Imperial College London

ProfessorDarioFarina

Faculty of EngineeringDepartment of Bioengineering

Chair in Neurorehabilitation Engineering
 
 
 
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Contact

 

+44 (0)20 7594 1387d.farina Website

 
 
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Location

 

RSM 4.15Royal School of MinesSouth Kensington Campus

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Summary

 

Publications

Publication Type
Year
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734 results found

Farina D, Zicher B, Ibáñez J, 2022, Beta inputs to motor neurons do not directly contribute to volitional force modulation, Journal of Physiology

Journal article

Lubel E, Sgambato BG, Barsakcioglu DY, Ibanez J, Tang M-X, Farina Det al., 2022, Kinematics of individual muscle units in natural contractions measured in vivo using ultrafast ultrasound, JOURNAL OF NEURAL ENGINEERING, Vol: 19, ISSN: 1741-2560

Journal article

Vujaklija I, IEEE Member, Ki Jung M, Hasenoehrl T, Roche AD, Sturma A, Muceli S, Senior IEEE Member, Crevenna R, Aszmann OC, Farina D, IEEE Fellowet al., 2022, Biomechanical analysis of body movements of myoelectric prosthesis users during standardized clinical tests, IEEE Transactions on Biomedical Engineering, ISSN: 0018-9294

Objective: The objective clinical evaluation of user's capabilities to handle their prosthesis is done using various tests which primarily focus on the task completion speed and do not explicitly account for the potential presence of compensatory motions. Given that the excessive body compensation is a common indicator of inadequate prosthesis control, tests which include subjective observations on the quality of performed motions have been introduced. However, these metrics are then influenced by the examiner's opinions, skills, and training making them harder to standardize across patient pools and compare across different prosthetic technologies. Here we aim to objectively quantify the severity of body compensations present in myoelectric prosthetic hand users and evaluate the extent to which traditional objective clinical scores are still able to capture them. Methods: We have instructed 9 below-elbow prosthesis users and 9 able-bodied participants to complete three established objective clinical tests: Box-and-Blocks-Test, Clothespin-Relocation-Test, and Southampton-Hand-Assessment-Procedure. During all tests, upper-body kinematics has been recorded. Results: While the analysis showed that there are some correlations between the achieved clinical scores and the individual body segment travel distances and average speeds, there were only weak correlations between the clinical scores and the observed ranges of motion. At the same time, the compensations were observed in all prosthesis users and, for the most part, they were substantial across the tests. Conclusion: The sole reliance on the currently available objective clinical assessment methods seems inadequate as the compensatory movements are prominent in prosthesis users and yet not sufficiently accounted for.

Journal article

Del Vecchio A, Jones RHA, Schofield IS, Kinfe TM, Ibáñez J, Farina D, Baker SNet al., 2022, Interfacing motor units in non-human primates identifies a principal neural component for force control constrained by the size principle, The Journal of Neuroscience, ISSN: 0270-6474

Motor units convert the last neural code of movement into muscle forces. The classic view of motor unit control is that the central nervous system sends common synaptic inputs to motoneuron pools and that motoneurons respond in an orderly fashion dictated by the size principle. This view however is in contrast with the large number of dimensions observed in motor cortex which may allow individual and flexible control of motor units. Evidence for flexible control of motor units may be obtained by tracking motor units longitudinally during tasks with some level of behavioural variability. Here we identified and tracked populations of motor units in the brachioradialis muscle of two macaque monkeys during ten sessions spanning over one month with a broad range of rate of force development (1.8 - 38.6 N∙m∙s-1). We found a very stable recruitment order and discharge characteristics of the motor units over sessions and contraction trials. The small deviations from orderly recruitment were fully predicted by the motor unit recruitment intervals, so that small shifts in recruitment thresholds happened only during contractions at high rate of force development. Moreover, we also found that one component explained more than ~50% of the motor unit discharge rate variance, and that the remaining components represented a time-shifted version of the first. In conclusion, our results show that motoneurons recruitment is determined by the interplay of the size principle and common input and that this recruitment scheme is not violated over time nor by the speed of the contractions.

