scholarly journals A High-Level Control Algorithm Based on sEMG Signalling for an Elbow Joint SMA Exoskeleton

Sensors ◽  
2018 ◽  
Vol 18 (8) ◽  
pp. 2522 ◽  
Author(s):  
Dorin Copaci ◽  
David Serrano ◽  
Luis Moreno ◽  
Dolores Blanco

A high-level control algorithm capable of generating position and torque references from surface electromyography signals (sEMG) was designed. It was applied to a shape memory alloy (SMA)-actuated exoskeleton used in active rehabilitation therapies for elbow joints. The sEMG signals are filtered and normalized according to data collected online during the first seconds of a therapy session. The control algorithm uses the sEMG signals to promote active participation of patients during the therapy session. In order to generate the reference position pattern with good precision, the sEMG normalized signal is compared with a pressure sensor signal to detect the intention of each movement. The algorithm was tested in simulations and with healthy people for control of an elbow exoskeleton in flexion–extension movements. The results indicate that sEMG signals from elbow muscles, in combination with pressure sensors that measure arm–exoskeleton interaction, can be used as inputs for the control algorithm, which adapts the reference for exoskeleton movements according to a patient’s intention.

Author(s):  
Dorin Copaci ◽  
David Serrano ◽  
Luis Moreno ◽  
Dolores Blanco

A high-level control algorithm capable of generating position and torque references from surface electromyography signals (sEMG) has been designed. It is applied to a shape memory alloy (SMA) actuated exoskeleton used in active rehabilitation therapies for elbow joints. The sEMG signals are filtered and normalized according data collected online during the first seconds of~therapy sessions. The control algorithm uses the sEMG signals to promote active participation of patients during the therapy session. In order to generate the position reference pattern with good precision, the sEMG normalized signal is compared with a pressure sensor signal to detect the intention of each movement. The algorithm has been tested in simulations and with healthy people for control of an elbow exoskeleton in flexion–extension movements. The results indicate that sEMG signals from elbow muscles in combination with pressure sensors that measure arm–exoskeleton interaction can be used as inputs for the control algorithm, which adapts the reference for exoskeleton movements according a patient's intention.


Author(s):  
Omer Orki ◽  
Offer Shai ◽  
Amir Ayali ◽  
Uri Ben-Hanan

This paper presents an ongoing project aiming at building a robot composed of Assur tensegrity structures, which mimics caterpillar locomotion. Caterpillars are soft-bodied animals capable of making complex movements with astonishing fault-tolerance. In our model, each caterpillar segment is represented by a 2D tensegrity triad consisting of two bars connected by two cables and a strut. The cables represent the major longitudinal muscles of the caterpillar, while the strut represents hydrostatic pressure. The control scheme in this model is divided into localized low-level controllers and a high-level control unit. The unique engineering properties of Assur tensegrity structures, which were mathematically proved last year, together with the suggested control algorithm provide the model with robotic softness. Moreover, the degree of softness can be continuously changed during simulation, making this model suitable for simulation of soft-bodied caterpillars as well as other types of soft animals.


Author(s):  
Hao Su ◽  
Venkat Krovi

In this paper, we present a decentralized dynamic control algorithm for a robot collective consisting of multiple nonholonomic wheeled mobile manipulators (NH-WMMs) capable of cooperatively transporting a common payload. In this algorithm, the high level controller deals with motion/force control of the payload, at the same time distributes the motion/force task into individual agents by grasp description matrix. In each individual agent, the low level controller decomposes the system dynamics into decoupled task space (end-effector motions/forces) and a dynamically-consistent null-space (internal motions/forces) component. The agent level control algorithm facilitates the prioritized operational task accomplishment with the end-effector impedance-mode controller and secondary null-space control. The scalability and modularity is guaranteed upon the decentralized control architecture. Numerical simulations are performed for a 2-NH-WMM system carrying a payload (with/without uncertainty) to validate this approach.


Energies ◽  
2018 ◽  
Vol 11 (10) ◽  
pp. 2500 ◽  
Author(s):  
Eduardo Hernández-Márquez ◽  
Carlos Avila-Rea ◽  
José García-Sánchez ◽  
Ramón Silva-Ortigoza ◽  
Gilberto Silva-Ortigoza ◽  
...  

This paper has two aims. The first is to develop a robust hierarchical tracking controller for the DC/DC Buck-Boost–inverter–DC motor system. This controller considers a high level control for the inverter–DC motor subsystems and a low level control for the DC/DC Buck-Boost converter subsystem. Such controls solve the tracking task associated with the angular velocity of the motor shaft and the output voltage of the converter, respectively, via the differential flatness approach. The second aim is to present a comparison of the robust hierarchical controller to a passive controller. This, with the purpose of showing that performance achieved with the hierarchical controller proposed in this paper, is better than the one achieved with the passive controller. Both controllers are experimentally implemented on a prototype of the DC/DC Buck-Boost–inverter–DC motor system by using Matlab-Simulink along with the DS1104 board from dSPACE. According to experimental results, the proposal in the present paper achieves a better performance than the passive controller.


