-orienting effects during static conditions (e.g., leaning of the body forwards or backwards, depending on location of vibration). However, it is not yet certain in humans, whether the somatosensory receptors located in the deep skin (cutaneous mechanoreceptors) have a substantive contribution to postural control, as vibratory stimulation encompasses the receptive field of all the somatosensory receptors from the skin to the muscles. The aim of this study was to investigate the postural effect of cutaneous mechanoreceptor afferences using electro-tactile stimulation applied to the neck. Ten healthy volunteers (8M, 2F) were evaluated. The average position of their centre of foot pressure (CoP) was acquired before, during, and after a subtle electro-tactile stimulation over their posterior neck (mean ± SD = 5.1 ± 2.3 mA at 100 Hz-140% of the perception threshold) during upright stance with their eyes closed. The electro-tactile stimulation led to a body-orienting effect with the subjects consistently leaning forward. An average shift of the CoP of 12.1 ± 11.9 mm (mean ± SD) was reported, which significantly (p < 0.05) differed from its average position under a control condition (no stimulation). These results indicate that cutaneous mechanoreceptive inflow from the neck is integrated to control stance. The findings are relevant for the
Franceschi M, Seminara L, Dosen S, et al., 2018, Live Demonstration: Electrotactile feedback from an electronic skin through flexible electrode matrix, ISSN: 0271-4310
Closing the prosthesis control loop by providing tactile sensory feedback to the user is a key point in research on active prosthetics as well as an often cited requirement of the prosthesis users.
Martinez-Valdes E, Negro F, Falla D, et al., 2018, Surface electromyographic amplitude does not identify differences in neural drive to synergistic muscles., J Appl Physiol (1985), Vol: 124, Pages: 1071-1079
Surface electromyographic (EMG) signal amplitude is typically used to compare the neural drive to muscles. We experimentally investigated this association by studying the motor unit (MU) behavior and action potentials in the vastus medialis (VM) and vastus lateralis (VL) muscles. Eighteen participants performed isometric knee extensions at four target torques [10, 30, 50, and 70% of the maximum torque (MVC)] while high-density EMG signals were recorded from the VM and VL. The absolute EMG amplitude was greater for VM than VL ( P < 0.001), whereas the EMG amplitude normalized with respect to MVC was greater for VL than VM ( P < 0.04). Because differences in EMG amplitude can be due to both differences in the neural drive and in the size of the MU action potentials, we indirectly inferred the neural drives received by the two muscles by estimating the synaptic inputs received by the corresponding motor neuron pools. For this purpose, we analyzed the increase in discharge rate from recruitment to target torque for motor units matched by recruitment threshold in the two muscles. This analysis indicated that the two muscles received similar levels of neural drive. Nonetheless, the size of the MU action potentials was greater for VM than VL ( P < 0.001), and this difference explained most of the differences in EMG amplitude between the two muscles (~63% of explained variance). These results indicate that EMG amplitude, even following normalization, does not reflect the neural drive to synergistic muscles. Moreover, absolute EMG amplitude is mainly explained by the size of MU action potentials. NEW & NOTEWORTHY Electromyographic (EMG) amplitude is widely used to compare indirectly the strength of neural drive received by synergistic muscles. However, there are no studies validating this approach with motor unit data. Here, we compared between-muscles differences in surface EMG amplitude and motor unit behavior. The results clarify the limitations of surface EM
Markovic M, Schweisfurth MA, Engels LF, et al., 2018, The clinical relevance of advanced artificial feedback in the control of a multi-functional myoelectric prosthesis, Journal of NeuroEngineering and Rehabilitation, Vol: 15
