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Predicting wrist kinematics from motor unit discharge timings for the control of active prostheses

Published on Dec 1, 2019in Journal of Neuroengineering and Rehabilitation3.582
· DOI :10.1186/s12984-019-0516-x
Tamás Kapelner4
Estimated H-index: 4
(GAU: University of Göttingen),
Ivan Vujaklija11
Estimated H-index: 11
(Aalto University)
+ 4 AuthorsDario Farina76
Estimated H-index: 76
(Imperial College London)
Abstract
Background Current myoelectric control algorithms for active prostheses map time- and frequency-domain features of the interference EMG signal into prosthesis commands. With this approach, only a fraction of the available information content of the EMG is used and the resulting control fails to satisfy the majority of users. In this study, we predict joint angles of the three degrees of freedom of the wrist from motor unit discharge timings identified by decomposition of high-density surface EMG.
  • References (39)
  • Citations (1)
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References39
Newest
#1Ivan Vujaklija (Aalto University)H-Index: 11
Robotic manipulators can be controlled in an autonomous way with great precision and dexterity. At the same time they can be equipped with sensors capable of conveying highly precise information on the surroundings, many times superior to that of a human sensory system. However, our limited capacity of interfacing these robots with the human body makes current prosthetic systems to be perceived by the users as simple tools rather than limbs. After decades of developments, osseointegration, selec...
1 CitationsSource
#1Ivan Vujaklija (Imperial College London)H-Index: 11
#2Vahid Shalchyan (IUST: Iran University of Science and Technology)H-Index: 4
Last. Dario Farina (Imperial College London)H-Index: 76
view all 6 authors...
In this paper, we propose a nonlinear minimally supervised method based on autoencoding (AEN) of EMG for myocontrol. The proposed method was tested against the state-of-the-art (SOA) control scheme using a Fitts’ law approach. Seven 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...
11 CitationsSource
#1Tamás Kapelner (GAU: University of Göttingen)H-Index: 4
#2Francesco Negro (University of Brescia)H-Index: 46
Last. Dario Farina (Imperial College London)H-Index: 76
view all 4 authors...
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 ac...
15 CitationsSource
#1Eduardo Martinez-Valdes (University of Potsdam)H-Index: 6
#2Francesco Negro (GAU: University of Göttingen)H-Index: 46
Last. Dario Farina (GAU: University of Göttingen)H-Index: 76
view all 6 authors...
Key points Classic motor unit (MU) recording and analysis methods do not allow the same MUs to be tracked across different experimental sessions, and therefore, there is limited experimental evidence on the adjustments in MU properties following training or during the progression of neuromuscular disorders. We propose a new processing method to track the same MUs across experimental sessions (separated by weeks) by using high-density surface electromyography. The application of the proposed meth...
23 CitationsSource
#1Ivan Vujaklija (Imperial College London)H-Index: 11
#2Aidan D. Roche (Medical University of Vienna)H-Index: 10
Last. Oskar C. Aszmann (Medical University of Vienna)H-Index: 25
view all 7 authors...
Missing 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, we suggest that one relevant factor determining the relatively small clinical impact of myocontrol algori...
22 CitationsSource
#1Dario Farina (Imperial College London)H-Index: 76
#2Ivan Vujaklija (Imperial College London)H-Index: 11
Last. Oskar C. Aszmann (Medical University of Vienna)H-Index: 25
view all 10 authors...
The 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-neur...
54 CitationsSource
#1Francesco Negro (GAU: University of Göttingen)H-Index: 46
#2Utku Ş. Yavuz (GAU: University of Göttingen)H-Index: 4
Last. Dario Farina (GAU: University of Göttingen)H-Index: 76
view all 3 authors...
Motor neurons in a pool receive both common and independent synaptic inputs, although the proportion and role of their common synaptic input is debated. Classic correlation techniques between motor unit spike trains do not measure the absolute proportion of common input and have limitations as a result of the non-linearity of motor neurons. We propose a method that for the first time allows an accurate quantification of the absolute proportion of low frequency common synaptic input ( 60%) of com...
26 CitationsSource
#1Ivan Vujaklija (GAU: University of Göttingen)H-Index: 11
#2Dario FarinaH-Index: 76
Last. Oskar C. Aszmann (Medical University of Vienna)H-Index: 25
view all 3 authors...
