Simultaneous and Proportional Control of Wrist and Hand Movements Based on a Neural-Driven Musculoskeletal Model.

Human-machine interfaces (HMIs) based on electromyography (EMG) signals have been developed for simultaneous and proportional control (SPC) of multiple degrees of freedom (DoFs). The EMG-driven musculoskeletal model (MM) has been used in HMIs to predict human movements in prosthetic and robotic control. However, the neural information extracted from surface EMG signals may be distorted due to their limitations.

Eliciting tactile sensations in the hand through non-invasive proximal nerve stimulation: a feasibility study.

Recently, non-invasive proximal nerve stimulation has been widely investigated to restore tactile sensations. It has been demonstrated that tactile sensations in the hand could be elicited by nerve stimulation on the upper arm. However, it is still unknown whether tactile sensations could be elicited by stimulation at a proximal location close to the neck.

Clean visual field reconstruction in robot-assisted laparoscopic surgery based on dynamic prediction.

Robot-assisted minimally invasive surgery has been broadly employed in complicated operations. However, the multiple surgical instruments may occupy a large amount of visual space in complex operations performed in narrow spaces, which affects the surgeon's judgment on the shape and position of the lesion as well as the course of its adjacent vessels/lacunae. In this paper, a surgical scene reconstruction method is proposed, which involves the tracking and removal of surgical instruments and the dynamic prediction of the obscured region.

Bio-robotics research for non-invasive myoelectric neural interfaces for upper-limb prosthetic control: a 10-year perspective review.

A decade ago, a group of researchers from academia and industry identified a dichotomy between the industrial and academic state-of-the-art in upper-limb prosthesis control, a widely used bio-robotics application. They proposed that four key technical challenges, if addressed, could bridge this gap and translate academic research into clinically and commercially viable products. These challenges are unintuitive control schemes, lack of sensory feedback, poor robustness and single sensor modality.

Effect of Subcutaneous Muscle Displacement of Flexor Carpi Radialis on Surface Electromyography.

Changes in joint angle can change the position and orientation of muscle fibers relative to the surface EMG electrode. Our previous study has shown that EMG patterns can identify hand/wrist movements with a greater degree of classification accuracy (CA) when muscle contractions involve a change in the joint angle. The results of this study suggest that changes in the position of the muscle relative to the recording electrode can influence the properties of the recorded EMG signals, however, this was not directly quantified.

A High-Performance Transmitarray Antenna with Thin Metasurface for 5G Communication Based on PSO (Particle Swarm Optimization).

A 5G metasurface (MS) transmitarray (TA) feed by compact-antenna array with the performance of high gain and side-lobe level (SLL) reduction is presented. The proposed MS has two identical metallic layers etched on both sides of the dielectric substrate and four fixed vias connecting two metallic layers that works at 28 GHz to increase the transmission phase shift range. The proposed planar TA consisting of unit cells with different dimensional information can simulate the function as an optical lens according to the Fermat's principle, so the quasi-spherical wave emitted by the compact Potter horn antenna at the virtual focal point will transform to the quasi-plane wave by the phase-adjustments.

Evoking haptic sensations in the foot through high-density transcutaneous electrical nerve stimulations.

Objective: Evoking haptic sensation on upper limb amputees via peripheral nerve stimulation has been investigated intensively in the past decade, but related studies involving lower limb amputees are limited. This study aimed to evaluate the feasibility of using non-invasive transcutaneous electrical nerve stimulation to evoke haptic sensation along the phantom limb of the amputated foot of transtibial amputees.

Approach: A high-density electrode grid (4 × 4) was placed over the skin surface above the distal branching of the sciatic, tibial, and common peroneal nerves.

Comparing EMG-Based Human-Machine Interfaces for Estimating Continuous, Coordinated Movements.

Electromyography (EMG)-based interfaces are trending toward continuous, simultaneous control with multiple degrees of freedom. Emerging methods range from data-driven approaches to biomechanical model-based methods. However, there has been no direct comparison between these two types of continuous EMG-based interfaces.

A Reliable Multi-User EMG Interface Based on A Generic-Musculoskeletal Model against Loading Weight Changes.

The reliability of myoelectric control is important to ensure the performance of prostheses during daily use. Recently, we proposed a multi-user neural-machine interface based on a generic musculoskeletal model to simultaneously and continuously estimate flexion/extension movements at the metacarpophalangeal (MCP) and wrist joints from surface electromyography (EMG) signals. Our previous results demonstrated that the multi-user EMG interface was reliable against upper limb posture changes.

Comparing Surface and Intramuscular Electromyography for Simultaneous and Proportional Control Based on a Musculoskeletal Model: A Pilot Study.