© 2018 The Author(s). Background: To effectively replace the human hand, a prosthesis should seamlessly respond to user intentions but also convey sensory information back to the user. Restoration of sensory feedback is rated highly by the prosthesis users, and feedback is critical for grasping in able-bodied subjects. Nonetheless, the benefits of feedback in prosthetics are still debated. The lack of consensus is likely due to the complex nature of sensory feedback during prosthesis control, so that its effectiveness depends on multiple factors (e.g., task complexity, user learning). Methods: We evaluated the impact of these factors with a longitudinal assessment in six amputee subjects, using a clinical setup (socket, embedded control) and a range of tasks (box and blocks, block turn, clothespin and cups relocation). To provide feedback, we have proposed a novel vibrotactile stimulation scheme capable of transmitting multiple variables from a multifunction prosthesis. The subjects wore a bracelet with four by two uniformly placed vibro-tactors providing information on contact, prosthesis state (active function), and grasping force. The subjects also completed a questionnaire for the subjective evaluation of the feedback. Results: The tests demonstrated that feedback was beneficial only in the complex tasks (block turn, clothespin and cups relocation), and that the training had an important, task-dependent impact. In the clothespin relocation and block turn tasks, training allowed the subjects to establish successful feedforward control, and therefore, the feedback became redundant. In the cups relocation task, however, the subjects needed some training to learn how to properly exploit the feedback. The subjective evaluation of the feedback was consistently positive, regardless of the objective benefits. These results underline the multifaceted nature of closed-loop prosthesis control as, depending on the context, the same feedback interface can have different
Vujaklija I, Shalchyan V, Kamavuako EN, et al., 2018, Online mapping of EMG signals into kinematics by autoencoding, Journal of NeuroEngineering and Rehabilitation, Vol: 15, ISSN: 1743-0003
Background In this paper, we propose a nonlinear minimally supervised method based on auto-encoding (AEN) of EMG for myocontrol. The proposed method was tested against the state-of-the-art (SOA) control scheme using a Fitts’ law approach. MethodsSeven able-bodied subjects performed a series of target acquisition myoelectric control tasks using the AEN and SOA algorithms for controlling two degrees-of-freedom (radial/ulnar deviation and flexion/extension of the wrist), and their online performance was characterized by six metrics. Results Both methods allowed a completion rate close to 100%, however AEN outperformed SOA for all other performance metrics, e.g. it allowed to perform the tasks on average in half the time with respect to SOA. Moreover, the amount of information transferred by the proposed method in bit/s was nearly twice the throughput of SOA. ConclusionsThese results show that autoencoders can map EMG signals into kinematics with the potential of providing intuitive and dexterous control of artificial limbs for amputees.
Luu BL, Muceli S, Saboisky JP, et al., 2018, Motor unit territories in human genioglossus estimated with multichannel intramuscular electrodes, Journal of Applied Physiology, Vol: 124, Pages: 664-671, ISSN: 8750-7587
The discharge patterns of genioglossus motor units during breathing have been well-characterized in previous studies, but their localization and territories are not known. In this study, we used two newly developed intramuscular multichannel electrodes to estimate the territories of genioglossus motor units in the anterior and posterior regions of the muscle. Seven healthy men participated. Each electrode contained fifteen bipolar channels, separated by 1 mm, and was inserted percutaneously below the chin, perpendicular to the skin, to a depth of 36 mm. Single motor unit activity was recorded with subjects awake, supine, and breathing quietly through a nasal mask for 180 s. Motor unit territories were estimated from the spike-triggered averages of the electromyographic signal from each channel. A total of 30 motor units were identified: 22 expiratory tonic, 1 expiratory phasic, 2 tonic, 3 inspiratory tonic, and 2 inspiratory phasic. Motor units appeared to be clustered based on unit type, with peak activities for expiratory units predominantly located in the anterior and superficial fibers of genioglossus and inspiratory units in the posterior region. Of these motor unit types, expiratory tonic units had the largest estimated territory, a mean 11.3 mm (SD 1.9). Estimated territories of inspiratory motor units ranged from 3 to 6 mm. In accordance with the distribution of motor unit types, the estimated territory of genioglossus motor units varied along the sagittal plane, decreasing from anterior to posterior. Our findings suggest that genioglossus motor units have large territories relative to the cross-sectional size of the muscle.
