Concurrent surface electromyography and force myography classification during times of prosthetic socket shift and user fatigue

Sanford, Joe; Patterson, Rita M.; Popa, Dan O.

doi:10.1177/2055668317708731

Cited by 9 publications

(4 citation statements)

References 37 publications

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“…It is interesting to note that integration of EMG and FMG improves classification of human intent and control of powered prosthetic devices, as compared to EMG alone 48 . Such integration would require an increased computational demand, because both EMG and FMG signals would need to be processed.…”

Section: Discussionmentioning

confidence: 99%

A smart approach to EMG envelope extraction and powerful denoising for human–machine interfaces

Esposito

Centracchio

Bifulco

et al. 2023

Sci Rep

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Electromyography (EMG) is widely used in human–machine interfaces (HMIs) to measure muscle contraction by computing the EMG envelope. However, EMG is largely affected by powerline interference and motion artifacts. Boards that directly provide EMG envelope, without denoising the raw signal, are often unreliable and hinder HMIs performance. Sophisticated filtering provides high performance but is not viable when power and computational resources must be optimized. This study investigates the application of feed-forward comb (FFC) filters to remove both powerline interferences and motion artifacts from raw EMG. FFC filter and EMG envelope extractor can be implemented without computing any multiplication. This approach is particularly suitable for very low-cost, low-power platforms. The performance of the FFC filter was first demonstrated offline by corrupting clean EMG signals with powerline noise and motion artifacts. The correlation coefficients of the filtered signals envelopes and the true envelopes were greater than 0.98 and 0.94 for EMG corrupted by powerline noise and motion artifacts, respectively. Further tests on real, highly noisy EMG signals confirmed these achievements. Finally, the real-time operation of the proposed approach was successfully tested by implementation on a simple Arduino Uno board.

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Section: Discussionmentioning

confidence: 99%

A smart approach to EMG envelope extraction and powerful denoising for human–machine interfaces

Esposito

Centracchio

Bifulco

et al. 2023

Sci Rep

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“…Force myography (FMG) or residual kinetics is a unique way of detecting functional or neurological motor activity by measuring volumetric changes in muscles [ 68 , 91 ]. It is a non-invasive technique to decode the position or movement of the muscle and convert it into a measurable signal Fig.…”

Section: Introductionmentioning

confidence: 99%

A survey on the state of the art of force myography technique (FMG): analysis and assessment

Sherif,

Bassuoni,

Mehrez

2024

Med Biol Eng Comput

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Precise feedback assures precise control commands especially for assistive or rehabilitation devices. Biofeedback systems integrated with assistive or rehabilitative robotic exoskeletons tend to increase its performance and effectiveness. Therefore, there has been plenty of research in the field of biofeedback covering different aspects such as signal acquisition, conditioning, feature extraction and integration with the control system. Among several types of biofeedback systems, Force myography (FMG) technique is a promising one in terms of affordability, high classification accuracies, ease to use, and low computational cost. Compared to traditional biofeedback systems such as electromyography (EMG) which offers some invasive techniques, FMG offers a completely non-invasive solution with much less effort for preprocessing with high accuracies. This work covers the whole aspects of FMG technique in terms of signal acquisition, feature extraction, signal processing, developing the machine learning model, evaluating tools for the performance of the model. Stating the difference between real-time and offline assessment, also highlighting the main uncovered points for further study, and thus enhancing the development of this technique. Graphical abstract

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“…On the other hand, the weight of the prosthesis can be problematic if it exceeds the weight of a human limb; in the case of hands, a prosthesis should not exceeded 374 g for an adult left hand and 400 g for the right hand [8]. In addition, it is important to note that excess prosthesis weight can generate discomfort and fatigue in the user [9,16,17]. The weight issue is closely related to the materials used to build the devices; therefore, there is currently an increasing trend towards additive (3D printing) manufacturing.…”

Section: Introductionmentioning

confidence: 99%

Development and Implementation of an Anthropomorphic Underactuated Prosthesis with Adaptive Grip

et al. 2021

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This paper describes the design of a prosthetic hand for wrist amputations. The mechanism considers the use of three actuators: one each for the movement of the little finger, annular finger, and middle finger. The second actuator controls the index finger, and the third controls the thumb. The prototype is considered relevant as it is able to move the distal phalanx in all fingers; the little, annular, and middle fingers are able to adapt to the shape of the object being gripped (adaptive grip). The sequence of movements achieved with the thumb emulate the opposition/reposition and flexion/extension movements, commanded by a single actuator. The proposed design was built by additive manufacturing and effortlessly achieves a large number of grips. Additionally, the prosthesis could perform specific movements, such as holding a needle, although this grip demands higher precision in the control of the fingers. Due to the manufacturing method, the prosthesis weighs only 200 g, increasing to 450 g when the actuators are included, therefore weighing less than an average adult’s hand.

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Concurrent surface electromyography and force myography classification during times of prosthetic socket shift and user fatigue

Cited by 9 publications

References 37 publications

A smart approach to EMG envelope extraction and powerful denoising for human–machine interfaces

A smart approach to EMG envelope extraction and powerful denoising for human–machine interfaces

A survey on the state of the art of force myography technique (FMG): analysis and assessment

Development and Implementation of an Anthropomorphic Underactuated Prosthesis with Adaptive Grip

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