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Journal articleVujaklija 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: 1743-0003Background 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.
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Journal articleFarina 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: 0270-6474e 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
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Journal articleSchweisfurth 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: 1-6Targeted 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.
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Conference paperUbeda 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 -
Journal articleDel Vecchio A, Negro F, Felici F, et al., 2017,
Distribution of muscle fiber conduction velocity for representative samples of motor units in the full recruitment range of the tibialis anterior muscle
, Acta Physiologica, Vol: 222, ISSN: 1748-1708AimMotor units are recruited in an orderly manner according to the size of motor neurons. Moreover, because larger motor neurons innervate fibers with larger diameters than smaller motor neurons, motor units should be recruited orderly according to their conduction velocity (MUCV). Because of technical limitations, these relations have been previously tested either indirectly or in small motor unit samples that revealed weak associations between motor unit recruitment threshold (RT) and MUCV. Here we analyze the relation between MUCV and RT for large samples of motor units.MethodsTen healthy volunteers completed a series of isometric ankle dorsiflexions at forces up to 70% of the maximum. Multi-channel surface electromyographic signals recorded from the tibialis anterior muscle were decomposed into single motor unit action potentials, from which the corresponding motor unit RT, MUCV, and action potential amplitude were estimated. Established relations between muscle fiber diameter and CV were used to estimate the fiber size.ResultsWithin individual subjects, the distributions of MUCV and fiber diameters were unimodal and did not show distinct populations. MUCV was strongly correlated with RT (mean (SD) R2 = 0.7 (0.09), p<0.001; 406 motor units), which supported the hypothesis that fiber diameter is associated to RT.ConclusionThe results provide further evidence for the relations between motor neuron and muscle fiber properties for large samples of motor units. The proposed methodology for motor unit analysis has also the potential to open new perspectives in the study of chronic and acute neuromuscular adaptations to ageing, training, and pathology.
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Journal articleDel Vecchio A, Negro F, Felici F, et al., 2017,
Associations between Motor Unit Action Potential Parameters and Surface EMG Features
, Journal of Applied Physiology, Vol: 123, Pages: 835-843, ISSN: 0021-8987The surface interference EMG signal provides some information on the neural drive to muscles. However, the association between neural drive to muscle and muscle activation has long been debated with controversial indications due to the unavailability of motor unit population data. In this study, we clarify the potential and limitations of interference EMG analysis to infer motor unit recruitment strategies with an experimental investigation of several concurrently active motor units and of the associated features of the surface EMG. For this purpose, we recorded high-density surface EMG signals during linearly increasing force contractions of the tibialis anterior muscle, up to 70% of maximal force. The recruitment threshold (RT), conduction velocity (MUCV), median frequency (MDFMU) and amplitude (RMSMU) of action potentials of 587 motor units from 13 individuals were assessed and associated to features of the interference EMG. MUCV was positively associated with RT (R2 = 0.64 ± 0.14) whereas MDFMU and RMSMU showed a weaker relation with RT (R2 = 0.11 ± 0.11; 0.39 ± 0.24, respectively). Moreover, the changes in average conduction velocity estimated from the interference EMG predicted well the changes in MUCV (R2 = 0.71), with a strong association to ankle dorsi-flexion force (R2 = 0.81 ± 0.12). Conversely, both the average EMG MDF and RMS were poorly associated to motor unit recruitment. These results clarify the limitations of EMG spectral and amplitude analysis in inferring the neural strategies of muscle control and indicate that, conversely, the average conduction velocity could provide relevant information on these strategies.
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Journal articleBergmeister KD, Vujaklija I, Muceli S, et al., 2017,
Broadband Prosthetic Interfaces: Combining Nerve Transfers and Implantable Multichannel EMG Technology to Decode Spinal Motor Neuron Activity
, FRONTIERS IN NEUROSCIENCE, Vol: 11, ISSN: 1662-453XModern robotic hands/upper limbs may replace multiple degrees of freedom of extremity function. However, their intuitive use requires a high number of control signals, which current man-machine interfaces do not provide. Here, we discuss a broadband control interface that combines targeted muscle reinnervation, implantable multichannel electromyographic sensors, and advanced decoding to address the increasing capabilities of modern robotic limbs. With targeted muscle reinnervation, nerves that have lost their targets due to an amputation are surgically transferred to residual stump muscles to increase the number of intuitive prosthetic control signals. This surgery re-establishes a nerve-muscle connection that is used for sensing nerve activity with myoelectric interfaces. Moreover, the nerve transfer determines neurophysiological effects, such as muscular hyper-reinnervation and cortical reafferentation that can be exploited by the myoelectric interface. Modern implantable multichannel EMG sensors provide signals from which it is possible to disentangle the behavior of single motor neurons. Recent studies have shown that the neural drive to muscles can be decoded from these signals and thereby the user's intention can be reliably estimated. By combining these concepts in chronic implants and embedded electronics, we believe that it is in principle possible to establish a broadband man-machine interface, with specific applications in prosthesis control. This perspective illustrates this concept, based on combining advanced surgical techniques with recording hardware and processing algorithms. Here we describe the scientific evidence for this concept, current state of investigations, challenges, and alternative approaches to improve current prosthetic interfaces.