23 CitationsSource
#1Francesco Negro (GAU: University of Göttingen)H-Index: 46
#2Silvia Muceli (GAU: University of Göttingen)H-Index: 17
Last. Dario Farina (GAU: University of Göttingen)H-Index: 76
view all 5 authors...
Objective. The study of motor unit behavior has been classically performed by selective recording systems of muscle electrical activity (EMG signals) and decomposition algorithms able to discriminate between individual motor unit action potentials from multi-unit signals. In this study, we provide a general framework for the decomposition of multi-channel intramuscular and surface EMG signals and we extensively validate this approach with experimental recordings. Approach. First, we describe the...
94 CitationsSource
#1Dario Farina (GAU: University of Göttingen)H-Index: 76
#2Ales Holobar (University of Maribor)H-Index: 23
Motor units are the smallest functional units of our movements. The study of their activation provides a window into the mechanisms of neural control of movement in humans. The classic methods for motor unit investigations date to several decades ago. They are based on invasive recordings with selective needle or wire electrodes. Conversely, the noninvasive (surface) EMG has been commonly processed as an interference signal, with the extraction of its global characteristics, e.g., amplitude. The...
39 CitationsSource
Cited By1
Newest
#1Tamás Kapelner (GAU: University of Göttingen)H-Index: 4
#2Massimo Sartori (UT: University of Twente)H-Index: 17
Last. Dario Farina (Imperial College London)H-Index: 76
view all 4 authors...
We propose a myoelectric control method based on neural data regression and musculoskeletal modeling. This paradigm uses the timings of motor neuron discharges decoded by high-density surface electromyogram (HD-EMG) decomposition to estimate muscle excitations. The muscle excitations are then mapped into the kinematics of the wrist joint using forward dynamics. The offline tracking performance of the proposed method was superior to that of state-of-the-art myoelectric regression methods based on...
Source
#1Yang Yu (SJTU: Shanghai Jiao Tong University)H-Index: 1
#2Chen Chen (SJTU: Shanghai Jiao Tong University)H-Index: 1
Last. Xiangyang Zhu (SJTU: Shanghai Jiao Tong University)H-Index: 23
view all 4 authors...
Abstract Human machine interface (HMI) based on surface electromyography (sEMG) promises to provide an intuitive and noninvasive way to interact with peripheral equipments, such as prostheses, exoskeletons, and robots. Most recently, advances in machine learning, especially in deep learning algorithms, present the capabilities in constructing complicated mapping functions. In this study, we construct a stacked autoencoder-based deep neural network (SAE-DNN) to continuously estimate multiple degr...
1 CitationsSource
Prosthetic devices for hand difference have advanced considerably in recent years, to the point where the mechanical dexterity of a state-of-the-art prosthetic hand approaches that of the natural hand. Control options for users, however, have not kept pace, meaning that the new devices are not used to their full potential. Promising developments in control technology reported in the literature have met with limited commercial and clinical success. We have previously described a biomechanical mod...
Source
#1Reed D. GurchiekH-Index: 2
#2Nick CheneyH-Index: 8
Last. Ryan S. McGinnisH-Index: 10
view all 3 authors...
Wearable sensors have the potential to enable comprehensive patient characterization and optimized clinical intervention. Critical to realizing this vision is accurate estimation of biomechanical time-series in daily-life, including joint, segment, and muscle kinetics and kinematics, from wearable sensor data. The use of physical models for estimation of these quantities often requires many wearable devices making practical implementation more difficult. However, regression techniques may provid...
Source
#1Dimitra Blana (Keele University)H-Index: 9
#2van, den, Bogert, Aj (CSU: Cleveland State University)
Last. Edward K. Chadwick (Keele University)H-Index: 23
view all 7 authors...
Prosthetic devices for hand difference have advanced considerably in recent years, to the point where the mechanical dexterity of a state-of-the-art prosthetic hand approaches that of the natural hand. Control options for users, however, have not kept pace, meaning that the new devices are not used to their full potential. Promising developments in control technology reported in the literature have met with limited commercial and clinical success. We have previously described a biomechanical mod...
Source