31 research outputs found
A neural tracking and motor control approach to improve rehabilitation of upper limb movements
<p>Abstract</p> <p>Background</p> <p>Restoration of upper limb movements in subjects recovering from stroke is an essential keystone in rehabilitative practices. Rehabilitation of arm movements, in fact, is usually a far more difficult one as compared to that of lower extremities. For these reasons, researchers are developing new methods and technologies so that the rehabilitative process could be more accurate, rapid and easily accepted by the patient. This paper introduces the proof of concept for a new non-invasive FES-assisted rehabilitation system for the upper limb, called smartFES (sFES), where the electrical stimulation is controlled by a biologically inspired neural inverse dynamics model, fed by the kinematic information associated with the execution of a planar goal-oriented movement. More specifically, this work details two steps of the proposed system: an <it>ad hoc </it>markerless motion analysis algorithm for the estimation of kinematics, and a neural controller that drives a synthetic arm. The vision of the entire system is to acquire kinematics from the analysis of video sequences during planar arm movements and to use it together with a neural inverse dynamics model able to provide the patient with the electrical stimulation patterns needed to perform the movement with the assisted limb.</p> <p>Methods</p> <p>The markerless motion tracking system aims at localizing and monitoring the arm movement by tracking its silhouette. It uses a specifically designed motion estimation method, that we named Neural Snakes, which predicts the arm contour deformation as a first step for a silhouette extraction algorithm. The starting and ending points of the arm movement feed an Artificial Neural Controller, enclosing the muscular Hill's model, which solves the inverse dynamics to obtain the FES patterns needed to move a simulated arm from the starting point to the desired point. Both position error with respect to the requested arm trajectory and comparison between curvature factors have been calculated in order to determine the accuracy of the system.</p> <p>Results</p> <p>The proposed method has been tested on real data acquired during the execution of planar goal-oriented arm movements. Main results concern the capability of the system to accurately recreate the movement task by providing a synthetic arm model with the stimulation patterns estimated by the inverse dynamics model. In the simulation of movements with a length of ± 20 cm, the model has shown an unbiased angular error, and a mean (absolute) position error of about 1.5 cm, thus confirming the ability of the system to reliably drive the model to the desired targets. Moreover, the curvature factors of the factual human movements and of the reconstructed ones are similar, thus encouraging future developments of the system in terms of reproducibility of the desired movements.</p> <p>Conclusion</p> <p>A novel FES-assisted rehabilitation system for the upper limb is presented and two parts of it have been designed and tested. The system includes a markerless motion estimation algorithm, and a biologically inspired neural controller that drives a biomechanical arm model and provides the stimulation patterns that, in a future development, could be used to drive a smart Functional Electrical Stimulation system (sFES). The system is envisioned to help in the rehabilitation of post stroke hemiparetic patients, by assisting the movement of the paretic upper limb, once trained with a set of movements performed by the therapist or in virtual reality. Future work will include the application and testing of the stimulation patterns in real conditions.</p
THE EXTENDED MRP MODEL FOR THE EVALUATION AND FINANCING OF SUPERANNUATION SCHEMES IN A SUPPLY CHAIN
The Orthotic Effect of Functional Electrical Stimulation on the Improvement of Walking in Stroke Patients with a Dropped Foot: A Systematic Review
The silicification value: a novel diatom-based indicator to assess climate change in freshwater habitats
Design and Development of Gliclazide Mucoadhesive Microcapsules: In Vitro and In Vivo Evaluation
Formulation Study of Intravesical Oxybutynin Instillation Solution with Enhanced Retention in Bladder
Treadmill training augmented with real-time visualisation feedback and function electrical stimulation for gait rehabilitation after stroke: a feasibility study
Mucoadhesive Bilayered Patches for Administration of Sumatriptan Succinate
The purpose of this study was to develop and optimize formulations of mucoadhesive bilayered buccal patches of sumatriptan succinate using chitosan as the base matrix. The patches were prepared by the solvent casting method. Gelatin and polyvinyl pyrrolidone (PVP) K30 were incorporated into the patches, to improve the film properties of the patches. The patches were found to be smooth in appearance, uniform in thickness, weight, and drug content; showed good mucoadhesive strength; and good folding endurance. A 32 full factorial design was employed to study the effect of independent variables viz. levels of chitosan and PVP K30, which significantly influenced characteristics like swelling index, in-vitro mucoadhesive strength, in vitro drug release, and in-vitro residence time. Different penetration enhancers were tried to improve the permeation of sumatriptan succinate through buccal mucosa. Formulation containing 3% dimethyl sulfoxide showed good permeation of sumatriptan succinate through mucosa. Histopathological studies revealed no buccal mucosal damage. It can be concluded that buccal route can be one of the alternatives available for administration of sumatriptan succinate