Journal article

de Oliveira DS, Casolo A, Balshaw TG, Maeo S, Lanza MB, Martin NRW, Maffulli N, Kinfe TM, Eskofier BM, Folland JP, Farina D, Del Vecchio Aet al., 2022, Neural decoding from surface high-density EMG signals: influence of anatomy and synchronization on the number of identified motor units, JOURNAL OF NEURAL ENGINEERING, Vol: 19, ISSN: 1741-2560

Journal article

Yeung D, Guerra IM, Barner-Rasmussen I, Siponen E, Farina D, Vujaklija Iet al., 2022, Co-Adaptive Control of Bionic Limbs via Unsupervised Adaptation of Muscle Synergies., IEEE Trans Biomed Eng, Vol: 69, Pages: 2581-2592

OBJECTIVE: In this work, we present a myoelectric interface that extracts natural motor synergies from multi-muscle signals and adapts in real-time with new user inputs. With this unsupervised adaptive myocontrol (UAM) system, optimal synergies for control are continuously co-adapted with changes in user motor control, or as a function of perturbed conditions via online non-negative matrix factorization guided by physiologically informed sparseness constraints in lieu of explicit data labelling. METHODS: UAM was tested in a set of virtual target reaching tasks completed by able-bodied and amputee subjects. Tests were conducted under normative and electrode perturbed conditions to gauge control robustness with comparisons to non-adaptive and supervised adaptive myocontrol schemes. Furthermore, UAM was used to interface an amputee with a multi-functional powered hand prosthesis during standardized Clothespin Relocation Tests, also conducted in normative and perturbed conditions. RESULTS: In virtual tests, UAM effectively mitigated performance degradation caused by electrode displacement, affording greater resilience over an existing supervised adaptive system for amputee subjects. Induced electrode shifts also had negligible effect on the real world control performance of UAM with consistent completion times (23.91 ±1.33 s) achieved across Clothespin Relocation Tests in the normative and electrode perturbed conditions. CONCLUSION: UAM affords comparable robustness improvements to existing supervised adaptive myocontrol interfaces whilst providing additional practical advantages for clinical deployment. SIGNIFICANCE: The proposed system uniquely incorporates neuromuscular control principles with unsupervised online learning methods and presents a working example of a freely co-adaptive bionic interface.

Journal article

Nowak M, Vujaklija I, Sturma A, Castellini C, Farina Det al., 2022, Simultaneous and proportional real-time myocontrol of up to three degrees of freedom of the wrist and hand, IEEE Transactions on Biomedical Engineering, ISSN: 0018-9294

Achieving robust, intuitive, simultaneous and proportional control over multiple degrees of freedom (DOFs) is an outstanding challenge in the development of myoelectric prosthetic systems. Since the priority inmyoelectric prosthesis solutions is robustness and stability, their number of functions is usually limited. Objective: Here, we introduce a system for intuitive concurrent hand and wrist control, based on a robust feature-extraction protocol and machine-learning. Methods: Using the meanabsolute value of high-density EMG, we train a ridge-regressor (RR) on only the sustained portions of the single-DOF contractions and leverage the regressor’s inherent ability to provide simultaneous multi-DOF estimates. In this way, we robustly capture the amplitude information of the inputs while harnessing the power of the RR to extrapolate otherwise noisy and often overfitted estimations of dynamic portions of movements. Results: The real-time evaluation of the system on 13 able-bodied participants and an amputee shows that almost all single-DOF tasks could be reached (96% success rate), while at the same time users were able to complete most of the two-DOF (62%) and even some of the very challenging three-DOF tasks (37%). To further investigate the translational potential of the approach, we reduced the original 192-channel setup to a 16-channel configuration and the observed performance did not deteriorate. Notably, the amputee performed similarly well to the other participants, according to all considered metrics. Conclusion: This is the first real-time operated myocontrol system that consistently provides intuitive simultaneous and proportional control over 3-DOFs of wrist and hand, relying on only surface EMG signals from the orearm. Significance: Focusing on reduced complexity, a real-time test and the inclusion of an amputee in the study demonstrate the translational potential of the control system for future applications in prosthetic control.

Journal article

Shirzadi M, Marateb HR, McGill KC, Muceli S, Mananas MA, Farina Det al., 2022, An Accurate and Real-time Method for Resolving Superimposed Action Potentials in MultiUnit Recordings., IEEE Trans Biomed Eng, Vol: PP

OBJECTIVE: Spike sorting of muscular and neural recordings requires separating action potentials that overlap in time (superimposed action potentials (APs)). We propose a new algorithm for resolving superimposed action potentials, and we test it on intramuscular EMG (iEMG) and intracortical recordings. METHODS: Discrete-time shifts of the involved APs are first selected based on a heuristic extension of the peel-off algorithm. Then, the time shifts that provide the minimal residual Euclidean norm are identified (Discrete Brute force Correlation (DBC)). The optimal continuous-time shifts are then estimated (High-Resolution BC (HRBC)). In Fusion HRBC (FHRBC), two other cost functions are used. A parallel implementation of the DBC and HRBC algorithms was developed. The performance of the algorithms was assessed on 11,000 simulated iEMG and 14,000 neural recording superpositions, including two to eight APs, and eight experimental iEMG signals containing four to eleven active motor units. The performance of the proposed algorithms was compared with that of the Branch-and-Bound (BB) algorithm using the Rank-Product (RP) method in terms of accuracy and efficiency. RESULTS: The average accuracy of the DBC, HRBC and FHRBC methods on the entire simulated datasets was 92.16±17.70, 93.65±16.89, and 94.90±15.15 (%). The DBC algorithm outperformed the other algorithms based on the RP method. The average accuracy and running time of the DBC algorithm on 10.5 ms superimposed spikes of the experimental signals were 92.1±21.7 (%) and 2.3±15.3 (ms). CONCLUSION AND SIGNIFICANCE: The proposed algorithm is promising for real-time neural decoding, a central problem in neural and muscular decoding and interfacing.

