A Stimulus Artifact Removal Technique for SEMG Signal Processing During Functional Electrical Stimulation

2015 ◽  
Vol 62 (8) ◽  
pp. 1959-1968 ◽  
Author(s):  
Shuang Qiu ◽  
Jing Feng ◽  
Rui Xu ◽  
Jiapeng Xu ◽  
Kun Wang ◽  
...  
Keyword(s):  
Signal Processing ◽  
Electrical Stimulation ◽  
Functional Electrical Stimulation ◽  
Artifact Removal ◽  
Semg Signal ◽  
Stimulus Artifact ◽  
Removal Technique

scholarly journals Mixed-signal template-based reduction scheme for stimulus artifact removal in electrical stimulation

2012 ◽  
Vol 51 (4) ◽  
pp. 449-458 ◽  
Author(s):  
Thi Kim Thoa Nguyen ◽  
Silke Musa ◽  
Wolfgang Eberle ◽  
Carmen Bartic ◽  
Georges Gielen
Keyword(s):  
Electrical Stimulation ◽  
Reduction Scheme ◽  
Artifact Removal ◽  
Mixed Signal ◽  
Stimulus Artifact

scholarly journals Embedded Bio-Mimetic System for Functional Electrical Stimulation Controlled by Event-Driven sEMG

Sensors ◽  
2020 ◽  
Vol 20 (5) ◽  
pp. 1535 ◽  
Author(s):  
Fabio Rossi ◽  
Paolo Motto Ros ◽  
Ricardo Maximiliano Rosales ◽  
Danilo Demarchi
Keyword(s):  
Electrical Stimulation ◽  
Embedded System ◽  
Real Time ◽  
Functional Electrical Stimulation ◽  
Optimal Solution ◽  
Elbow Flexion ◽  
Knee Extension ◽  
Operating Conditions ◽  
Semg Signal ◽  
Event Driven

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.

scholarly journals Intention recognition for FES in a grasp-and-release task using volitional EMG and inertial sensors

2017 ◽  
Vol 3 (2) ◽  
pp. 161-165 ◽  
Author(s):  
Christina Salchow ◽  
Andreas Dorn ◽  
Markus Valtin ◽  
Thomas Schauer
Keyword(s):  
Signal Processing ◽  
Electrical Stimulation ◽  
Functional Electrical Stimulation ◽  
Inertial Sensors ◽  
Inertial Sensor ◽  
Hand Function ◽  
Residual Activity ◽  
Control Approach ◽  
Combined Control ◽  
Motion Capturing

AbstractFunctional Electrical Stimulation (FES) facilitates the motor recovery of the hand function after stroke. The integration of biofeedback and other strategies to actively in-volve a patient in the therapy is important for the rehabili-tation progress. We introduce a combined control approach for a FES-driven neuroprosthesis using volitional electromyo-graphy (vEMG) and motion capturing via a novel inertial sensor network for patients that still possess a residual activity in the paralyzed muscles. A real-time vEMG measurement and signal processing in between stimulation pulses has been realized during active FES. Experiments showed that our system allows for quick adaption to individual users.

A Review on Functional Electrical Stimulation for a Dropped Foot

2017 ◽  
Vol 27 (2-4) ◽  
pp. 267-277
Author(s):  
Robert P. Wilder ◽  
Tyler C. Wind ◽  
Elizabeth V. Jones ◽  
Brenda E. Crider ◽  
Richard Edlich
Keyword(s):  
Electrical Stimulation ◽  
Functional Electrical Stimulation
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