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Journal articleKarimimehr K, Marateb HR, Muceli S, et al.,
A Real-Time Method for Decoding the Neural Drive to Muscles Using Single-Channel Intra-Muscular EMG Recordings
, International Journal of Neural Systems, ISSN: 1793-6462 -
Journal articleMarkovic M, Karnal H, Graimann B, et al.,
GLIMPSE: Google Glass interface for sensory feedback in myoelectric hand prostheses
, Journal of Neural Engineering, ISSN: 1741-2560Objective:Providing sensory feedback to the user of the prosthesis is an important challenge. The common approach is to use tactile stimulation, which is easy to implement but requires training and has limited information bandwidth. In this study, we propose an alternative approach based onaugmented reality. Approach: We have developed the GLIMPSE, a Google Glassapplication which connects to the prosthesis via a Bluetooth interface and renders the prosthesis states (EMG signals, aperture, force and contact) using augmented reality (see-through display) and sound (bone conduction transducer). The interface was tested in healthy subjects that used the prosthesis with (FB group) and without (NFB group) feedback during a modified clothespins test that allowed to vary the difficulty of the task. The outcome measures were the number of unsuccessful trials, the time to accomplish the task, and the subjective ratings of the relevance of the feedback. Results: There was no difference in performance between FB and NFB groups in the case of a simple task (basic, same-colorclothespins test), but the feedback significantly improved the performance in a more complex task (pins of different resistances). Importantly, the GLIMPSE feedback did not increase the time to accomplish the task. Therefore, the supplemental feedback might be useful in the tasks which are more demanding, and thereby less likely to benefit from learning and feedforward control. The subjects integrated the supplemental feedback with the intrinsic sources (vision and muscle proprioception), developing their own idiosyncratic strategiesto accomplish the task. Significance: The present study demonstratesa novel self-contained, ready-to-deploy, wearable feedback interfacebased on widely used and readily available technology. The interface was successfully tested and was proven to be feasible and functionallybeneficial. The GLIMPSE can be used as a practical solution but also as a general and flexible instrument to
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Journal articleVujaklija I, Roche AD, Hasenoehrl T, et al., 2017,
Translating research on myoelectric control into clinics – are the performance assessment methods adequate?
, Frontiers in Neurorobotics, Vol: 11, ISSN: 1662-5218Missing an upper limb dramatically impairs daily-life activities. Efforts in overcoming the issues arising from this disability have been made in both academia and industry, although their clinical outcome is still limited. Translation of prosthetic research into clinics has been challenging because of the difficulties in meeting the necessary requirements of the market. In this perspective article, we suggest that one relevant factor determining the relatively small clinical impact of myocontrol algorithms for upper limb prostheses is the limit of commonly used laboratory performance metrics. The laboratory conditions, in which the majority of the solutions are being evaluated, fail to sufficiently replicate real-life challenges. We qualitatively support this argument with representative data from seven transradial amputees. Their ability to control a myoelectric prosthesis was tested by measuring the accuracy of offline EMG signal classification, as a typical laboratory performance metrics, as well as by clinical scores when performing standard tests of daily living. Despite all subjects reaching relatively high classification accuracy offline, their clinical scores varied greatly and were not strongly predicted by classification accuracy. We therefore support the suggestion to test myocontrol systems using clinical tests on amputees, fully fitted with sockets and prostheses highly resembling the systems they would use in daily living, as evaluation benchmark. Agreement on this level of testing for systems developed in research laboratories would facilitate clinically relevant progresses in this field.