Journal article

Caillet A, Phillips ATM, Farina D, Modenese Let al., 2022, Mathematical relationships between spinal motoneuron properties, eLife, ISSN: 2050-084X

Our understanding of the behaviour of spinal alpha-motoneurons (MNs) in mammals partly relies on our knowledge of the relationships between MN membrane properties, such as MN size, resistance, rheobase, capacitance, time constant, axonal conduction velocity and afterhyperpolarization period. We reprocessed the data from 40 experimental studies in adult cat, rat and mouse MN preparations, to empirically derive a set of quantitative mathematical relationships between these MN electrophysiological and anatomical properties. This validated mathematical framework, which supports past findings that the MN membrane properties are all related to each other and clarifies the nature of their associations, is besides consistent with the Henneman’s size principle and Rall’s cable theory. The derived mathematical relationships provide a convenient tool for neuroscientists and experimenters to complete experimental datasets, to explore relationships between pairs of MN properties never concurrently observed in previous experiments, or to investigate inter-mammalian-species variations in MN membrane properties. Using this mathematical framework, modelers can build profiles of inter-consistent MN-specific properties to scale pools of MN models, with consequences on the accuracy and the interpretability of the simulations.

Journal article

Ibanez Pereda J, Zicher B, Brown KE, Rocchi L, Casolo A, Del Vecchio A, Spampinato DA, Vollette C-A, Rothwell JC, Baker SN, Farina Det al., 2022, Standard intensities of transcranial alternating current stimulation over the motor cortex do not entrain corticospinal inputs to motor neurons, The Journal of Physiology, ISSN: 0022-3751

Transcranial alternating current stimulation (TACS) is commonly used to synchronise a cortical area and its outputs to the stimulus waveform, but evidence for this based on brain recordings in humans is challenging. The corticospinal tract transmits beta oscillations (~21Hz) from motor cortex to tonically contracted limb muscles linearly. Therefore, muscle activity may be used to measure the level of beta entrainment in the corticospinal tract due to TACS over motor cortex. Here, we assessed if TACS is able to modulate the neural inputs to muscles, which would provide indirect evidence for TACS-driven neural entrainment. In the first part of this study, we ran simulations of motor neuron (MN) pools receiving inputs from corticospinal neurons with different levels of beta entrainment. Results suggest that MNs are highly sensitive to changes in corticospinal beta activity. Then, we ran experiments on healthy human subjects (N=10) in which TACS (at 1mA) was delivered over the motor cortex at 21Hz (beta stimulation), or at 7Hz or 40Hz (control conditions) while the abductor digiti minimi or the tibialis anterior muscle were tonically contracted. Muscle activity was measured using high-density electromyography, which allowed us to decompose the activity of pools of motor units innervating the muscles. By analysing motor unit pool activity, we observed that none of the TACS conditions could consistently alter the spectral contents of the common neural inputs received by the muscles. These results suggest that 1mA-TACS over motor cortex given at beta frequencies does not entrain corticospinal activity.

Journal article

Hug F, Avrillon S, Sarcher A, Del Vecchio A, Farina Det al., 2022, Correlation networks of spinal motor neurons that innervate lower limb muscles during a multi-joint isometric task, JOURNAL OF PHYSIOLOGY-LONDON, ISSN: 0022-3751

Journal article

Hug F, Avrillon S, Sarcher A, Del Vecchio A, Farina Det al., 2022, Correlation networks of spinal motor neurons that innervate lower limb muscles during a multi-joint isometric task, The Journal of Physiology, ISSN: 0022-3751

