Background: muscle activation measured by electromyography (EMG) provides additional insight into functional differences between movements and muscle involvement. Objective: to evaluate the EMG of ...triceps surae during heel-raise exercise in healthy subjects performed at leg press machine with different feet positions. Methods: ten trained healthy male adults aged between 20 and 30 years voluntarily took part in the study. After biometric analyses the EMG signals were obtained using a 8-channel telemeterized surface EMG system (EMG System do Brazil, Brazil Ltda) (amplifier gain: 1000x, common rejection mode ratio >100 dB, band pass filter: 20 to 500 Hz). All data was acquired and processed using a 16-bit analog to digital converter, with a sampling frequency of 2kHz on the soleus (Sol), medial (GM) and lateral (GL) gastrocnemius muscles in both legs, in accordance with the recommendations of SENIAN. The root mean square (RMS) of the EMG amplitude was calculated to evaluate muscle activity of the three muscles. After being properly prepared for eletromyography procedures, all subjects were instructed to perform 3 sets of 5 repetitions during heel-raise exercise using the maximal load that enabled 10 repetitions on leg press 45° machine, each set being performed with one of the following feet positions: neutral (0º), internal and external rotation (both with 45° from neutral position). The tests were sequential and applied a 5-minute rest interval between sets. The order of the tests was randomized. Results: thought had been found interaction (F=0.27, P= 0.75) on RMS parameters and feet position, the values of Sol muscle were significantly (F=17.86, P= 0.003) lower compared with GL and GM muscles independently of feet position. Conclusion: The change in the feet position during the heel-rise exercise performed in the leg press does not influence the activation of the triceps surae, and the soleus is less activated than the gastrocnemius in that exercise.
The relatively large pick-up volume of surface electrodes has for long motivated the concern that muscles other than that of interest may contribute to surface electromyograms (EMGs). Recent findings ...suggest however the pick-up volume of surface electrodes may be smaller than previously appreciated, possibly leading to the detection of surface EMGs insensitive to muscle activity. Here we combined surface and intramuscular recordings to investigate how comparably action potentials from gastrocnemius and soleus are represented in surface EMGs detected with different inter-electrode distances. We computed the firing instants of motor units identified from intramuscular EMGs detected from gastrocnemius and soleus while five participants stood upright. We used these instants to trigger and average surface EMGs detected from multiple skin regions along gastrocnemius. Results from 66 motor units (whereof 31 from gastrocnemius) revealed the surface-recorded amplitude of soleus action potentials was 6% of that of gastrocnemius and did not decrease for inter-electrode distances smaller than 4 cm. Gastrocnemius action potentials were more likely detected for greater inter-electrode distances and their amplitude increased steeply up to 5 cm inter-electrode distance. These results suggest that reducing inter-electrode distance excessively may result in the detection of surface EMGs insensitive to gastrocnemius activity without substantial attenuation of soleus crosstalk.
Memories Faulkner, Zane Edward; Leaver, Echo Elizabeth
Imagination, cognition and personality,
12/2016, Volume:
36, Issue:
2
Journal Article
Peer reviewed
The fallibility of memory has important implications for various disciplinary fields, as well as societal interests. Research on false memory abounds in terms of the ability of researchers to implant ...memories for plausible and highly implausible negative events. The extant literature does not currently answer the question of whether memories for positive events can be implanted. Moreover, previous research has attempted, with mixed success, to discriminate between true and false memories employing different objective and subjective measures. Currently, there is still no conclusive way to distinguish between true and false memories. The present study expanded upon the current deficits in the research literature by inducing both positive and negative false memory events in participants. Physiological measures (i.e., skin conductance, heart rate, electromyography, and pulse plethysmography) were employed in an effort to discriminate between participants’ true and false memories. Results indicated that positive and negative events can be implanted at an impressively high rate and with a very simple manipulation. False memories were found to exhibit a greater arousal pattern than true memories and, specifically with electromyography, positive false memories elicited greater arousal patterns than positive true memories.
