We are pleased to announce that BIDS Extension Proposal 42 - Electromyogrpahy is open for community review!

https://github.com/bids-standard/bids-specification/discussions/2219

The review period is open from September 29 - October 10.
#bids #neuroimaging #electromyography #emg

Community Review: BEP042 - Electromyography (EMG) · bids-standard bids-specification · Discussion #2219

We are pleased to announce the community review period for BIDS Extension Proposal (BEP) 042! BEP042 extends the BIDS standard to include electromyography recordings. The draft specification may be...

GitHub
Thrilled to share that my abstract “Effects of Grip Variation on Muscle Excitation and Spatial Activation Patterns During the Lat Pull-Down: A Preliminary HD-sEMG Study” was accepted as an Oral Communication at SISMeS 2025 🎉
#HDsEMG #Electromyography #ResistanceTraining #LatPullDown #SportsScience #SISMeS2025
Meta's Next-Gen Leak! Quest 3 Enhancements & Games Coming soon (& More!)

YouTube
The VR Industry is about to CHANGE

YouTube
Analyzing the Impact of Accumulated Training Shots on Electromyography Parameters in Trained Archery Athletes: Exploring Fatigue and Its Association with Training Practices

Background: Accumulated training shots throughout a session may induce changes in electromyography (EMG) parameters of the primary muscles involved in movement in archery athletes. Thus, the aim of this study was two-fold: (i) analyze the impact of 50 and 100 archery shots on a single session on the EMG parameters of trained archery athletes; and (ii) explore the effects of training routines of the athletes to cope with fatigue induced by the accumulated shots on the EMG parameters. Methods: They were divided into two groups: those who regularly performed ≤100 shots per training session (n = 13) and those who performed >100 shots per session (n = 7). The participants were exposed to a condition involving 100 archery shots, with measurements taken at baseline, after 50, and after 100 shots. EMG was used to measure the electric potential of the deltoid (middle and posterior), trapezius (upper, middle, and lower), and infraspinatus during isometric contraction. The collected outcomes included the mean and maximal amplitude of EMG root mean square (EMGRMS, µV) and the median frequency of the raw surface EMG signal power spectrum (EMGMED, Hz). Results: The results showed significant differences for most of the analyzed muscles analyzed, specifically in the deltoid, infraspinatus, and trapezius (p < 0.05). Conclusions: Our study suggests that in most of the muscles analyzed, EMG parameters—particularly mean and maximal EMGRMS—tend to increase from baseline to 50 shots, with significant declines observed after 100 shots, indicating muscle fatigue. The training routines of the athletes do not appear to significantly influence their response to fatigue conditions.

MDPI
Optimal Identification of Muscle Synergies From Typical Sit-to-Stand Clinical Tests

<italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">Goal:</i> The goal of this manuscript is to investigate the optimal methods for extracting muscle synergies from a sit-to-stand test; in particular, the performance in identifying the modular structures from signals of different length is characterized. <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">Methods:</i> Surface electromyography signals have been recorded from instrumented sit-to-stand trials. Muscle synergies have then been extracted from signals of different duration (i.e. 5 times sit to stand and 30 seconds sit to stand) from different portions of a complete sit-to-stand-to-sit cycle. Performance have then been characterized using cross-validation procedures. Moreover, an optimal method based on a modified Akaike Information Criterion measure is applied on the signal for selecting the correct number of synergies from each trial. <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">Results:</i> Results show that it is possible to identify correctly muscle synergies from relatively short signals in a sit-to-stand experiment. Moreover, the information about motor control structures is identified with a higher consistency when only the sit-to-stand phase of the complete cycle is considered. <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">Conclusions:</i> Defining a set of optimal methods for the extraction of muscle synergies from a clnical test such as the sit-to-stand is of key relevance to ensure the applicability of any synergy-related analysis in the clinical practice, without requiring knowledge of the technical signal processing methods and the underlying features of the signal.

Hey Mastodon, I’m trying to help find someone doing research involving human facial EMG recording. (e.g. levator labii and corrugator signals) You know anyone? Heard any rumors?
#EMG
#Electromyography

Please encourage your early-career colleagues to apply for this award! If you are an early-career psychophysiology researcher, please consider applying. Details are presented below. #psychophysiology #erp #eeg #cardiovascular #electromyography #fmri

https://myemail.constantcontact.com/SPR-2023-Early-Career-Award-Applications---Now-Open-.html?soid=1132313913223&aid=nj6SNQTPIgQ&fbclid=IwAR3_jKZjLwfjXu_CBU16djFWPgR-nrdzGJu2CUJmi5Yk5qwgv_BO-hoJKCE

SPR 2023 Early Career Award Applications - Now Open!