Movements are reportedly controlled through the combination of synergies that generate specific motor outputs by imposing an activation pattern on a group of muscles. To date, the smallest unit of analysis of these synergies has been the muscle through the measurement of its activation. However, the muscle is not the lowest neural level of movement control. In this human study (n = 10), we used a purely data-driven method grounded on graph theory to extract networks of motor neurons based on their correlated activity during an isometric multi-joint task. Specifically, high-density surface electromyography recordings from six lower limb muscles were decomposed into motor neurons spiking activity. We analyzed these activities by identifying their common low-frequency components, from which networks of correlated activity to the motor neurons were derived and interpreted as networks of common synaptic inputs. The vast majority of the identified motor neurons shared common inputs with other motor neuron(s). In addition, groups of motor neurons were partly decoupled from their innervated muscle, such that motor neurons innervating the same muscle did not necessarily receive common inputs. Conversely, some motor neurons from different muscles – including distant muscles – received common inputs. Our study supports the theory that movements are produced through the control of small numbers of groups of motor neurons via common inputs and that there is a partial mismatch between these groups of motor neurons and muscle anatomy. We provide a new neural framework for a deeper understanding of the structure of common inputs to motor neurons.Abstract figure legend Ten participants performed an isometric multi-joint task, which consisted in producing force on an instrumented pedal. Adhesive grids of 64 electrodes were placed over six lower limb muscles (gastrocnemius medialis [GM] and lateralis [GL], vastus lateralis [VL] and medialis [VM], biceps femoris [BF], semit

Journal article

Yao L, Jiang N, Mrachacz-Kersting N, Zhu X, Farina D, Wang Yet al., 2022, Reducing the calibration time in somatosensory BCI by using tactile ERD, IEEE Transactions on Neural Systems and Rehabilitation Engineering, Vol: 30, ISSN: 1534-4320

Objective: We propose a tactile-induced-oscillation approach to reduce the calibration time in somatosensory brain-computer interfaces (BCI). Methods: Based on the similarity between tactile induced event-related desynchronization (ERD) and imagined sensation induced ERD activation, we extensively evaluated BCI performance when using a conventional and a novel calibration strategy. In the conventional calibration, the tactile imagined data was used, while in the sensory calibration model sensory stimulation data was used. Subjects were required to sense the tactile stimulus when real tactile was applied to the left or right wrist and were required to perform imagined sensation tasks in the somatosensory BCI paradigm. Results: The sensory calibration led to a significantly better performance than the conventional calibration when tested on the same imagined sensation dataset (F(1,19)=10.89, P=0.0038), with an average 5.1% improvement in accuracy. Moreover, the sensory calibration was 39.3% faster in reaching a performance level of above 70% accuracy. Conclusion: The proposed approach of using tactile ERD from the sensory cortex provides an effective way of reducing the calibration time in a somatosensory BCI system. Significance: The tactile stimulation would be specifically useful before BCI usage, avoiding excessive fatigue when the mental task is difficult to perform. The tactile ERD approach may find BCI applications for patients or users with preserved afferent pathways.

Journal article

Bracklein M, Barsakcioglu DY, Ibanez J, Eden J, Burdet E, Mehring C, Farina Det al., 2022, The control and training of single motor units in isometric tasks are constrained by a common input signal, ELIFE, Vol: 11, ISSN: 2050-084X

Journal article

Gstoettner C, Festin C, Prahm C, Bergmeister KD, Salminger S, Sturma A, Hofer C, Russold MF, Howard CL, McDonnall D, Farina D, Aszmann OCet al., 2022, Feasibility of a Wireless Implantable Multi-electrode System for High-bandwidth Prosthetic Interfacing: Animal and Cadaver Study., Clin Orthop Relat Res, Vol: 480, Pages: 1191-1204

BACKGROUND: Currently used prosthetic solutions in upper extremity amputation have limited functionality, owing to low information transfer rates of neuromuscular interfacing. Although surgical innovations have expanded the functional potential of the residual limb, available interfaces are inefficacious in translating this potential into improved prosthetic control. There is currently no implantable solution for functional interfacing in extremity amputation which offers long-term stability, high information transfer rates, and is applicable for all levels of limb loss. In this study, we presented a novel neuromuscular implant, the the Myoelectric Implantable Recording Array (MIRA). To our knowledge, it is the first fully implantable system for prosthetic interfacing with a large channel count, comprising 32 intramuscular electrodes. QUESTIONS/PURPOSES: The purpose of this study was to evaluate the MIRA in terms of biocompatibility, functionality, and feasibility of implantation to lay the foundations for clinical application. This was achieved through small- and large-animal studies as well as test surgeries in a human cadaver. METHODS: We evaluated the biocompatibility of the system's intramuscular electromyography (EMG) leads in a rabbit model. Ten leads as well as 10 pieces of a biologically inert control material were implanted into the paravertebral muscles of four animals. After a 3-month implantation, tissue samples were taken and histopathological assessment performed. The probes were scored according to a protocol for the assessment of the foreign body response, with primary endpoints being inflammation score, tissue response score, and capsule thickness in µm. In a second study, chronic functionality of the full system was evaluated in large animals. The MIRA was implanted into the shoulder region of six dogs and three sheep, with intramuscular leads distributed across agonist and antagonist muscles of shoulder flexion. During the observation perio