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Journal articleFarina D, Vujaklija I, Sartori M, et al., 2017,
Man/machine interface based on the discharge timings of spinal motor neurons after targeted muscle reinnervation
, Nature Biomedical Engineering, Vol: 1, ISSN: 2157-846XThe intuitive control of upper-limb prostheses requires a man/machine interface that directly exploits biological signals. Here, we define and experimentally test an offline man/machine interface that takes advantage of the discharge timings of spinal motor neurons. The motor-neuron behaviour is identified by deconvolution of the electrical activity of muscles reinnervated by nerves of a missing limb in patients with amputation at the shoulder or humeral level. We mapped the series of motor-neuron discharges into control commands across multiple degrees of freedom via the offline application of direct proportional control, pattern recognition and musculoskeletal modelling. A series of experiments performed on six patients reveal that the man/machine interface has superior offline performance than conventional direct electromyographic control applied after targeted muscle innervation. The combination of surgical procedures, decoding and mapping into effective commands constitutes an interface with the output layers of the spinal cord circuitry that allows for the intuitive control of multiple degrees of freedom.
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Book chapterUbeda A, Del Vecchio A, Sartori M, et al., 2017,
Corticospinal coherence during frequency-modulated isometric ankle dorsiflexion
, Converging Clinical and Engineering Research on Neurorehabilitation II, Editors: Ibanez, GonzalezVargas, Azorin, Akay, Pons, Publisher: SPRINGER INTERNATIONAL PUBLISHING AG, Pages: 135-140, ISBN: 978-3-319-46668-2In this paper we analyze the role of corticomuscular transmission for the time-varying force control. Corticospinal coherence is assessed during frequency-modulated isometric ankle dorsiflexions. Our preliminary results show a significant coupling between EEG signals and motor unit spike trains at the target frequency, suggesting that low-frequency cortical oscillations may have an important functional role in force control.
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Conference paperMuceli S, Vujaklija I, Jiang N, et al., 2017,
A Biologically-Inspired Robust Control System for Myoelectric Control
, 3rd International Conference on NeuroRehabilitation (ICNR), Publisher: SPRINGER INTERNATIONAL PUBLISHING AG, Pages: 975-979, ISSN: 2195-3562- Author Web Link
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- Citations: 4
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Conference paperVujaklija I, Muceli S, Bergmeister K, et al., 2017,
Prospects of Neurorehabilitation Technologies Based on Robust Decoding of the Neural Drive to Muscles Following Targeted Muscle Reinnervation
, 3rd International Conference on NeuroRehabilitation (ICNR), Publisher: SPRINGER INTERNATIONAL PUBLISHING AG, Pages: 1359-1363, ISSN: 2195-3562- Author Web Link
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- Citations: 1
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Conference paperVujaklija I, Amsuess S, Roche AD, et al., 2017,
Clinical Evaluation of a Socket-Ready Naturally Controlled Multichannel Upper Limb Prosthetic System
, 2nd International Symposium on Wearable Robotics (WeRob), Publisher: SPRINGER INTERNATIONAL PUBLISHING AG, Pages: 3-7, ISSN: 2195-3562- Author Web Link
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- Citations: 7
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Journal articleAszmann OC, Vujaklija I, Roche AD, et al., 2016,
Elective amputation and bionic substitution restore functional hand use after critical soft tissue injuries
, Scientific Reports, Vol: 6, ISSN: 2045-2322Critical soft tissue injuries may lead to a non-functional and insensate limb. In these cases standard reconstructive techniques will not suffice to provide a useful outcome, and solutions outside the biological arena must be considered and offered to these patients. We propose a concept which, after all reconstructive options have been exhausted, involves an elective amputation along with a bionic substitution, implementing an actuated prosthetic hand via a structured tech-neuro-rehabilitation program. Here, three patients are presented in whom this concept has been successfully applied after mutilating hand injuries. Clinical tests conducted before, during and after the procedure, evaluating both functional and psychometric parameters, document the benefits of this approach. Additionally, in one of the patients, we show the possibility of implementing a highly functional and natural control of an advanced prosthesis providing both proportional and simultaneous movements of the wrist and hand for completing tasks of daily living with substantially less compensatory movements compared to the traditional systems. It is concluded that the proposed procedure is a viable solution for re-gaining highly functional hand use following critical soft tissue injuries when existing surgical measures fail. Our results are clinically applicable and can be extended to institutions with similar resources.
