The sEMG signals were filtered and rectified (low cut-off filter 10 Hz, high-cut off filter 1000 Hz, notch filter at 50 Hz), digitized at a sampling rate of 2000 Hz with a common mode rejection ratio of > 80 dB (W4p-SP-W02, Delsys Inc., Boston, USA), and were stored on a laboratory computer for offline analysis. During offline analysis, the root mean square (RMS) of the sEMG signals during the three second maximum for each contraction were calculated using EMG Works® (Delsys Inc., Boston, USA). Subsequently, the signals of the 2 contractions per test position were averaged per assessor. Strength data was recorded in Newtons.
Emg works
Manufactured by Delsys
Sourced in United States
EMG Works is a comprehensive software package designed for the analysis and visualization of electromyography (EMG) data. The core function of EMG Works is to provide users with a tool for the acquisition, processing, and interpretation of EMG signals.
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7 protocols using emg works
1
sEMG Muscle Strength Measurement Protocol
2
Muscle Fatigue Assessment during Robotic Surgery
3
Evaluating Muscle Fatigue During Robotic Surgery
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Muscle activity was recorded bilaterally using EMG from 4 muscles: biceps brachii (arms), deltoid (shoulder), upper trapezius (neck), and latissimus dorsi (back). These muscles are the muscles most at risk for fatigue.20 (link),21 (link) The skin overlying the placement area was prepared by shaving and cleansing with a 70% isopropyl alcohol pad. EMG surface wireless sensors with a 10 mm interelectrode distance (Trigno, Delsys, Inc., Boston, MA, US) were then placed on these sites according to the Surface EMG for a Non-Invasive Assessment of Muscles22 and other recommendations.23 (link) The surgeons performed 1 isometric maximal voluntary contraction (MVC) of each muscle group before commencing the surgery, and EMG was recorded. During the predefined POI, 120 s of EMG recordings were performed (Table 1 ). In the RS group, these POIs were present in portions of the surgical procedures performed with the assistance of the robotic console. The raw EMG signal was collected at a sampling rate of 2000 Hz and filtered using high-pass and low-pass filters of 10 and 500 Hz, respectively. Next, the signal was smoothed using the root mean square (RMS) over 150 ms envelopes (EMG Works, Delsys Inc., Boston, MA). Finally, the average RMS EMG from the POI was normalized to isometric MVC EMG and computed as %MVCRMS.
4
Upper Limb Muscle Activity in Stroke
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Surface EMG was recorded from six muscles of the upper body on the more-affected side: trapezius (middle portion), deltoid medius, biceps brachii (BB), extensor carpi radialis, flexor carpi radialis, and first dorsal interosseus (FDI) using Trigno wireless sensors (Delsys, USA). The data were collected continuously during formal WMT sessions at early (day 2–3) and late (between days 12–14) therapy, and in a subset of patients, again during the 6-month follow-up session. Each EMG sensor contains four silver bar electrodes, arranged in two pairs with an interelectrode pair distance of 10 mm. The sensor is designed to maximize the detection of muscle activation in a field perpendicular to the muscle fibers. Data were amplified 300 times, filtered between 20 and 450 Hz, and sampled at 2 kHz using EMGworks (Delsys, USA) as per intrinsic device settings.
5
Normalized EMG Analysis of Upper Trapezius
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The EMG signal was collected using a Delsys Trigno system and analyzed using Delsys EMGworks ® (Delsys, NA) acquisition software. All raw EMG data were collected at a sampling rate of 2000 Hz. The raw data were band-pass filtered between 30 and 500 Hz using a finite impulse response filter and then further smoothed using root mean square method with a window length of 125 ms and window overlap of 62.5 ms. The MVIC was determined by identifying the highest activity during a 500-ms window during one of the two 5-second MVIC for each tested muscle. The average root mean square of the total arc of motion (concentric and eccentric phase) of the 3 test repetitions was normalized based on the MVIC and expressed as %MVIC for each muscle under each movement condition. Finally, 2 muscle activation ratios were calculated by dividing the normalized EMG activity of the UT by that of the SA (UT/SA activation ratio) and by dividing the normalized EMG activity of the UT by that of the LT (UT/LT activation ratio).
6
Muscle Activation and Torque Measurements
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Torque values were recorded from the analog output of the dynamometer. Analog torque and EMG data were collected through a 16-bit AD board (model USB-2659 BNC; National Instruments, Austin, TX, USA) connected to a personal computer. Data were sampled at 4 kHz using commercial software (EMGWorks, version 4.0; Delsys, Inc.). Torque and EMG responses to all stimulations were recorded. Peak twitch torque, average RFD, and peak-to-peak EMG of the gastrocnemius and soleus were calculated. Average RFD for each twitch response was calculated using time and force values from between when the signal crossed 20% of the difference between the start and peak of the signal, and the peak force of each response. To attenuate signal noise, torque data were filtered using a low-pass fourth-order zero-lag Butterworth filter, with a cutoff frequency of 24 Hz as determined by a residual analysis. Data were analyzed and compiled using standard functions and customwritten code (EMGWorks, version 4.0; Delsys, Inc.; Excel 2013; Microsoft Corporation, Redmond, WA, USA; Matlab, version R2012b; Mathworks, Inc.).
7
Wireless EMG Assessment of Cycling
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Wireless Electromyography (EMG) electrodes (Trigno, Delsys, Boston, Mass) were placed onto the belly of right thigh including; vastus medialis (VM), rectus femoris (RF), vastus lateralis (VL), and biceps femoris (BF). The sites were prepared by abrasion then cleaned with alcohol wipes and skin was marked with a broad‐tip pen. For analyses, the data acquisition software (EMG Works, Delsys, Boston, Mass) was interfaced with LabChart (LabChart v8.1.6, ADInstruments, NSW, Australia) and simultaneously recorded throughout the duration of the cycling protocols. The EMG data were sampled at 1 kHz on the LabChart Software with a bandwidth filter of 20–450 Hz applied to remove movement artifact. The EMG data were later calculated as the root mean square (RMS) and analyzed using LabChart Reader (LabChart v8.1.2). At each 2 km interval during the TTs, every contraction during a 5 sec epoch were visually inspected for movement artifact, and the average 10 msec around the peak RMS amplitude of each contraction was examined. Peak EMG RMS during the maximal sprints was described as 100% recruitment. EMG data during the TT were normalized by dividing the peak EMG RMS of each 5 sec epoch every 2 km by the peak sprint values and are expressed as a percent (%) change.
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