Journal article

Gallina A, Disselhorst-Klug C, Farina D, Merletti R, Besomi M, Holobar A, Enoka RM, Hug F, Falla D, Søgaard K, McGill K, Clancy EA, Carson RG, van Dieën JH, Gandevia S, Lowery M, Besier T, Kiernan MC, Rothwell JC, Tucker K, Hodges PWet al., 2022, Consensus for experimental design in electromyography (CEDE) project: High-density surface electromyography matrix., J Electromyogr Kinesiol, Vol: 64

High-density surface electromyography (HDsEMG) can be used to measure the spatial distribution of electrical muscle activity over the skin. As this distribution is associated with the generation and propagation of muscle fiber action potentials, HDsEMG is processed to extract information on regional muscle activation, muscle fiber characteristics and behaviour of individual motor units. This matrix, developed by the Consensus for Experimental Design in Electromyography (CEDE) project, summarizes recommendations on the use of HDsEMG in experimental studies. For each application, recommendations are included regarding electrode montage, electrode type and configuration, electrode location and orientation, data analysis, and interpretation. Cautions and reporting standards are also included. The steps of the Delphi process to reach consensus are contained in an appendix. This matrix is intended to help researchers when collecting, reporting, and interpreting HDsEMG data. It is hoped that this document will be used to generate new empirical evidence to improve how HDsEMG is used in research and in clinical applications.

Journal article

Jiang X, Liu X, Fan J, Ye X, Dai C, Clancy EA, Farina D, Chen Wet al., 2022, Optimization of HD-sEMG-Based Cross-Day Hand Gesture Classification by Optimal Feature Extraction and Data Augmentation, IEEE TRANSACTIONS ON HUMAN-MACHINE SYSTEMS, ISSN: 2168-2291

Journal article

Niazi IK, Navid MS, Rashid U, Amjad I, Olsen S, Haavik H, Alder G, Kumari N, Signal N, Taylor D, Farina D, Jochumsen Met al., 2022, Associative cued asynchronous BCI induces cortical plasticity in stroke patients., Ann Clin Transl Neurol, Vol: 9, Pages: 722-733

OBJECTIVE: We propose a novel cue-based asynchronous brain-computer interface(BCI) for neuromodulation via the pairing of endogenous motor cortical activity with the activation of somatosensory pathways. METHODS: The proposed BCI detects the intention to move from single-trial EEG signals in real time, but, contrary to classic asynchronous-BCI systems, the detection occurs only during time intervals when the patient is cued to move. This cue-based asynchronous-BCI was compared with two traditional BCI modes (asynchronous-BCI and offline synchronous-BCI) and a control intervention in chronic stroke patients. The patients performed ankle dorsiflexion movements of the paretic limb in each intervention while their brain signals were recorded. BCI interventions decoded the movement attempt and activated afferent pathways via electrical stimulation. Corticomotor excitability was assessed using motor-evoked potentials in the tibialis-anterior muscle induced by transcranial magnetic stimulation before, immediately after, and 30 min after the intervention. RESULTS: The proposed cue-based asynchronous-BCI had significantly fewer false positives/min and false positives/true positives (%) as compared to the previously developed asynchronous-BCI. Linear-mixed-models showed that motor-evoked potential amplitudes increased following all BCI modes immediately after the intervention compared to the control condition (p <0.05). The proposed cue-based asynchronous-BCI resulted in the largest relative increase in peak-to-peak motor-evoked potential amplitudes(141% ± 33%) among all interventions and sustained it for 30 min(111% ± 33%). INTERPRETATION: These findings prove the high performance of a newly proposed cue-based asynchronous-BCI intervention. In this paradigm, individuals receive precise instructions (cue) to promote engagement, while the timing of brain activity is accurately detected to establish a precise ass

Journal article

Bracklein M, Barsakcioglu DY, Del Vecchio A, Ibanez J, Farina Det al., 2022, Reading and modulating cortical beta bursts from motor unit spiking activity, JOURNAL OF NEUROSCIENCE, Vol: 42, ISSN: 0270-6474

Journal article

Thompson CK, Johnson MD, Negro F, Farina D, Heckman CJet al., 2022, Motor Unit Discharge Patterns in Response to Focal Tendon Vibration of the Lower Limb in Cats and Humans, Frontiers in Integrative Neuroscience, Vol: 16, ISSN: 1662-5145