Simultaneous and proportional control (SPC) of neural-machine interfaces uses magnitudes of smoothed electromyograms (EMG) as control inputs. Though surface EMG (sEMG) electrodes are common for clinical neural-machine interfaces, intramuscular EMG (iEMG) electrodes may be indicated in some circumstances (e.g.

Myoelectric Control Based on A Generic Musculoskeletal Model: Towards A Multi-User Neural-Machine Interface.

This study aimed to develop a novel electromyography (EMG)-based neural-machine interface (NMI) that is user-generic for continuously predicting coordinated motion between metacarpophalangeal (MCP) and wrist flexion/extension. The NMI requires a minimum calibration procedure that only involves capturing maximal voluntary muscle contraction for the monitored muscles for individual users. At the center of the NMI is a user-generic musculoskeletal model based on the experimental data collected from 6 able-bodied (AB) subjects and 9 different upper limb postures.

Myoelectric Control Based on a Generic Musculoskeletal Model: Toward a Multi-User Neural-Machine Interface.

This paper aimed to develop a novel electromyography (EMG)-based neural-machine interface (NMI) that is user-generic for continuously predicting coordinated motion betweenmuscle contractionmetacarpophalangeal (MCP) and wrist flexion/extension. The NMI requires a minimum calibration procedure that only involves capturing maximal voluntary muscle contraction for themonitoredmuscles for individual users. At the center of the NMI is a user-generic musculoskeletal model based on the experimental data collected from six able-bodied (AB) subjects and nine different upper limb postures.

Transcranial direct current stimulation versus user training on improving online myoelectric control for amputees.

Objective: Transcranial direct current stimulation (tDCS) and user training (UT) are two types of methods to improve myoelectric control performance for amputees. In this study, we compared the independent effect between tDCS and UT, and investigated the combined effect of tDCS and UT.

Approach: An online paradigm of simultaneous and proportional control (SPC) based on electromyography (EMG) was adopted.

Residuals of autoregressive model providing additional information for feature extraction of pattern recognition-based myoelectric control.

Myoelectric control based on pattern recognition has been studied for several decades. Autoregressive (AR) features are one of the mostly used feature extraction methods among myoelectric control studies. Almost all previous studies only used the AR coefficients without the residuals of AR model for classification.

Improving robustness against electrode shift of high density EMG for myoelectric control through common spatial patterns.

Background: Most prosthetic myoelectric control studies have concentrated on low density (less than 16 electrodes, LD) electromyography (EMG) signals, due to its better clinical applicability and low computation complexity compared with high density (more than 16 electrodes, HD) EMG signals. Since HD EMG electrodes have been developed more conveniently to wear with respect to the previous versions recently, HD EMG signals become an alternative for myoelectric prostheses. The electrode shift, which may occur during repositioning or donning/doffing of the prosthetic socket, is one of the main reasons for degradation in classification accuracy (CA).

A structurally decoupled mechanism for measuring wrist torque in three degrees of freedom.

The wrist joint is a critical part of the human body for movement. Measuring the torque of the wrist with three degrees of freedom (DOFs) is important in some fields, including rehabilitation, biomechanics, ergonomics, and human-machine interfacing. However, the particular structure of the wrist joint makes it difficult to measure the torque in all three directions simultaneously.

Improving Myoelectric Control for Amputees through Transcranial Direct Current Stimulation.

Most prosthetic myoelectric control studies have shown good performance for unimpaired subjects. However, performance is generally unacceptable for amputees. The primary problem is the poor quality of electromyography (EMG) signals of amputees compared with healthy individuals.

Can transcranial direct current stimulation enhance performance of myoelectric control for multifunctional prosthesis?

Pattern recognition based myoelectric control has been studied by many researchers. However, the classification accuracy was pretty low for amputees towards multifunctional prosthesis control in practice. In this work, a novel method of transcranial direct current stimulation (tDCS) which can modulate brain activity was used to enhance performance for myoelectric prosthesis control.

A linear model for simultaneously and proportionally estimating wrist kinematics from emg during mirrored bilateral movements.

This paper presents a linear model for simultaneous and proportional estimation of the two degree-of-freedoms (DOFs) wrist angle positions with surface electromyography (EMG). A 5th order state-space model was used to estimate wrist kinematics from 4-channel surface EMG signals of the contralateral forearm during mirrored bilateral movements without motion constraints. The EMG signal from each of the three limbed normal subjects was collected along with each angle position in two DOFs from both of the arms, with motion parameters tested including the radial/ulnar deviation and flexion/extension of the wrist.