Segmenting Mechanomyography Measures of Muscle Activity Phases Using Inertial Data

Woodward, Richard B.; Stokes, María; Shefelbine, Sandra J.; Vaidyanathan, Ravi

doi:10.1038/s41598-019-41860-4

Cited by 39 publications

(35 citation statements)

References 38 publications

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“…With respect to waveform analysis, previous studies have used both EMG and MMG to evaluate muscle contraction 26 , 32 , 33 . In these methods, the MMGRMS and MMGMPF are generally used for analysis, and we also used a similar method.…”

Section: Discussionmentioning

confidence: 99%

“…6 (MMG). The raw MMG data were band-pass filtered between 2 and 100 Hz, whereas the raw EMG data were band-pass filtered between 10 and 500 Hz using a fourth-order Butterworth filter as was performed in previous studies 33 , 39 . Added on this previous study, as the area under 2 Hz included much noise, lower threshold of 2 Hz for filtering was selected (Fig.…”

Section: Methodsmentioning

confidence: 99%

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Quantification of patellar tendon reflex using portable mechanomyography and electromyography devices

Tsuji

Misawa

Takigawa

et al. 2021

Sci Rep

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Deep tendon reflexes are one of the main components of the clinical nervous system examinations. These assessments are inexpensive and quick. However, evaluation can be subjective and qualitative. This study aimed to objectively evaluate hyperreflexia of the patellar tendon reflex using portable mechanomyography (MMG) and electromyography (EMG) devices. This study included 10 preoperative patients (20 legs) who had a pathology that could cause bilateral patellar tendon hyperreflexia and 12 healthy volunteers (24 legs) with no prior history of neurological disorders. We attached MMG/EMG sensors onto the quadriceps and tapped the patellar tendon with maximal and constant force. Our results showed a significantly high amplitude of the root mean square (RMS) and low frequency of the mean power frequency (MPF) in the rectus femoris, vastus medialis, and vastus lateralis muscles in both EMG and MMG with both maximal and constant force. Especially in the patients with cervical and thoracic myelopathy, the receiver operating characteristic (ROC) curve for diagnosing hyperreflexia of the patellar tendon showed a moderate to very high area under the curve for all EMG–RMS, EMG–MPF, MMG–RMS, and MMG–MPF values. The use of EMG and MMG for objectively quantifying the patellar tendon reflex is simple and desirable for future clinical applications and could help diagnose neurological disorders.

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Section: Discussionmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

Quantification of patellar tendon reflex using portable mechanomyography and electromyography devices

Tsuji

Misawa

Takigawa

et al. 2021

Sci Rep

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“…We chose three predictors of interest based on emerging wearable technologies and their ability to classify stress states, sleep status, and extent of physical exertion. For example, tooth-borne biosensors can monitor saliva in the oral cavity to measure alpha amylase and estimate stress states ( Robles et al, 2011 ; Tseng et al, 2018 ), wrist-worn accelerometers can monitor actigraphy and estimate sleep/wake cycles, including sleep loss and deprivation ( Dunican et al, 2018 ), and arm- or leg-worn mechanomyography and electromyography sensors can be used to characterize the intensity and duration of physical exertion ( Esposito et al, 1998 ; Woodward et al, 2019 ). Given the increasing availability of these sensors, these three specific predictors are likely to be used in real-world situations.…”

Section: Predictors Of Interest: Stress Sleep and Physical Exertionmentioning

confidence: 99%

Toward Predicting Human Performance Outcomes From Wearable Technologies: A Computational Modeling Approach

