A hybrid method for real-time stimulation artefact removal during functional electrical stimulation with time-variant parameters

Author(s):  
Zheng-Yang Bi ◽  
Yu-Xuan Zhou ◽  
Chen-Xi Xie ◽  
Hai-Peng Wang ◽  
Hong-Xing Wang ◽  
...  
Author(s):  
Corinna Schultheiss ◽  
Thomas Schauer ◽  
Holger Nahrstaedt ◽  
Rainer O. Seidl ◽  
Jehoschua Bieler

In order to support swallowing, the efficacy of functional electrical stimulation for different stimulation settings of the submental musculature has been investigated. The stimulation was administrated at rest and synchronously to voluntary initiated swallows. The onset of a swallow was detected in real-time by a combined electromyography/ bioimpedance measurement at the neck in order to trigger the stimulation. The amplitude and speed of larynx elevation caused by the FES has been assessed by the observed change in bioimpedance whereas a reduction of bioimpedance corresponds to an increase in larynx elevation. Study results from 40 healthy subjects revealed that 73% of the subjects achieved a larger and faster larynx elevation during swallowing with triggered FES and therefor a better protection of their airways. However, we also observed a decrease in larynx elevation compared to normal swallowing in 11 out of the 40 subjects what might not benefit from such a treatment. The largest improvement of larynx elevation and speed during swallowing could be achieved with three stimulation channels formed by four electrodes in the submental region.


Sensors ◽  
2020 ◽  
Vol 20 (5) ◽  
pp. 1535 ◽  
Author(s):  
Fabio Rossi ◽  
Paolo Motto Ros ◽  
Ricardo Maximiliano Rosales ◽  
Danilo Demarchi

The analysis of the surface ElectroMyoGraphic (sEMG) signal for controlling the Functional Electrical Stimulation (FES) therapy is being widely accepted as an active rehabilitation technique for the restoration of neuro-muscular disorders. Portability and real-time functionalities are major concerns, and, among others, two correlated challenges are the development of an embedded system and the implementation of lightweight signal processing approaches. In this respect, the event-driven nature of the Average Threshold Crossing (ATC) technique, considering its high correlation with the muscle force and the sparsity of its representation, could be an optimal solution. In this paper we present an embedded ATC-FES control system equipped with a multi-platform software featuring an easy-to-use Graphical User Interface (GUI). The system has been first characterized and validated by analyzing CPU and memory usage in different operating conditions, as well as measuring the system latency (fulfilling the real-time requirements with a 140 ms FES definition process). We also confirmed system effectiveness, testing it on 11 healthy subjects: The similarity between the voluntary movement and the stimulate one has been evaluated, computing the cross-correlation coefficient between the angular signals acquired during the limbs motion. We obtained high correlation values of 0.87 ± 0.07 and 0.93 ± 0.02 for the elbow flexion and knee extension exercises, respectively, proving good stimulation application in real therapy-scenarios.


2014 ◽  
Vol 2014 ◽  
pp. 1-12 ◽  
Author(s):  
Matija Štrbac ◽  
Slobodan Kočović ◽  
Marko Marković ◽  
Dejan B. Popović

We present a computer vision algorithm that incorporates a heuristic model which mimics a biological control system for the estimation of control signals used in functional electrical stimulation (FES) assisted grasping. The developed processing software acquires the data from Microsoft Kinect camera and implements real-time hand tracking and object analysis. This information can be used to identify temporal synchrony and spatial synergies modalities for FES control. Therefore, the algorithm acts as artificial perception which mimics human visual perception by identifying the position and shape of the object with respect to the position of the hand in real time during the planning phase of the grasp. This artificial perception used within the heuristically developed model allows selection of the appropriate grasp and prehension. The experiments demonstrate that correct grasp modality was selected in more than 90% of tested scenarios/objects. The system is portable, and the components are low in cost and robust; hence, it can be used for the FES in clinical or even home environment. The main application of the system is envisioned for functional electrical therapy, that is, intensive exercise assisted with FES.


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