Electromyogram features during linear torque decrement and their changes with fatigue

Impact of repetitive mouse aiming on muscle fatigue and fine motor performance of the distal upper limb

Gaming is demanding, however, the impact of gaming on muscle fatigue and performance changes is unclear. The purpose of this study was to evaluate muscle fatigue and performance impairments during an extended mouse aiming fatigue protocol. Twenty participants were recruited (8F, 12 M), separated into gaming and non-gaming groups. Surface electromyography was measured from eight muscles of the right distal upper limb. Participants performed a 30-second aiming task using aim training software. The fatiguing protocol involved six, 5-minute bouts of hitting targets in AimLab. To assess muscle fatigue, reference contractions of radial and ulnar deviation (30% max) as well as ratings of perceived fatigue (RPF) were collected throughout the experiment. The wrist extensors produced the greatest levels of muscle activity while aiming a mouse, producing up to 9.3% MVC. No changes in performance measures were observed throughout the experiment. However, significant fatigue of extensors was observed through changes in RPF, mean power frequency, median frequency, and spike shape analysis. Performance metrics indicated no impairments caused by the fatiguing protocol. Changes in EMG characteristics indicate that the wrist extensors became significantly fatigued through prolonged mouse aiming, indicating the extensors may be prone to gaming related fatigue and injury.

Impact of repetitive mouse clicking on forearm muscle fatigue and mouse aiming performance

Exercise induced performance fatigue has been shown to impair many aspects of fine motor function in the distal upper limb. However, most fatiguing protocols do not reflect the conditions experienced with computer use. The purpose of this study was to determine how a prolonged, low-force mouse clicking fatigue protocol impacts performance fatigue of the distal upper limb for gamers and non-gamers. Participants completed a total of 1 h of mouse clicking at 5 clicks per second. Muscle fatigue and performance were intermittently assessed. RMS amplitude increased for the forearm flexors throughout the fatigue protocol. Accuracy decreased following the first bout of clicking and returned to baseline values after 40-min. EDC and ECU displayed the greatest muscle activity while aiming, producing 11.4% and 12.9% of MVC, respectively. These findings indicate that mouse clicking may not result in performance fatigue, however, high levels of extensor activity may explain common injuries among gamers.

Using force or EMG envelope as feedback signal for motor control system

PURPOSE

This work studied muscle neuro-mechanics during symmetrical up-going ramp (UGR) and down-going ramp (DGR).

AIM

to evaluate during the modulation of muscular action the outcome of force feedback (FF) or neural feedback (NF) on the behavior of the trailing signals - i.e. the EMG envelope (eEMG) for FF or force signal for NF.

METHOD

Subjects: 20. Investigated muscles: dorsal interosseous (FDI) and tibialis anterior (TA). Detected signals: force and EMG. Visual feedback: force (FF), eEMG (NF). Effort triangles: ramps duration 7.5 s, vertex at 50 and 100 % of the maximal voluntary action. Eventually, each subject performed FF50%, FF100%, NF50% and NF100% per each muscle. In each condition the areas beneath the force and eEMG signals were computed to calculate the ratios between the DGR and UGR values during the different tasks (force area DGR / force area UGR; eEMG area DGR / eEMG area UGR). Electro-mechanical coupling efficiency (EMCE) was estimated through the eEMG area / force area ratio for both UGR and DGR in each condition.

RESULTS

a) FF. FDI: eEMG area ratio was 0.84 ± 0.15 and 0.73 ± 0.17 for FF50% and FF100%, respectively. TA: eEMG area ratio was 0.88 ± 0.11 and 0.91 ± 0.17 for FF50% and FF100%, respectively. b) NF: FDI: force area ratio was 1.18 ± 0.13 and 1.17 ± 0.13 for NF50% and NF100%, respectively. TA: force area ratio was 1.17 ± 0.21 and 1.07 ± 0.19 for NF50% and NF100%, respectively. c) DGR EMCE was greater than UGR EMCE in all four tasks.