Farina D, Geng, Dong, et al., 2018, Psychophysical evaluation of subdermal electrical stimulation in relation to prosthesis sensory feedback, IEEE Transactions on Neural Systems and Rehabilitation Engineering, Vol: 26, Pages: 709-715, ISSN: 1534-4320
This paper evaluated the psychophysical properties of subdermal electrical stimulation to investigate its feasibility in providing sensory feedback for limb prostheses. The detection threshold (DT), pain threshold (PT), just noticeable difference (JND), as well as the elicited sensation quality, comfort, intensity, and location were assessed in 16 healthy volunteers during stimulation of the ventral and dorsal forearm with subdermal electrodes. Moreover, the results were compared with those obtained from transcutaneous electrical stimulation. Despite a lower DT and PT, subdermal stimulation attained a greater relative dynamic range (i.e., PT/DT) and significantly smaller JNDs for stimulation amplitude. Muscle twitches and movements were more commonly elicited by surface stimulation, especially at the higher stimulation frequencies, whereas the pinprick sensation was more often reported with subdermal stimulation. Less comfort was perceived in subdermal stimulation of the ventral forearm at the highest tested stimulation frequency of 100 Hz. In summary, subdermal electrical stimulation was demonstrated to be able to produce similar sensation quality as transcutaneous stimulation and outperformed the latter in terms of energy efficiency and sensitivity. These results suggest that stimulation through implantable subdermal electrodes may lead to an efficient and compact sensory feedback system for substituting the lost sense in amputees.
Lin C, Wang B, Jiang N, et al., 2018, Robust extraction of basis functions for simultaneous and proportional myoelectric control via sparse non-negative matrix factorization, Journal of Neural Engineering, Vol: 15, ISSN: 1741-2552
Objective. This paper proposes a novel simultaneous and proportional multiple degree of freedom (DOF) myoelectric control method for active prostheses. Approach. The approach is based on non-negative matrix factorization (NMF) of surface EMG signals with the inclusion of sparseness constraints. By applying a sparseness constraint to the control signal matrix, it is possible to extract the basis information from arbitrary movements (quasi-unsupervised approach) for multiple DOFs concurrently. Main Results. In online testing based on target hitting, able-bodied subjects reached a greater throughput (TP) when using sparse NMF (SNMF) than with classic NMF or with linear regression (LR). Accordingly, the completion time (CT) was shorter for SNMF than NMF or LR. The same observations were made in two patients with unilateral limb deficiencies. Significance. The addition of sparseness constraints to NMF allows for a quasi-unsupervised approach to myoelectric control with superior results with respect to previous methods for the simultaneous and proportional control of multi-DOF. The proposed factorization algorithm allows robust simultaneous and proportional control, is superior to previous supervised algorithms, and, because of minimal supervision, paves the way to online adaptation in myoelectric control.
Farina D, Ubeda, Sartori, et al., 2018, Estimation of Neuromuscular Primitives from EEG Slow Cortical Potentials in Incomplete Spinal Cord Injury Individuals for a New Class of Brain-Machine Interfaces, Frontiers in Computational Neuroscience, Vol: 12, ISSN: 1662-5188
One of the current challenges in human motor rehabilitation is the robust application of Brain-Machine Interfaces to assistive technologies such as powered lower limb exoskeletons. Reliable decoding of motor intentions and accurate timing of the robotic device actuation is fundamental to optimally enhance the patient's functional improvement. Several studies show that it may be possible to extract motor intentions from electroencephalographic (EEG) signals. These findings, although notable, suggests that current techniques are still far from being systematically applied to an accurate real-time control of rehabilitation or assistive devices. Here we propose the estimation of spinal primitives of multi-muscle control from EEG, using electromyography (EMG) dimensionality reduction as a solution to increase the robustness of the method. We successfully apply this methodology, both to healthy and incomplete spinal cord injury (SCI) patients, to identify muscle contraction during periodical knee extension from the EEG. We then introduce a novel performance metric, which accurately evaluates muscle primitive activations.
Kapelner T, Negro F, Aszmann OC, et al., 2018, Decoding Motor Unit Activity from Forearm Muscles: Perspectives for Myoelectric Control, IEEE Transactions on Neural Systems and Rehabilitation Engineering, Vol: 26, Pages: 244-251, ISSN: 1534-4320
© 2017 IEEE. We prove the feasibility of decomposing high density surface EMG signals from forearm muscles in non-isometric wrist motor tasks of normally limbed and limb-deficient individuals with the perspective of using the decoded neural information for prosthesis control. For this purpose, we recorded surface EMG signals during motions of three degrees of freedom of the wrist in seven normally limbed subjects and two patients with limb deficiency. The signals were decomposed into individual motor unit activity with a convolutive blind source separation algorithm. On average, for each subject, 16 ± 7 motor units were identified per motor task. The discharge timings of these motor units were estimated with an accuracy > 85%. Moreover, the activity of 6 ± 5 motor units per motor task was consistently detected in all repetitions of the same task. The joint angle at which motor units were first identified was 62.5 ± 26.4% of the range of motion, indicating a prevalence in the identification of high threshold motor units. These findings prove the feasibility of accurate identification of the neural drive to muscles in contractions relevant for myoelectric control, allowing the development of a new generation of myocontrol methods based on motor unit spike trains.
