Using EMG Amplitude and Frequency to Calculate a Multimuscle Fatigue Score and Evaluate Global Shoulder Fatigue

McDonald, Alison C.; Mulla, Daanish M.; Keir, Peter J.

doi:10.1177/0018720818794604

Cited by 34 publications

(18 citation statements)

References 22 publications

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“…Through the analysis, we preliminarily explain the phenomena of classifier degradation in this study. The analysis results show the significant effects of muscle fatigue on the mean values and variances of all features, which meets the phenomena presented by several studies [37,[44][45][46]. The difference of the statistical characteristics implies that the distributions of the features extracted from sEMG signals vary with the fatigue levels.…”

Section: Discussionsupporting

confidence: 82%

The Muscle Fatigue’s Effects on the sEMG-Based Gait Phase Classification: An Experimental Study and a Novel Training Strategy

Zhu

Wei

et al. 2021

Applied Sciences

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Surface Electromyography (sEMG) enables an intuitive control of wearable robots. The muscle fatigue-induced changes of sEMG signals might limit the long-term usage of the sEMG-based control algorithms. This paper presents the performance deterioration of sEMG-based gait phase classifiers, explains the deterioration by analyzing the time-varying changes of the extracted features, and proposes a training strategy that can improve the classifiers’ robustness against muscle fatigue. In particular, we first select some features that are commonly used in fatigue-related studies and use them to classify gait phases under muscle fatigue. Then, we analyze the time-varying characteristics of extracted features, with the aim of explaining the performance of the classifiers. Finally, we propose a training strategy that effectively improves the robustness against muscle fatigue, which contributes to an easy-to-use method. Ten subjects performing prolonged walking are recruited. Our study contributes to a novel perspective of designing gait phase classifiers under muscle fatigue.

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Section: Discussionsupporting

confidence: 82%

The Muscle Fatigue’s Effects on the sEMG-Based Gait Phase Classification: An Experimental Study and a Novel Training Strategy

Zhu

Wei

et al. 2021

Applied Sciences

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“…Each experimental condition was recorded separately for 10 min, and there was a 2 min break between consecutive trials. Previously, several related research articles have used sampling times of around 10 min for single experimental tasks, so for the experiments in this paper, the sampling time for single experimental tasks is sufficient [25][26][27]. Each participant can determine the gaze distance between the mobile phone and the eyes under different experimental conditions.…”

Section: Materials and Methods Participantsmentioning

confidence: 99%

Effect of airplane passenger seat armrest height on human neck comfort when using a smartphone

Tang¹,

Yu²,

Chu³

et al. 2021

Int J Occup Med Environ Health

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Objectives:The objective of this study was to explore the relationship between seat armrest height and human neck comfort when using a smartphone while sitting on a passenger seat during the flight. Material and Methods: The authors used a wireless angle-measuring instrument and subjective comfort scale to evaluate the changes of head flexion angle and neck comfort level of 24 young smartphone users in an aircraft simulated cabin. Results: The study results indicated that using a smartphone while sitting on a passenger seat during the flight would pose a larger discomfort to the neck, and the discomfort would be higher for gaming than reading tasks. Seat armrest height is related to the comfort level of the neck when using a smartphone, increasing the height of the armrest can effectively alleviate discomfort in this state. Conclusions: Considering the prevalence of passengers using smartphones in aircraft, a seat armrest that can be properly adjusted in height, which can effectively reduce the risk of passenger head flexion angle and neck discomfort. Int J Occup Med Environ Health. 2022;35(2)

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“…The study of muscle activity and coordination patterns is a useful tool for the identification of motor disorders and the evaluation of motor recovery after rehabilitation. Muscle activation patterns were identified in both upper [18] and lower limbs [19]; furthermore, EMG was employed for studying abnormal muscular activity, such as spasticity [20], and effect such as muscle fatigue [21]. Moreover, the factorization of the EMG signal is also at the basis of motor control theories, such as muscle synergies, which provide insight into the control mechanisms for motor planning [22,23].…”

Section: Introductionmentioning

confidence: 99%

Combined Use of EMG and EEG Techniques for Neuromotor Assessment in Rehabilitative Applications: A Systematic Review

Brambilla

Pirovano

Mira

et al. 2021

Sensors

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Electroencephalography (EEG) and electromyography (EMG) are widespread and well-known quantitative techniques used for gathering biological signals at cortical and muscular levels, respectively. Indeed, they provide relevant insights for increasing knowledge in different domains, such as physical and cognitive, and research fields, including neuromotor rehabilitation. So far, EEG and EMG techniques have been independently exploited to guide or assess the outcome of the rehabilitation, preferring one technique over the other according to the aim of the investigation. More recently, the combination of EEG and EMG started to be considered as a potential breakthrough approach to improve rehabilitation effectiveness. However, since it is a relatively recent research field, we observed that no comprehensive reviews available nor standard procedures and setups for simultaneous acquisitions and processing have been identified. Consequently, this paper presents a systematic review of EEG and EMG applications specifically aimed at evaluating and assessing neuromotor performance, focusing on cortico-muscular interactions in the rehabilitation field. A total of 213 articles were identified from scientific databases, and, following rigorous scrutiny, 55 were analyzed in detail in this review. Most of the applications are focused on the study of stroke patients, and the rehabilitation target is usually on the upper or lower limbs. Regarding the methodological approaches used to acquire and process data, our results show that a simultaneous EEG and EMG acquisition is quite common in the field, but it is mostly performed with EMG as a support technique for more specific EEG approaches. Non-specific processing methods such as EEG-EMG coherence are used to provide combined EEG/EMG signal analysis, but rarely both signals are analyzed using state-of-the-art techniques that are gold-standard in each of the two domains. Future directions may be oriented toward multi-domain approaches able to exploit the full potential of combined EEG and EMG, for example targeting a wider range of pathologies and implementing more structured clinical trials to confirm the results of the current pilot studies.

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Using EMG Amplitude and Frequency to Calculate a Multimuscle Fatigue Score and Evaluate Global Shoulder Fatigue

Cited by 34 publications

References 22 publications

The Muscle Fatigue’s Effects on the sEMG-Based Gait Phase Classification: An Experimental Study and a Novel Training Strategy

The Muscle Fatigue’s Effects on the sEMG-Based Gait Phase Classification: An Experimental Study and a Novel Training Strategy

Effect of airplane passenger seat armrest height on human neck comfort when using a smartphone

Combined Use of EMG and EEG Techniques for Neuromotor Assessment in Rehabilitative Applications: A Systematic Review

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