A Modular, Smart, and Wearable System for High Density sEMG Detection

Cerone, Giacinto Luigi; Botter, Alberto; Gazzoni, Marco

doi:10.1109/tbme.2019.2904398

Cited by 87 publications

(77 citation statements)

References 61 publications

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“…Currently, the implementation of HD-sEMG in dynamic control of wearable exoskeletons is limited by a number of factors, such as the number of cables between amplifiers and electrodes, as well as large amplifiers. This lack of portability restricts measurements in dynamic conditions (motion) and induces movement restrictions, user discomfort, and signal artifacts (23), therefore limiting control of wearables. However, recent developments show promising steps toward more portable amplifiers that reject movement artifacts and powerline interference, while at the same time do not obstruct movements and ensure tight placement of the electrodes (23,55).…”

Section: Discussionmentioning

confidence: 99%

“…This lack of portability restricts measurements in dynamic conditions (motion) and induces movement restrictions, user discomfort, and signal artifacts (23), therefore limiting control of wearables. However, recent developments show promising steps toward more portable amplifiers that reject movement artifacts and powerline interference, while at the same time do not obstruct movements and ensure tight placement of the electrodes (23,55). To this point, the main limitation of portable amplifiers is the relatively limited number of electrodes provided [32 (23) and 16 (55)]; however, they open new avenues for HD-sEMG control of exoskeletons.…”

Section: Discussionmentioning

confidence: 99%

“…Moreover, this can be used to explore myocontrol in pathological populations when combined with currently used machine learning classification techniques (22). Currently, HD-sEMG is performed with a large number of cables and is biased by heavy and sizable amplifiers which limit its use in dynamic situations, such as the control of wearable exoskeletons (23).…”

Section: Introductionmentioning

confidence: 99%

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Characterization of Forearm Muscle Activation in Duchenne Muscular Dystrophy via High-Density Electromyography: A Case Study on the Implications for Myoelectric Control

et al. 2020

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Duchenne muscular dystrophy (DMD) is a genetic disorder that results in progressive muscular degeneration. Although medical advances increased their life expectancy, DMD individuals are still highly dependent on caregivers. Hand/wrist function is central for providing independence, and robotic exoskeletons are good candidates for effectively compensating for deteriorating functionality. Robotic hand exoskeletons require the accurate decoding of motor intention typically via surface electromyography (sEMG). Traditional low-density sEMG was used in the past to explore the muscular activations of individuals with DMD; however, it cannot provide high spatial resolution. This study characterized, for the first time, the forearm high-density (HD) electromyograms of three individuals with DMD while performing seven hand/wrist-related tasks and compared them to eight healthy individuals (all data available online). We looked into the spatial distribution of HD-sEMG patterns by using principal component analysis (PCA) and also assessed the repeatability and the amplitude distributions of muscle activity. Additionally, we used a machine learning approach to assess DMD individuals' potentials for myocontrol. Our analysis showed that although participants with DMD were able to repeat similar HD-sEMG patterns across gestures (similarly to healthy participants), a fewer number of electrodes was activated during their gestures compared to the healthy participants. Additionally, participants with DMD activated their muscles close to maximal contraction level (0.63 ± 0.23), whereas healthy participants had lower normalized activations (0.26 ± 0.2). Lastly, participants with DMD showed on average fewer PCs (3), explaining 90% of the complete gesture space than the healthy (5). However, the ability of the DMD participants to produce repeatable HD-sEMG patterns was unexpectedly comparable to that of healthy participants, and the same holds true for their offline myocontrol performance, disproving our hypothesis and suggesting a clear potential for the myocontrol of wearable exoskeletons. Our findings present evidence for the first

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Section: Discussionmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Characterization of Forearm Muscle Activation in Duchenne Muscular Dystrophy via High-Density Electromyography: A Case Study on the Implications for Myoelectric Control

et al. 2020

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“…EMG signals were detected in monopolar configuration using a wireless and modular high-density EMG amplifier 19 . This device is composed of two modules, each detecting, conditioning and transmitting 32 EMG signals (gain: 192 V/V; sampling frequency: 2048 Hz; nbits of the AD converter: 16).…”

Section: Mechanical Muscle Tapmentioning

confidence: 99%

The peripheral origin of tap-induced muscle contraction revealed by multi-electrode surface electromyography in human vastus medialis

Botter

Vieira

Geri

et al. 2020

Sci Rep

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It is well established that muscle percussion may lead to the excitation of muscle fibres. It is still debated, however, whether the excitation arises directly at the percussion site or reflexively, at the end plates. Here we sampled surface electromyograms (EMGs) from multiple locations along human vastus medialis fibres to address this issue. In five healthy subjects, contractions were elicited by percussing the distal fibre endings at different intensities (5-50 N), and the patellar tendon. EMGs were detected with two 32-electrode arrays, positioned longitudinally and transversally to the percussed fibres, to detect the origin and the propagation of action potentials and their spatial distribution across vastus medialis. During muscle percussion, compound action potentials were first observed at the electrode closest to the tapping site with latency smaller than 5 ms, and spatial extension confined to the percussed strip. Conversely, during tendon tap (and voluntary contractions), action potentials were first detected by electrodes closest to end plates and at a greater latency (mean ± s.d., 28.2 ± 1.7 ms, p < 0.001). No evidence of reflex responses to muscle tap was observed. Multi-electrode surface EMGs allowed for the first time to unequivocally and quantitatively describe the non-reflex nature of the response evoked by a muscle tap.

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“…Over the years, Surface Electromyography (SEMG) as myoelectric signal, has been widely applied for assistive and rehabilitation technology, human robot collaboration, teleportation,etc [1]- [3]. It is generated by the muscle cells which are electrically or neurologically activated, and detected by using surface electrodes [4].…”

Section: Introductionmentioning

confidence: 99%

SEMG based Intention Identification of Complex Hand Motion using Nonlinear Time Series Analysis

Xue

2019

2019 9th International Conference on Information Science and Technology (ICIST)

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This paper proposes a hand motion recognition system for classifying different complex hand motions based on Surface Electromyography (SEMG). By defining ten common hand motions, the SEMG signals are recorded based on a SEMG capture device. A series of signal processing methods, including signal denoising, and feature extraction are analyzed to acquire the SEMG features. A trained Random Forest (RF) algorithm is used for the classification of ten different hand motions. The experimental results show that the proposed hand motion recognition system has a higher classification accuracy for identifying different hand motions.

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A Modular, Smart, and Wearable System for High Density sEMG Detection

Cited by 87 publications

References 61 publications

Characterization of Forearm Muscle Activation in Duchenne Muscular Dystrophy via High-Density Electromyography: A Case Study on the Implications for Myoelectric Control

Characterization of Forearm Muscle Activation in Duchenne Muscular Dystrophy via High-Density Electromyography: A Case Study on the Implications for Myoelectric Control

The peripheral origin of tap-induced muscle contraction revealed by multi-electrode surface electromyography in human vastus medialis

SEMG based Intention Identification of Complex Hand Motion using Nonlinear Time Series Analysis

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