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Journal articleVujaklija I, Aszmann OC, Farina D,
New developments in prosthetic arm systems
, Orthopedic Research and Reviews, ISSN: 1179-1462 -
Journal articleVujaklija I, Farina D, Aszmann OC, 2016,
New developments in prosthetic arm systems
, Orthopedic Research and Reviews, Vol: 8, Pages: 31-39, ISSN: 1179-1462Absence of an upper limb leads to severe impairments in everyday life, which can further influence the social and mental state. For these reasons, early developments in cosmetic and body-driven prostheses date some centuries ago, and they have been evolving ever since. Following the end of the Second World War, rapid developments in technology resulted in powered myoelectric hand prosthetics. In the years to come, these devices were common on the market, though they still suffered high user abandonment rates. The reasons for rejection were trifold - insufficient functionality of the hardware, fragile design, and cumbersome control. In the last decade, both academia and industry have reached major improvements concerning technical features of upper limb prosthetics and methods for their interfacing and control. Advanced robotic hands are offered by several vendors and research groups, with a variety of active and passive wrist options that can be articulated across several degrees of freedom. Nowadays, elbow joint designs include active solutions with different weight and power options. Control features are getting progressively more sophisticated, offering options for multiple sensor integration and multi-joint articulation. Latest developments in socket designs are capable of facilitating implantable and multiple surface electromyography sensors in both traditional and osseointegration-based systems. Novel surgical techniques in combination with modern, sophisticated hardware are enabling restoration of dexterous upper limb functionality. This article is aimed at reviewing the latest state of the upper limb prosthetic market, offering insights on the accompanying technologies and techniques. We also examine the capabilities and features of some of academia’s flagship solutions and methods.
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Journal articleKapelner T, Jiang N, Holobar A, et al., 2016,
Motor unit characteristics after targeted muscle reinnervation
, PLOS One, Vol: 11, ISSN: 1932-6203Targeted muscle reinnervation (TMR) is a surgical procedure used to redirect nerves originally controlling muscles of the amputated limb into remaining muscles above the amputation, to treat phantom limb pain and facilitate prosthetic control. While this procedure effectively establishes robust prosthetic control, there is little knowledge on the behavior and characteristics of the reinnervated motor units. In this study we compared the m. pectoralis of five TMR patients to nine able-bodied controls with respect to motor unit action potential (MUAP) characteristics. We recorded and decomposed high-density surface EMG signals into individual spike trains of motor unit action potentials. In the TMR patients the MUAP surface area normalized to the electrode grid surface (0.25 ± 0.17 and 0.81 ± 0.46, p < 0.001) and the MUAP duration (10.92 ± 3.89 ms and 14.03 ± 3.91 ms, p < 0.01) were smaller for the TMR group than for the controls. The mean MUAP amplitude (0.19 ± 0.11 mV and 0.14 ± 0.06 mV, p = 0.07) was not significantly different between the two groups. Finally, we observed that MUAP surface representation in TMR generally overlapped, and the surface occupied by motor units corresponding to only one motor task was on average smaller than 12% of the electrode surface. These results suggest that smaller MUAP surface areas in TMR patients do not necessarily facilitate prosthetic control due to a high degree of overlap between these areas, and a neural information—based control could lead to improved performance. Based on the results we also infer that the size of the motor units after reinnervation is influenced by the size of the innervating motor neuron.
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Journal articleHofmann D, Jiang N, Vujaklija I, et al., 2015,
Bayesian Filtering of Surface EMG for Accurate Simultaneous and Proportional Prosthetic Control.
, IEEE Transactions on Neural Systems and Rehabilitation Engineering, Vol: 24, Pages: 1333-1341, ISSN: 1534-4320The amplitude of the surface EMG (sEMG) is commonly estimated by rectification or other nonlinear transformations, followed by smoothing (low-pass linear filtering). Although computationally efficient, this approach leads to an estimation accuracy with a limited theoretical signal-to-noise ratio (SNR). Since sEMG amplitude is one of the most relevant features for myoelectric control, its estimate has become one of the limiting factors for the performance of myoelectric control applications, such as powered prostheses. In this study, we present a recursive nonlinear estimator of sEMG amplitude based on Bayesian filtering. Furthermore, we validate the advantage of the proposed Bayesian filter over the conventional linear filters through an online simultaneous and proportional control (SPC) task, performed by eight able-bodied subjects and three below-elbow limb deficient subjects. The results demonstrated that the proposed Bayesian filter provides significantly more accurate SPC, particularly for the patients, when compared with conventional linear filters. This result presents a major step toward accurate prosthetic control for advanced multi-function prostheses.
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