Kersting NM, Jiang N, Dremstrup K, et al., 2018, Associative Plasticity Induced by a Brain-Computer Interface Based on Movement-Related Cortical Potentials, Brain-Computer Interfaces Handbook: Technological and Theoretical Advances, Pages: 669-684, ISBN: 9780367375454
This chapter presents the basic concepts of a brain-computer-interface (BCI) designed for neuromodulation that is based on known theories of memory storage and learning. Initially, an overview is provided of the control signal, the movement-related cortical potential (MRCP), its advantages over other signal modalities, and its neural generators. This is followed by a detailed account of factors that affect the MRCP morphology such as task parameters, shifts in user attention and plasticity, and insights into algorithm design for both detection and classification in an online self-paced BCI. Finally, the applications of this type of associative BCI to more complex tasks such as human gait and in the clinical environment with patients are presented.
Granucci G, Garavaglia S, Agostinetti P, et al., 2018, Expected performances of the DTT heating systems, Pages: 1184-1187
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Turolla A, Venneri A, Farina D, et al., 2018, Rehabilitation Induced Neural Plasticity after Acquired Brain Injury., Neural Plast, Vol: 2018
Farina D, Castronovo AM, Vujaklija I, et al., 2017, Common synaptic input to motor neurons and neural drive to targeted reinnervated muscles, Journal of Neuroscience, Vol: 37, Pages: 11285-11292, ISSN: 0270-6474
e compared the behavior of motor neurons innervating their physiological muscle targets with motor neurons from the same spinal segment whose axons were surgically redirected to remnant muscles (targeted muscle reinnervation). The objective was to assess whether motor neurons with nonphysiological innervation receive similar synaptic input and could be voluntary controlled as motor neurons with natural innervation. For this purpose, we acquired high-density EMG signals from the biceps brachii in 5 male transhumeral amputees who underwent targeted reinnervation of this muscle by the ulnar nerve and from the first dorsal interosseous muscle of 5 healthy individuals to investigate the natural innervation of the ulnar nerve. The same recordings were also performed from the biceps brachii muscle of additional 5 able-bodied individuals. The EMG signals were decomposed into discharges of motor unit action potentials. Motor neurons were progressively recruited for the full range of submaximal muscle activation in all conditions. Moreover, their discharge rate significantly increased from recruitment to target activation level in a similar way across the subject groups. Motor neurons across all subject groups received common synaptic input as identified by coherence analysis of their spike trains. However, the relative strength of common input in both the delta (0.5–5 Hz) and alpha (5–13 Hz) bands was significantly smaller for the surgically reinnervated motor neuron pool with respect to the corresponding physiologically innervated one. The results support the novel approach of motor neuron interfacing for prosthesis control and provide new insights into the role of afferent input on motor neuron activity. SIGNIFICANCE STATEMENT Targeted muscle reinnervation surgically redirects nerves that lost their target in the amputation into redundant muscles in the region of the stump. The study of the behavior of motor neurons following this surgery is needed for designin
Farina D, Yao, Sheng, et al., 2017, Performance of Brain-Computer Interfacing Based on Tactile Selective Sensation and Motor Imagery, IEEE Transactions on Neural Systems and Rehabilitation Engineering, Vol: 26, Pages: 60-68, ISSN: 1534-4320
A large proportion of users do not achieve adequate control using current non-invasive brain–computer interfaces (BCIs). This issue has being coined “BCI-Illiteracy” and is observed among different BCI modalities. Here, we compare the performance and the BCI-illiteracy rate of a tactile selective sensation (SS) and motor imagery (MI) BCI, for a large subject samples. We analyzed 80 experimental sessions from 57 subjects with two-class SS protocols. For SS, the group average performance was 79.8 ± 10.6%, with 43 out of the 57 subjects (75.4%) exceeding the 70% BCI-illiteracy threshold for left- and right-hand SS discrimination. When compared with previous results, this tactile BCI outperformed all other tactile BCIs currently available. We also analyzed 63 experimental sessions from 43 subjects with two-class MI BCI protocols, where the group average performance was 77.2 ± 13.3%, with 69.7% of the subjects exceeding the 70% performance threshold for left- and right-hand MI. For within-subject comparison, the 24 subjects who participated to both the SS and MI experiments, the BCI performance was superior with SS than MI especially in beta frequency band (p < 0.05), with enhanced R2 discriminative information in the somatosensory cortex for the SS modality. Both SS and MI showed a functional dissociation between lower alpha ([8 10] Hz) and upper alpha ([10 13] Hz) bands, with BCI performance significantly better in the upper alpha than the lower alpha (p < 0.05) band. In summary, we demonstrated that SS is a promising BCI modality with low BCI illiteracy issue and has great potential in practical applications reaching large population.