et al. 2021

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Wearable technologies for measuring digital and chemical physiology are pervading the consumer market and hold potential to reliably classify states of relevance to human performance including stress, sleep deprivation, and physical exertion. The ability to efficiently and accurately classify physiological states based on wearable devices is improving. However, the inherent variability of human behavior within and across individuals makes it challenging to predict how identified states influence human performance outcomes of relevance to military operations and other high-stakes domains. We describe a computational modeling approach to address this challenge, seeking to translate user states obtained from a variety of sources including wearable devices into relevant and actionable insights across the cognitive and physical domains. Three status predictors were considered: stress level, sleep status, and extent of physical exertion; these independent variables were used to predict three human performance outcomes: reaction time, executive function, and perceptuo-motor control. The approach provides a complete, conditional probabilistic model of the performance variables given the status predictors. Construction of the model leverages diverse raw data sources to estimate marginal probability density functions for each of six independent and dependent variables of interest using parametric modeling and maximum likelihood estimation. The joint distributions among variables were optimized using an adaptive LASSO approach based on the strength and directionality of conditional relationships (effect sizes) derived from meta-analyses of extant research. The model optimization process converged on solutions that maintain the integrity of the original marginal distributions and the directionality and robustness of conditional relationships. The modeling framework described provides a flexible and extensible solution for human performance prediction, affording efficient expansion with additional independent and dependent variables of interest, ingestion of new raw data, and extension to two- and three-way interactions among independent variables. Continuing work includes model expansion to multiple independent and dependent variables, real-time model stimulation by wearable devices, individualized and small-group prediction, and laboratory and field validation.

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“…First, Cudlip, et al [8] suggest the utilization of EMG, either via surface or fine wire, for testing to assess function and activity of the SM [8]. However, surface electrodes were determined to have some contamination in signal from surrounding structures, and fine wire electrodes are found to pick up electrical signal from only portions of the muscle [9]. Therefore, these commonly utilized methods of testing muscle activity are self-limiting.…”

Section: Introductionmentioning

confidence: 99%

Validity of Using Cross-Sectional Area for Strength Assessment of the Supraspinatus Muscle during Diagonal Horizontal Adduction Testing with Measured Isometric Resistance Applied through Dynamometry

Steven¹,

William²

2021

J Musculoskelet Disord Treat

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Background: A new test for assessing supraspinatus muscle (SM) injury, the Diagonal Horizontal Adduction test (DHA), has been developed which demonstrates more isolation of the SM and the similar widening of cross-sectional area (CSA) visualized through musculoskeletal ultrasound (MSK). Purpose:The purpose of this study was to determine whether the resistance changes in CSA of the SM using DHA testing are consistent with the forces generated by this muscle under voluntary contraction using Isometric Dynamometry (ID). Study Design:A prospective cohort study involving 44 subjects (mean age of 24.2 ± 1.9) with no previous history of shoulder surgery or pathology. All subjects performed graded resistance and no controls were necessary. Methods: Subjects were observed and measured while providing isometric contraction in the DHA position using Biodex ID during an isometric contraction at resistance levels of 0%, 50%, and 100% of maximum contraction. Cross-Section Area (CSA) of the SM was captured and measured using a Terason t3200 MSK ultrasound unit.Results: One-way Analysis of Variance with repeated measures examining differences of CSA at each level of resistance were significant at p < 0.05. Post-hoc testing revealed a significant difference in CSA between 0% and 100%, 0% and 50%, and 50% and 100% maximal voluntary contraction of the muscle. Conclusions:The CSA of the SM using MSK is consistent with the amount of force generated by the muscle during contraction. Greater force led to significantly greater CSA. Clinical Relevance:The change in CSA during increased resistance suggests previous comparisons of SM isolation using the DHA technique are useful in determining strength of contraction and amount of activation during manual testing and may be able to be used in place of fine-wire EMG.What this Study Adds to Existing Knowledge: The DHA test for the supraspinatus shows comparable results with CSA and MSK Ultrasound as compared to other SM testing methods such as local and fine wire EMG.

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Segmenting Mechanomyography Measures of Muscle Activity Phases Using Inertial Data

Cited by 39 publications

References 38 publications

Quantification of patellar tendon reflex using portable mechanomyography and electromyography devices

Quantification of patellar tendon reflex using portable mechanomyography and electromyography devices

Toward Predicting Human Performance Outcomes From Wearable Technologies: A Computational Modeling Approach

Validity of Using Cross-Sectional Area for Strength Assessment of the Supraspinatus Muscle during Diagonal Horizontal Adduction Testing with Measured Isometric Resistance Applied through Dynamometry

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