2018 ◽  
Vol 15 (148) ◽  
pp. 20180550
Author(s):  
Vahhab Zarei ◽  
Rohit Y. Dhume ◽  
Arin M. Ellingson ◽  
Victor H. Barocas

Due to its high level of innervation, the lumbar facet capsular ligament (FCL) is suspected to play a role in low back pain (LBP). The nociceptors in the lumbar FCL may experience excessive deformation and generate pain signals. As such, understanding the mechanical behaviour of the FCL, as well as that of its underlying nerves, is critical if one hopes to understand its role in LBP. In this work, we constructed a multiscale structure-based finite-element (FE) model of a lumbar FCL on a spinal motion segment undergoing physiological motions of flexion, extension, ipsilateral and contralateral bending, and ipsilateral axial rotation. Our FE model was created for a generic FCL geometry by morphing a previously imaged FCL anatomy onto an existing generic motion segment model. The fibre organization of the FCL in our models was subject-specific based on previous analysis of six dissected specimens. The fibre structures from those specimens were mapped onto the FCL geometry on the motion segment. A motion segment model was used to determine vertebral kinematics under specified spinal loading conditions, providing boundary conditions for the FCL-only multiscale FE model. The solution of the FE model then provided detailed stress and strain fields within the tissue. Lastly, we used this computed strain field and our previous studies of deformation of nerves embedded in fibrous networks during simple deformations (e.g. uniaxial stretch, shear) to estimate the nerve deformation based on the local tissue strain and fibre alignment. Our results show that extension and ipsilateral bending result in largest strains of the lumbar FCL, while contralateral bending and flexion experience lowest strain values. Similar to strain trends, we calculated that the stretch of the microtubules of the nerves, as well as the forces exerted on the nerves' membrane are maximal for extension and ipsilateral bending, but the location within the FCL of peak microtubule stretch differed from that of peak membrane force.


Sensors ◽  
2020 ◽  
Vol 20 (4) ◽  
pp. 1196 ◽  
Author(s):  
Seulah Lee ◽  
Babar Jamil ◽  
Sunhong Kim ◽  
Youngjin Choi

Myoelectric prostheses assist users to live their daily lives. However, the majority of users are primarily confined to forearm amputees because the surface electromyography (sEMG) that understands the motion intents should be acquired from a residual limb for control of the myoelectric prosthesis. This study proposes a novel fabric vest socket that includes embroidered electrodes suitable for a high-level upper amputee, especially for shoulder disarticulation. The fabric vest socket consists of rigid support and a fabric vest with embroidered electrodes. Several experiments were conducted to verify the practicality of the developed vest socket with embroidered electrodes. The sEMG signals were measured using commercial Ag/AgCl electrodes for a comparison to verify the performance of the embroidered electrodes in terms of signal amplitudes, the skin-electrode impedance, and signal-to-noise ratio (SNR). These results showed that the embroidered electrodes were as effective as the commercial electrodes. Then, posture classification was carried out by able-bodied subjects for the usability of the developed vest socket. The average classification accuracy for each subject reached 97.92%, and for all the subjects it was 93.2%. In other words, the fabric vest socket with the embroidered electrodes could measure sEMG signals with high accuracy. Therefore, it is expected that it can be readily worn by high-level amputees to control their myoelectric prostheses, as well as it is cost effective for fabrication as compared with the traditional socket.


F1000Research ◽  
2013 ◽  
Vol 2 ◽  
pp. 20
Author(s):  
Christopher T Noto ◽  
Suleman Mazhar ◽  
James Gnadt ◽  
Jagmeet S Kanwal

A major problem facing behavioral neuroscientists is a lack of unified, vendor-distributed data acquisition systems that allow stimulus presentation and behavioral monitoring while recording neural activity. Numerous systems perform one of these tasks well independently, but to our knowledge, a useful package with a straightforward user interface does not exist. Here we describe the development of a flexible, script-based user interface that enables customization for real-time stimulus presentation, behavioral monitoring and data acquisition. The experimental design can also incorporate neural microstimulation paradigms. We used this interface to deliver multimodal, auditory and visual (images or video) stimuli to a nonhuman primate and acquire single-unit data. Our design is cost-effective and works well with commercially available hardware and software. Our design incorporates a script, providing high-level control of data acquisition via a sequencer running on a digital signal processor to enable behaviorally triggered control of the presentation of visual and auditory stimuli. Our experiments were conducted in combination with eye-tracking hardware. The script, however, is designed to be broadly useful to neuroscientists who may want to deliver stimuli of different modalities using any animal model.


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