Neural control of finger movement via intracortical brain–machine interface

ZT Irwin, KE Schroeder, PP Vu, AJ Bullard… - Journal of neural …, 2017 - iopscience.iop.org
Objective. Intracortical brain–machine interfaces (BMIs) are a promising source of prosthesis
control signals for individuals with severe motor disabilities. Previous BMI studies have …

Feedback control of functional electrical stimulation for 2-D arm reaching movements

RS Razavian, B Ghannadi, N Mehrabi… - … on Neural Systems …, 2018 - ieeexplore.ieee.org
Functional electrical stimulation (FES) can be used as a neuroprosthesis in which muscles
are stimulated by electrical pulses to compensate for the loss of voluntary movement control …

Real-time control of hind limb functional electrical stimulation using feedback from dorsal root ganglia recordings

TM Bruns, JB Wagenaar, MJ Bauman… - Journal of neural …, 2013 - iopscience.iop.org
Objective. Functional electrical stimulation (FES) approaches often utilize an open-loop
controller to drive state transitions. The addition of sensory feedback may allow for closed …

Stochastic modelling of muscle recruitment during activity

S Martelli, D Calvetti, E Somersalo… - Interface …, 2015 - royalsocietypublishing.org
Muscle forces can be selected from a space of muscle recruitment strategies that produce
stable motion and variable muscle and joint forces. However, current optimization methods …

FES-induced co-activation of antagonist muscles for upper limb control and disturbance rejection

APL Bo, LO da Fonseca, ACC de Sousa - Medical engineering & physics, 2016 - Elsevier
Control systems for human movement based on Functional Electrical Stimulation (FES) have
shown to provide excellent performance in different experimental setups. Nevertheless …

Hybrid machine learning-neuromusculoskeletal modeling for control of lower limb prosthetics

A Cimolato, G Milandri, LS Mattos… - 2020 8th IEEE RAS …, 2020 - ieeexplore.ieee.org
Objective: Current limitations in Electromyography (EMG)-driven Neuromusculoskeletal
(NMS) modeling for control of wearable robotics are the requirement of both Motion Capture …

Semiparametric identification of human arm dynamics for flexible control of a functional electrical stimulation neuroprosthesis

EM Schearer, YW Liao, EJ Perreault… - … on Neural Systems …, 2016 - ieeexplore.ieee.org
We present a method to identify the dynamics of a human arm controlled by an implanted
functional electrical stimulation neuroprosthesis. The method uses Gaussian process …

Mechanical characterization and modeling of direct metal laser sintered stainless steel GP1

SF Siddiqui, AA Fasoro, C Cole… - Journal of …, 2019 - asmedigitalcollection.asme.org
The additive manufacturing (AM) process is unique in that it can facilitate anisotropy
because of the layer-by-layer deposition technique intrinsic to this process. In order to …

A coupled model for the prediction of surface variation in face milling large-scale workpiece with complex geometry

S Liu, S Jin, XP Zhang, K Chen… - Journal of …, 2019 - asmedigitalcollection.asme.org
Face milling commonly generates surface quality of variation, is especially severe for milling
of large-scale components with complex surface geometry such as cylinder block, engine …

A synergy-based motor control framework for the fast feedback control of musculoskeletal systems

R Sharif Razavian, B Ghannadi… - Journal of …, 2019 - asmedigitalcollection.asme.org
This paper presents a computational framework for the fast feedback control of
musculoskeletal systems using muscle synergies. The proposed motor control framework …