Mrachacz-Kersting N, Voigt M, Stevenson AJT, et al., 2017, The effect of type of afferent feedback timed with motor imagery on the induction of cortical plasticity., Brain Res, Vol: 1674, Pages: 91-100
A peripherally generated afferent volley that arrives at the peak negative (PN) phase during the movement related cortical potential (MRCP) induces significant plasticity at the cortical level in healthy individuals and chronic stroke patients. Transferring this type of associative brain-computer interface (BCI) intervention into the clinical setting requires that the proprioceptive input is comparable to the techniques implemented during the rehabilitation process. These consist mainly of functional electrical stimulation (FES) and passive movement induced by an actuated orthosis. In this study, we compared these two interventions (BCIFES and BCIpassive) where the afferent input was timed to arrive at the motor cortex during the PN of the MRCP. Twelve healthy participants attended two experimental sessions. They were asked to perform 30 dorsiflexion movements timed to a cue while continuous electroencephalographic (EEG) data were collected from FP1, Fz, FC1, FC2, C3, Cz, C4, CP1, CP2, and Pz, according to the standard international 10-20 system. MRCPs were extracted and the PN time calculated. Next, participants were asked to imagine the same movement 30 times while either FES (frequency: 20Hz, intensity: 8-35mAmp) or a passive ankle movement (amplitude and velocity matched to a normal gait cycle) was applied such that the first afferent inflow would coincide with the PN of the MRCP. The change in the output of the primary motor cortex (M1) was quantified by applying single transcranial magnetic stimuli to the area of M1 controlling the tibialis anterior (TA) muscle and measuring the motor evoked potential (MEP). Spinal changes were assessed pre and post by eliciting the TA stretch reflex. Both BCIFES and BCIpassive led to significant increases in the excitability of the cortical projections to TA (F(2,22)=4.44, p=0.024) without any concomitant changes at the spinal level. These effects were still present 30min after the cessation of both interventions. There was n
Strbac M, Isakovic M, Belic M, et al., 2017, Short- and Long-Term Learning of Feedforward Control of a Myoelectric Prosthesis with Sensory Feedback by Amputees., IEEE Trans Neural Syst Rehabil Eng, Vol: 25, Pages: 2133-2145
Human motor control relies on a combination of feedback and feedforward strategies. The aim of this study was to longitudinally investigate artificial somatosensory feedback and feedforward control in the context of grasping with myoelectric prosthesis. Nine amputee subjects performed routine grasping trials, with the aim to produce four levels of force during four blocks of 60 trials across five days. The electrotactile force feedback was provided in the second and third block using multipad electrode and spatial coding. The first baseline and last validation block (open-loop control) evaluated the effects of long- (across sessions) and short-term (within session) learning, respectively. The outcome measures were the absolute error between the generated and target force, and the number of force saturations. The results demonstrated that the electrotactile feedback improved the performance both within and across sessions. In the validation block, the performance did not significantly decrease and the quality of open-loop control (baseline) improved across days, converging to the performance characterizing closed-loop control. This paper provides important insights into the feedback and feedforward processes in prosthesis control, contributing to the better understanding of the role and design of feedback in prosthetic systems.