High-frequency vibration of the tendon provides potent activation of Ia afferents time-locked to the stimulation frequency and provides excitatory ionotropic activation of homonymous motor pools. In cats, the evoked motor unit discharge is constrained to discharge at integer multiples of the vibration frequency, resulting in a probability of discharge that is highly punctuated. Here we quantify the robustness of this punctuated response in the cat and evaluate whether it is present in the human. Soleus electromyography (EMG) was collected from eight cats using 64 channel electrodes during three modes of motoneuron activation. First, tendon vibration parameters were modified. Second, secondary reflex inputs are applied concurrently with tendon vibration. Third, the state of the spinal cord was altered through pharmacological or surgical manipulations. Analogous surface high-density EMG was collected from the lower leg of six humans during both vibration evoked and matched volitional contractions. Array EMG signals from both the cat and human were decomposed into corresponding motor unit action potential spike trains, and the punctuation in discharge was quantified. In the cat, regardless of vibration parameters, secondary synaptic drive, and state of spinal circuitry, focal tendon vibration evoked punctuated motor unit discharge. However, in the human lower limb, the vibration-evoked contractions do not produce punctuated motor unit discharge.

Journal article

Koutsoftidis S, Barsakcioglu DY, Petkos K, Farina D, Drakakis Eet al., 2022, Myolink: a 128-channel, 18 nV/ √{Hz} , Embedded Recording System, Optimized for High-density Surface Electromyogram Acquisition., IEEE Trans Biomed Eng, Vol: PP

OBJECTIVE: We present Myolink, a portable, modular, low-noise electrophysiology amplifier optimized for high-density surface electromyogram (HD sEMG) acquisition. METHODS: Myolink consists of 4 modules. Each 108 cm module can concurrently acquire 32 unipolar electrode potentials at sampling rates of up to 8 kHz with 24-bit resolution. Modules may be stacked and operated synchronously, supporting the concurrent acquisition of up to 128 channels. A custom high-performance analog front-end provides an input-referred-noise < 0.4 VRMS for a bandwidth of 23-524 Hz (tuneable by design choices), which is lower than current commercial systems. Digitized signals are processed by a custom on-board FPGA-based controller and subsequently transmitted to a PC via a medical-grade isolated USB2.0 interface. RESULTS: The system has been tested by recording experimental HD sEMG signals, which have been subsequently decomposed into motor unit action potentials. Compared to commercially available systems, the proposed recording system led to higher-quality surface EMG acquisition, as well as higher decomposition accuracy across a wide range of forces, with the greater gain for forces 20% of the maximum voluntary contraction. SIGNIFICANCE: A portable, ultra-low-noise, HD sEMG amplifier design has been implemented and characterized. The system provides IRN performance beyond the capabilities of current state-of-the-art instrumentation and this improvement has a significant effect on HD sEMG decomposition.

Journal article

Mendez Guerra I, Barsakcioglu DY, Vujaklija I, Wetmore DZ, Farina Det al., 2022, Far-field electric potentials provide access to the output from the spinal cord from wrist-mounted sensors, Journal of Neural Engineering, Vol: 19, ISSN: 1741-2552

OBJECTIVE: Neural interfaces need to become more unobtrusive and socially acceptable to appeal to general consumers outside rehabilitation settings. APPROACH: We developed a non-invasive neural interface that provides access to spinal motor neuron activities from the wrist, which is the preferred location for a wearable. The interface decodes far-field potentials present at the tendon endings of the forearm muscles using blind source separation. First, we evaluated the reliability of the interface to detect motor neuron firings based on far-field potentials, and thereafter we used the decoded motor neuron activity for the prediction of finger contractions in offline and real-time conditions. MAIN RESULTS: The results showed that motor neuron activity decoded from the far-field potentials at the wrist accurately predicted individual and combined finger commands and therefore allowed for highly accurate real-time task classification. SIGNIFICANCE: These findings demonstrate the feasibility of a non-invasive, neural interface at the wrist for precise real-time control based on the output of the spinal cord.

Journal article

Eden J, Bräcklein M, Ibáñez J, Barsakcioglu DY, Di Pino G, Farina D, Burdet E, Mehring Cet al., 2022, Principles of human movement augmentation and the challenges in making it a reality, Nature Communications, Vol: 13, ISSN: 2041-1723

Augmenting the body with artificial limbs controlled concurrently to one's natural limbs has long appeared in science fiction, but recent technological and neuroscientific advances have begun to make this possible. By allowing individuals to achieve otherwise impossible actions, movement augmentation could revolutionize medical and industrial applications and profoundly change the way humans interact with the environment. Here, we construct a movement augmentation taxonomy through what is augmented and how it is achieved. With this framework, we analyze augmentation that extends the number of degrees-of-freedom, discuss critical features of effective augmentation such as physiological control signals, sensory feedback and learning as well as application scenarios, and propose a vision for the field.