SPR 2023 Early Career Award Application Please encourage your early-career colleagues to apply for this award! If you are an early-career researcher, please consider applying. Details are presented be

Society for Psychophysiological Research

Electromyography Hack Chat

Join us on Wednesday, January 19 at noon Pacific as we kick off the 2022 Hack Chat season with the Electromyography Hack Chat with hut!

It's one of the simplest acts most people can perform, but just wiggling your finger is a vastly complex process under the hood. Once you consciously decide to move your digit, a cascade of electrochemical reactions courses from the brain down the spinal cord and along nerves to reach the muscles fibers of the forearm, where still more reactions occur to stimulate the muscle fibers and cause them to contract, setting that finger to wiggling.

The electrical activity going on inside you while you're moving your muscles is actually strong enough to make it to the skin, and is detectable using electromyography, or EMG. But just because a signal exists doesn't mean it's trivial to make use of. Teasing a usable signal from one muscle group amidst the noise from everything else going on in a human body can be a chore, but not an insurmountable one, even for the home gamer.

To make EMG a little easier, our host for this Hack Chat, hut, has been hard at work on PsyLink, a line of prototype EMG interfaces that can be used to detect muscle movements and use them to control whatever you want. In this Hack Chat, we'll dive into EMG in general and PsyLink in particular, and find out how to put our muscles to work for something other than wiggling our fingers.

Our Hack Chats are live community events in the Hackaday.io Hack Chat group messaging. This week we’ll be sitting down on Wednesday, January 19 at 12:00 PM Pacific time. If time zones have you tied up, we have a handy time zone converter.

#hackadaycolumns #actionpotential #electromyography #emg #hackchat #muscle #nerve #neural #phsyiology

Electromyography Hack Chat

Join us on Wednesday, January 19 at noon Pacific as we kick off the 2022 Hack Chat season with the Electromyography Hack Chat with hut! It’s one of the simplest acts most people can perform, …

Hackaday

PsyLink An Open Source Neural Interface For Non-Invasive EMG

We don't see many EMG (electromyography) projects, despite how cool the applications can be. This may be because of technical difficulties with seeing the tiny muscular electrical signals amongst the noise, it could be the difficulty of interpreting any signal you do find. Regardless, [hut] has been striving forwards with a stream of prototypes, culminating in the aptly named 'Prototype 8'

The current prototype uses a main power board hosting an Arduino Nano 33 BLE Sense, as well as a boost converter to pump up the AAA battery to provide 5 volts for the Arduino and a selection of connected EMG amplifier units. The EMG sensor is based around the INA128 instrumentation amplifier, in a pretty straightforward configuration. The EMG samples along with data from the IMU on the Nano 33 BLE Sense, are passed along to a connected PC via Bluetooth, running the PsyLink software stack. This is based on Python, using the BLE-GATT library for BT comms, PynPut handing the PC input devices (to emit keyboard and mouse events) and tensorflow for the machine learning side of things. The idea is to use machine learning from the EMG data to associate with a specific user interface event (such as a keypress) and with a little training, be able to play games on the PC with just hand/arm gestures. IMU data are used to augment this, but in this demo, that's not totally clear.

An earlier prototype of the PsyLink.

All hardware and software can be found on the project codeberg page, which did make us double-take as to why GnuRadio was being used, but thinking about it, it's really good for signal processing and visualization. What a good idea!

Obviously there are many other use cases for such a EMG controlled input device, but who doesn't want to play Mario Kart, you know, for science?

Checkout the demo video (embedded below) and you can see for yourself, just be aware that this is streaming from peertube, so the video might be a little choppy depending on your local peers. Finally, if Mastodon is your cup of tea, here's the link for that. Earlier projects have attempted to dip into EMG before, like this Bioamp board from Upside Down Labs. Also we dug out an earlier tutorial on the subject by our own [Bil Herd.]

#medicalhacks #analog #arduino #electromyography #emg #gnuradio #instrumentationamp #opamp #python

PsyLink An Open Source Neural Interface For Non-Invasive EMG

We don’t see many EMG (electromyography) projects, despite how cool the applications can be. This may be because of technical difficulties with seeing the tiny muscular electrical signals amo…

Hackaday