Sartori M, Yavuz U, Farina D, 2017, In Vivo Neuromechanics: Decoding Causal Motor Neuron Behavior with Resulting Musculoskeletal Function., Scientific Reports, Vol: 7, ISSN: 2045-2322
Human motor function emerges from the interaction between the neuromuscular and the musculoskeletal systems. Despite the knowledge of the mechanisms underlying neural and mechanical functions, there is no relevant understanding of the neuro-mechanical interplay in the neuro-musculo-skeletal system. This currently represents the major challenge to the understanding of human movement. We address this challenge by proposing a paradigm for investigating spinal motor neuron contribution to skeletal joint mechanical function in the intact human in vivo. We employ multi-muscle spatial sampling and deconvolution of high-density fiber electrical activity to decode accurate α-motor neuron discharges across five lumbosacral segments in the human spinal cord. We use complete α-motor neuron discharge series to drive forward subject-specific models of the musculoskeletal system in open-loop with no corrective feedback. We perform validation tests where mechanical moments are estimated with no knowledge of reference data over unseen conditions. This enables accurate blinded estimation of ankle function purely from motor neuron information. Remarkably, this enables observing causal associations between spinal motor neuron activity and joint moment control. We provide a new class of neural data-driven musculoskeletal modeling formulations for bridging between movement neural and mechanical levels in vivo with implications for understanding motor physiology, pathology, and recovery.
Vieira TM, Botter A, Muceli S, et al., 2017, Specificity of surface EMG recordings for gastrocnemius during upright standing., Scientific Reports, Vol: 7, ISSN: 2045-2322
The relatively large pick-up volume of surface electrodes has for long motivated the concern that muscles other than that of interest may contribute to surface electromyograms (EMGs). Recent findings suggest however the pick-up volume of surface electrodes may be smaller than previously appreciated, possibly leading to the detection of surface EMGs insensitive to muscle activity. Here we combined surface and intramuscular recordings to investigate how comparably action potentials from gastrocnemius and soleus are represented in surface EMGs detected with different inter-electrode distances. We computed the firing instants of motor units identified from intramuscular EMGs detected from gastrocnemius and soleus while five participants stood upright. We used these instants to trigger and average surface EMGs detected from multiple skin regions along gastrocnemius. Results from 66 motor units (whereof 31 from gastrocnemius) revealed the surface-recorded amplitude of soleus action potentials was 6% of that of gastrocnemius and did not decrease for inter-electrode distances smaller than 4 cm. Gastrocnemius action potentials were more likely detected for greater inter-electrode distances and their amplitude increased steeply up to 5 cm inter-electrode distance. These results suggest that reducing inter-electrode distance excessively may result in the detection of surface EMGs insensitive to gastrocnemius activity without substantial attenuation of soleus crosstalk.
Fares H, Seminara L, Ibrahim A, et al., 2017, Distributed sensing and stimulation systems for sense of touch restoration in prosthetics, Pages: 177-180
Modern prostheses aim at restoring the functional and aesthetic characteristics of the lost limb. To foster prosthesis embodiment and functionality, it is necessary to re-establish both volitional control and sensory feedback. Contemporary feedback interfaces presented in research use few sensors and stimulation units to feedback at most two discrete feedback variables (e.g., grasping force and aperture), whereas the human sense of touch relies on a distributed network of mechanoreceptors providing high-fidelity spatial information. To provide this type of feedback in prosthetics, it is necessary to sense tactile information from artificial skin placed on the prosthesis and transmit tactile feedback above the amputation in order to map the interaction between the prosthesis and the environment. This paper will provide a perspective on the use of distributed sensing and electrical stimulation systems for the restoration of the sense of touch in prosthetics.
Seminara L, Franceschi M, Pinna L, et al., 2017, Electronic skin and electrocutaneous stimulation to restore the sense of touch in hand prosthetics, ISSN: 0271-4310
Electronic skin can be integrated into a prosthetic device to endow the prosthesis with artificial cutaneous sensing, thereby partially restoring the sensory information lost due to an amputation. Non-invasive cutaneous electrostimulation transmits the tactile information sensed by the electronic skin on the prosthetic hand to the human brain, through the amputee's afferent nervous system. In this paper, our current benchtop prototype of a distributed sensing-stimulation system is presented, together with the envisaged high-fidelity solution which will be integrated into a real prosthetic hand.