Journal article

Puttaraksa G, Muceli S, Barsakcioglu DY, Holobar A, Clarke AK, Charles SK, Pons JL, Farina Det al., 2022, Online tracking of the phase difference between neural drives to antagonist muscle pairs in essential tremor patients, IEEE Transactions on Neural Systems and Rehabilitation Engineering, Vol: 30, Pages: 709-718, ISSN: 1534-4320

Transcutaneous electrical stimulation has been applied in tremor suppression applications. Out-of-phase stimulation strategies applied above or below motor threshold result in a significant attenuation of pathological tremor. For stimulation to be properly timed, the varying phase relationship between agonist-antagonist muscle activity during tremor needs to be accurately estimated in real-time. Here we propose an online tremor phase and frequency tracking technique for the customized control of electrical stimulation, based on a phase-locked loop (PLL) system applied to the estimated neural drive to muscles. Surface electromyography signals were recorded from the wrist extensor and flexor muscle groups of 13 essential tremor patients during postural tremor. The EMG signals were pre-processed and decomposed online and offline via the convolution kernel compensation algorithm to discriminate motor unit spike trains. The summation of motor unit spike trains detected for each muscle was bandpass filtered between 3 to 10 Hz to isolate the tremor related components of the neural drive to muscles. The estimated tremorogenic neural drive was used as input to a PLL that tracked the phase differences between the two muscle groups. The online estimated phase difference was compared with the phase calculated offline using a Hilbert Transform as a ground truth. The results showed a rate of agreement of 0.88 ± 0.22 between offline and online EMG decomposition. The PLL tracked the phase difference of tremor signals in real-time with an average correlation of 0.86 ± 0.16 with the ground truth (average error of 6.40° ± 3.49°). Finally, the online decomposition and phase estimation components were integrated with an electrical stimulator and applied in closed-loop on one patient, to representatively demonstrate the working principle of the full tremor suppression system. The results of this study support the feasibility of real-time estimation of the pha

Journal article

Ghaderi P, Nosouhi M, Jordanic M, Marateb HR, Mañanas MA, Farina Det al., 2022, Kernel Density Estimation of Electromyographic Signals and Ensemble Learning for Highly Accurate Classification of a Large Set of Hand/Wrist Motions, Frontiers in Neuroscience, Vol: 16, ISSN: 1662-4548

The performance of myoelectric control highly depends on the features extracted from surface electromyographic (sEMG) signals. We propose three new sEMG features based on the kernel density estimation. The trimmed mean of density (TMD), the entropy of density, and the trimmed mean absolute value of derivative density were computed for each sEMG channel. These features were tested for the classification of single tasks as well as of two tasks concurrently performed. For single tasks, correlation-based feature selection was used, and the features were then classified using linear discriminant analysis (LDA), non-linear support vector machines, and multi-layer perceptron. The eXtreme gradient boosting (XGBoost) classifier was used for the classification of two movements simultaneously performed. The second and third versions of the Ninapro dataset (conventional control) and Ameri’s movement dataset (simultaneous control) were used to test the proposed features. For the Ninapro dataset, the overall accuracy of LDA using the TMD feature was 98.99 ± 1.36% and 92.25 ± 9.48% for able-bodied and amputee subjects, respectively. Using ensemble learning of the three classifiers, the average macro and micro-F-score, macro recall, and precision on the validation sets were 98.23 ± 2.02, 98.32 ± 1.93, 98.32 ± 1.93, and 98.88 ± 1.31%, respectively, for the intact subjects. The movement misclassification percentage was 1.75 ± 1.73 and 3.44 ± 2.23 for the intact subjects and amputees. The proposed features were significantly correlated with the movement classes [Generalized Linear Model (GLM); P-value < 0.05]. An accurate online implementation of the proposed algorithm was also presented. For the simultaneous control, the overall accuracy was 99.71 ± 0.08 and 97.85 ± 0.10 for the XGBoost and LDA classifiers, respectively. The proposed features are thus promising for conventional and simultaneous myoelectric

Journal article

Sturma A, Stamm T, Hruby LA, Bischof B, Salminger S, Gstoettner C, Prahm C, Pittermann A, Wakolbinger R, Hofer C, Farina D, Aszmann OCet al., 2022, Rehabilitation of high upper limb amputees after Targeted Muscle Reinnervation, Journal of Hand Therapy, Vol: 35, Pages: 58-66, ISSN: 0894-1130