Objectives/Hypothesis
Laryngeal muscle activation is a complex and dynamic process. Current evaluation methods include needle and surface electromyography (sEMG). Limitations of needle ...electromyography include patient discomfort, interpretive complexity, and limited duration of recording. sEMG demonstrates interpretive challenges given loss of spatial selectivity. Application of high‐density sEMG (HD sEMG) arrays were evaluated for potential to compensate for spatial selectivity loss while retaining benefits of noninvasive monitoring.
Study Design
Basic science.
Methods
Ten adults performed phonatory tasks while a 20‐channel array recorded spatiotemporal data of the anterior neck. Data were processed to provide average spectral power of each electrode. Comparison was made between rest, low‐, and high‐pitch phonation. Two‐dimensional (2D) spectral energy maps were created to evaluate use in gross identification of muscle location.
Results
Three phonatory tasks yielded spectral power measures across the HD sEMG array. Each electrode within the array demonstrated unique power values across all subjects (P < .001). Comparison of each electrode to itself across phonatory tasks yielded differences in all subjects during rest versus low versus high, rest versus low, and rest versus high and in 9/10 subjects (P < .001) for low versus high phonation. Symmetry of HD sEMG signal was noted. Review of 2D coronal energy maps allowed for gross identification of cricothyroid muscle amidst anterior strap musculature.
Conclusions
HD sEMG can be used to identify differences in anterior neck muscle activity between rest, low‐, and high‐pitch phonation. HD sEMG of the anterior neck holds potential to enhance diagnostic and therapeutic monitoring for pathologies of laryngeal function.
Level of Evidence
NA
Laryngoscope, 129:2347–2353, 2019
A proposal for new diagnostic criteria for ALS Shefner, Jeremy M.; Al-Chalabi, Ammar; Baker, Mark R. ...
Clinical neurophysiology,
August 2020, 2020-08-00, 20200801, Volume:
131, Issue:
8
Journal Article
This tutorial is aimed primarily to non-engineers, using or planning to use surface electromyography (sEMG) as an assessment tool for muscle evaluation in the prevention, monitoring, assessment and ...rehabilitation fields. The main purpose is to explain basic concepts related to: (a) signal detection (electrodes, electrode–skin interface, noise, ECG and power line interference), (b) basic signal properties, such as amplitude and bandwidth, (c) parameters of the front-end amplifier (input impedance, noise, CMRR, bandwidth, etc.), (d) techniques for interference and artifact reduction, (e) signal filtering, (f) sampling and (g) A/D conversion, These concepts are addressed and discussed, with examples.
The second purpose is to outline best practices and provide general guidelines for proper signal detection, conditioning and A/D conversion, aimed to clinical operators and biomedical engineers. Issues related to the sEMG origin and to electrode size, interelectrode distance and location, have been discussed in a previous tutorial. Issues related to signal processing for information extraction will be discussed in a subsequent tutorial.
In recent years, deep learning algorithms have become increasingly more prominent for their unparalleled ability to automatically learn discriminant features from large amounts of data. However, ...within the field of electromyography-based gesture recognition, deep learning algorithms are seldom employed as they require an unreasonable amount of effort from a single person, to generate tens of thousands of examples. This paper's hypothesis is that general, informative features can be learned from the large amounts of data generated by aggregating the signals of multiple users, thus reducing the recording burden while enhancing gesture recognition. Consequently, this paper proposes applying transfer learning on aggregated data from multiple users while leveraging the capacity of deep learning algorithms to learn discriminant features from large datasets. Two datasets comprised 19 and 17 able-bodied participants, respectively (the first one is employed for pre-training), were recorded for this work, using the Myo armband. A third Myo armband dataset was taken from the NinaPro database and is comprised ten able-bodied participants. Three different deep learning networks employing three different modalities as input (raw EMG, spectrograms, and continuous wavelet transform (CWT)) are tested on the second and third dataset. The proposed transfer learning scheme is shown to systematically and significantly enhance the performance for all three networks on the two datasets, achieving an offline accuracy of 98.31% for 7 gestures over 17 participants for the CWT-based ConvNet and 68.98% for 18 gestures over 10 participants for the raw EMG-based ConvNet. Finally, a use-case study employing eight able-bodied participants suggests that real-time feedback allows users to adapt their muscle activation strategy which reduces the degradation in accuracy normally experienced over time.
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