Oliveira AS, De Brito Silva P, Lund M, et al., 2017, Balance training enhances motor coordination during perturbations elicited to a side-step cutting task, Journal of Orthopaedic & Sports Physical Therapy, ISSN: 0190-6011
Study Design: Controlled Laboratory study; Objectives: To study the effects of balance training (BTR) on motor coordination and knee mechanics during perturbed side.step cutting maneuvers in healthy adults. Background: BTR may improve motor coordination, however little is known about the changes in motor coordination during unexpected perturbations to postural control following BTR. Methods: Twenty.six healthy men were randomly assigned to a training group (TG) or control (CG). Before BTR, subjects performed unperturbed, 90° side.step cutting maneuvers and one unexpected perturbed cut (10.cm translation of a moveable platform). The TG participated in a 6.week BTR program while CG participants followed their regular activity schedule. Both groups were re.tested after a 6.week period. Surface electromyography was recorded from 16 muscles of the supporting limb and trunk, as well as kinematics, and ground reaction forces. Motor modules were extracted from the EMG by non.negative matrix factorization. External knee abduction moments were calculated using inverse dynamics equations. Results: BTR resulted in a reduction of the external knee abduction moment (33 ± 25%, p<0.001, ŋp2=0.725), and increased the activation of trunk and proximal hip muscles in specific motor modules during perturbed cutting. BTR also increased burst duration for the motor module related to landing early in the perturbation phase (23 ± 11%, p<0.01, ŋp2=0.532). Conclusion: BTR resulted in altered motor coordination and reduced knee abduction moment during an unexpected perturbation. The previously reported reduction in injury incidence following BTR may be linked to changes in dynamic postural stability and adapted modular neuromuscular control.
Patel GK, Hahne JM, Castellini C, et al., 2017, Context-dependent adaptation improves robustness of myoelectric control for upper-limb prostheses, Journal of Neural Engineering, Vol: 14, ISSN: 1741-2560
Objective. Dexterous upper-limb prostheses are available today to restore grasping, but an effective and reliable feed-forward control is still missing. The aim of this work was to improve the robustness and reliability of myoelectric control by using context information from sensors embedded within the prosthesis. Approach. We developed a context-driven myoelectric control scheme (cxMYO) that incorporates the inference of context information from proprioception (inertial measurement unit) and exteroception (force and grip aperture) sensors to modulate the outputs of myoelectric control. Further, a realistic evaluation of the cxMYO was performed online in able-bodied subjects using three functional tasks, during which the cxMYO was compared to a purely machine-learning-based myoelectric control (MYO). Main results. The results demonstrated that utilizing context information decreased the number of unwanted commands, improving the performance (success rate and dropped objects) in all three functional tasks. Specifically, the median number of objects dropped per round with cxMYO was zero in all three tasks and a significant increase in the number of successful transfers was seen in two out of three functional tasks. Additionally, the subjects reported better user experience. Significance. This is the first online evaluation of a method integrating information from multiple on-board prosthesis sensors to modulate the output of a machine-learning-based myoelectric controller. The proposed scheme is general and presents a simple, non-invasive and cost-effective approach for improving the robustness of myoelectric control.
Gesslbauer B, Hruby LA, Roche AD, et al., 2017, Axonal components of nerves innervating the human arm., Ann Neurol, Vol: 82, Pages: 396-408
OBJECTIVE: Axons traveling within the brachial plexus are responsible for the dexterous control of human arm and hand movements. Despite comprehensive knowledge on the topographical anatomy of nerves innervating the human upper limbs, the definite quantity of sensory and motor axons within this neural network remains elusive. Our aim was to perform a quantitative analysis of the axonal components of human upper limb nerves based on highly specific molecular features from spinal cord level to the terminal nerves at wrist level. METHODS: Nerve specimen harvest at predefined harvesting sites (plexus roots and cords as well as major nerves originating from the brachial plexus innervating the arm and hand) was performed in 9 human heart-beating organ donors. Double immunofluorescence staining using antibodies against choline-acetyltransferase and neurofilament was performed to differentiate motor and sensory axons on nerve cross sections. RESULTS: Three hundred fifty thousand axons emerge from the spinal cord to innervate the human upper limb, of which 10% are motor neurons. In all nerves studied, sensory axons outnumber motor axons by a ratio of at least 9:1. The sensory axon contribution increases when moving distally, whereas only 1,700 motor axons reach the hand to innervate the intrinsic musculature. INTERPRETATION: Our results suggest that upper limb motor execution, and particularly dexterous coordination of hand movement, require an unexpectedly low number of motor neurons, with a large convergence of afferent input for feedback control. Ann Neurol 2017;82:396-408.