STUDY DESIGN: This is a Delphi study based on a scoping literature review. INTRODUCTION: Targeted muscle reinnervation (TMR) enables patients with high upper limb amputations to intuitively control a prosthetic arm with up to six independent control signals. Although there is a broad agreement regarding the importance of structured motor learning and prosthetic training after such nerve transfers, to date, no evidence-based protocol for rehabilitation after TMR exists. PURPOSE OF THE STUDY: We aimed at developing a structured rehabilitation protocol after TMR surgery after major upper limb amputation. The purpose of the protocol is to guide clinicians through the full rehabilitation process, from presurgical patient education to functional prosthetic training. METHODS: European clinicians and researchers working in upper limb prosthetic rehabilitation were invited to contribute to a web-based Delphi study. Within the first round, clinical experts were presented a summary of recent literature and were asked to describe the rehabilitation steps based on their own experience and scientific evidence. The second round was used to refine these steps, while the importance of each step was rated within the third round. RESULTS: Experts agreed on a rehabilitation protocol that consists of 16 steps and starts before surgery. It is based on two overarching principles, namely the necessity of multiprofessional teamwork and a careful selection and education of patients within the rehabilitation team. Among the different steps in therapy, experts rated the training with electromyographic biofeedback as the most important one. DISCUSSION: Within this study, a first rehabilitation protocol for TMR patients based on a broad experts' consensus and relevant literature could be developed. The detailed steps for rehabilitation start well before surgery and prosthetic fitting, and include relatively novel interventions as motor imagery and biofeedback. Future studies need to further inve

Journal article

Ma S, Chen C, Zhao J, Han D, Sheng X, Farina D, Zhu Xet al., 2022, Analytical Modelling of Surface EMG Signals Generated by Curvilinear Fibers With Approximate Conductivity Tensor, IEEE TRANSACTIONS ON BIOMEDICAL ENGINEERING, Vol: 69, Pages: 1052-1062, ISSN: 0018-9294

Journal article

Ernst J, Weiss T, Wanke N, Frahm J, Felmerer G, Farina D, Schilling AF, Wilke MAet al., 2022, Case Report: Plasticity in Central Sensory Finger Representation and Touch Perception After Microsurgical Reconstruction of Infraclavicular Brachial Plexus Injury, FRONTIERS IN NEUROSCIENCE, Vol: 16

Journal article

de Oliveira DS, Casolo A, Balshaw TG, Maeo S, Lanza MB, Martin NRW, Maffulli N, Kinfe TM, Eskofier B, Folland JP, Farina D, Del Vecchio Aet al., 2022, Neural decoding from surface high-density EMG signals: influence of anatomy and synchronization on the number of identified motor units

<jats:title>Abstract</jats:title><jats:sec><jats:title>Objective</jats:title><jats:p>High-density surface electromyography (HD-sEMG) allows the reliable identification of individual motor unit (MU) action potentials. Despite the accuracy in decomposition, there is a large variability in the number of identified MUs across individuals and exerted forces. Here we present a systematic investigation of the anatomical and neural factors that determine this variability.</jats:p></jats:sec><jats:sec><jats:title>Approach</jats:title><jats:p>We investigated factors of influence on HD-sEMG decomposition, such as synchronization of MU discharges, distribution of MU territories, muscle-electrode distance (MED - subcutaneous fat thickness), maximum anatomical cross-sectional area (ACSA<jats:sub>max</jats:sub>), and fiber CSA. For this purpose, we recorded HD-sEMG signals, ultrasound, magnetic resonance imaging, and muscle biopsy of the biceps brachii muscle from two groups of participants – untrained-controls (UT=14) and strength-trained (&gt;3 years of training, ST=16) – while they performed isometric ramp contractions with elbow flexors (at 15, 35, 50 and 70% maximum voluntary torque - MVT). We assessed the correlation between the number of accurately detected MUs by HD-sEMG decomposition and each measured parameter, for each target force level. Multiple regression analysis was then applied.</jats:p></jats:sec><jats:sec><jats:title>Main results</jats:title><jats:p>ST subjects showed lower MED (UT: 4.8 ± 1.4 vs. ST: 3.7 ± 0.8 mm) associated to a greater number of identified motor units (UT: 21.3 ± 10.2 vs. ST: 29.2 ± 11.8 MUs/subject). Both groups showed a negative correlation between MED and the number of identified MUs at low forces (r= −0.6, p=0.002 at 15% MVT). Moreover, the number of identified MUs was pos

Journal article

Yu T, Akhmadeev K, Le Carpentier E, Aoustin Y, Farina Det al., 2022, Highly Accurate Real-Time Decomposition of Single Channel Intramuscular EMG, IEEE TRANSACTIONS ON BIOMEDICAL ENGINEERING, Vol: 69, Pages: 746-757, ISSN: 0018-9294

Journal article

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