Aliakbaryhosseinabadi S, Kamavuako EN, Jiang N, et al., 2017, Influence of dual-tasking with different levels of attention diversion on characteristics of the movement-related cortical potential, Brain Research, Vol: 1674, Pages: 10-19, ISSN: 0006-8993
Dual tasking is defined as performing two tasks concurrently and has been shown to have a significant effect on attention directed to the performance of the main task. In this study, an attention diversion task with two different levels was administered while participants had to complete a cue-based motor task consisting of foot dorsiflexion. An auditory oddball task with two levels of complexity was implemented to divert the user’s attention. Electroencephalographic (EEG) recordings were made from nine single channels. Event-related potentials (ERPs) confirmed that the oddball task of counting a sequence of two tones decreased the auditory P300 amplitude more than the oddball task of counting one target tone among three different tones. Pre-movement features quantified from the movement-related cortical potential (MRCP) were changed significantly between single and dual-task conditions in motor and fronto-central channels. There was a significant delay in movement detection for the case of single tone counting in two motor channels only (237.1–247.4 ms). For the task of sequence counting, motor cortex and frontal channels showed a significant delay in MRCP detection (232.1–250.5 ms). This study investigated the effect of attention diversion in dual-task conditions by analysing both ERPs and MRCPs in single channels. The higher attention diversion lead to a significant reduction in specific MRCP features of the motor task. These results suggest that attention division in dual-tasking situations plays an important role in movement execution and detection. This has important implications in designing real-time brain-computer interface systems.
Schweisfurth MA, Ernst J, Vujaklija I, et al., 2017, Longitudinal high-density EMG classification: Case study in a glenohumeral TMR subject., 2017 International Conference on Rehabilitation Robotics (ICORR), Vol: 2017, Pages: 1-6
Targeted muscle reinnervation (TMR) represents a breakthrough interface for prosthetic control in high-level upper-limb amputees. However, clinically, it is still limited to the direct motion-wise control restricted by the number of reinnervation sites. Pattern recognition may overcome this limitation. Previous studies on EMG classification in TMR patients experienced with myocontrol have shown greater accuracy when using high-density (HD) recordings compared to conventional single-channel derivations. This case study investigates the potential of HD-EMG classification longitudinally over a period of 17 months post-surgery in a glenohumeral amputee. Five experimental sessions, separated by approximately 3 months, were performed. They were timed during a standard rehabilitation protocol that included intensive physio- and occupational therapy, myosignal training, and routine use of the final myoprosthesis. The EMG signals recorded by HD-EMG grids were classified into 12 classes. The first sign of EMG activity was observed in the second experimental session. The classification accuracy over 12 classes was 76% in the third session and ∼95% in the last two sessions. When using training and testing sets that were acquired with a 1-h time interval in between, a much lower accuracy (32%, Session 4) was obtained, which improved upon prosthesis usage (Session 5, 67%). The results document the improvement in EMG classification accuracy throughout the TMR-rehabilitation process.
Ubeda A, Del Vecchio A, Sartori M, et al., 2017, Electromechanical delay in the tibialis anterior muscle during time-varying ankle dorsiflexion, International Conference on Rehabilitation Robotics (ICORR), Publisher: IEEE, Pages: 68-71, ISSN: 1945-7898
Aliakbaryhosseinabadi S, Nlandu Kamavuako E, Farina D, et al., 2017, Effect of attention division on movement detection and execution in dual-task conditions, Pages: 552-555, ISSN: 1948-3546
Dual tasking refers to the simultaneous execution of two tasks with different demands. In this study, we aimed to investigate the effect of a second task on a main task of motor execution and on the ability CP to detect the cortical potential related to the main task from non-invasive electroencephalographic (EEG). Participants were asked to perform a series of cue-based ankle dorsiflexions as the primary task (single task level). In some experimental runs, in addition to the primary task they concurrently attended an auditory oddball paradigm consisting of three tones while they were asked to count the number of sequences of special tones (dual task level). EEG signals were recorded from nine channels centered on Cz. Analysis of event-related potential (ERP) signals from Cz confirmed that the oddball task decreased the attention to the ankle dorsiflexion significantly. Furthermore, movement-related cortical potential (MRCP) analysis revealed that the amplitude of the MRCP and pre-movement slopes were changed significantly. These variations were significantly greater for the EEG channels corresponding to the motor cortex and the frontal-central cortex.
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