CONCLUSION

The influence of UGR on deployed EMCE in the following force decrement phase underpins the changes of trailing signals area during DGR. This underlines the necessity of a careful evaluation of the features of FF or NF for experimental studies or rehabilitation purposes involving the motor control system.

Transient Electromyographic Responses by Isokinetic Torque Release during Mechanically Assisted Elbow Flexion

Power assistance on joint torque may not be beneficial to all the related muscles. We investigated the effects of power assistance on torque release during isokinetic elbow flexion. An isokinetic dynamometer system was used to simulate dynamic elbow flexion with power assistance, which altered the exercise conditions of baseline isometric torque (greater and lower) and rotation speed (faster and slower) of the lever arm. Ten male right-handed participants performed exercise tasks using the system. We measured (1) the electromyogram (EMG) amplitudes of the biceps brachii (BB), brachioradialis (BR), and triceps brachii (TB) muscles, (2) torque output and its variability, and (3) the perceived assistance level. Transient responses of the objective measurements were analyzed by observing three time epochs before and after power assistance. Greater variability and lower perceived assistance levels were observed when greater torque was released at a faster rotation speed. The torque output and EMG amplitudes of BB and BR muscles decreased over time. However, EMG amplitudes in the TB muscle were relatively constant until 200 ms after power assistance resulting in greater muscle co-contraction. This could be attributed to the increased postural stability of the human musculature system when the external perturbation on joint movement occurred by power assistance, independent of exercise conditions.

Effects of mechanical assistance on muscle activity and motor performance during isometric elbow flexion

Mechanical assistance on joint movement is generally beneficial; however, its effects on cooperative performance and muscle activity needs to be further explored. This study examined how motor performance and muscle activity are altered when mechanical assistance is provided during isometric force control of ramp-down and hold phases. Thirteen right-handed participants (age: 24.7 ± 1.8 years) performed trajectory tracking tasks. Participants were asked to maintain the reference magnitude of 47 N (REF) during isometric elbow flexion. The force was released to a step-down magnitude of either 75% REF or 50% REF and maintained, with and without mechanical assistance. The ramp-down durations of force release were set to 0.5, 2.5, or 5.0 s. Throughout the experiment, we measured the following: (1) the force output using load cells to compute force variability and overshoot ratio; (2) peak perturbation on the elbow movement using an accelerometer; (3) the surface electromyography (sEMG) from biceps brachii and triceps brachii muscles; and (4) EMG oscillation from the biceps brachii muscle in the bandwidth of 15-45 Hz. Our results indicated that mechanical assistance, which involved greater peak perturbation, demonstrated lower force variability than non-assistance (p < 0.01), while EMG oscillation in the biceps brachii muscle from 15 to 45 Hz was increased (p < 0.05). These findings imply that if assistive force is provided during isometric force control, the central nervous system actively tries to stabilize motor performance by controlling specific motor unit activity in the agonist muscle.

Force and electromyography responses during isometric force release of different rates and step-down magnitudes

This study investigated motor responses of force release during isometric elbow flexion by comparing effects of different ramp durations and step-down magnitudes. Twelve right-handed participants (age: 23.1 ± 1.1) performed trajectory tracking tasks. Participants were instructed to release their force from the reference magnitude (REF; 40% of maximal voluntary contraction force) to a step-down magnitude of 67% REF or 33% REF and maintain the released magnitude. Force release was guided by ramp durations of either 1 s or 5 s. Electromyography of the biceps brachii and triceps brachii was performed during the experimental task, and the co-contraction ratio was evaluated. Force output was recorded to evaluate the parameters of motor performance, such as force variability and overshoot ratio. Although a longer ramp duration of 5 s decreased the force variability and overshoot ratio than did shorter ramp duration of 1 s, higher perceived exertion and co-contraction ratio were followed. Force variability was greater when force was released to the step-down magnitude of 33% REF than that when the magnitude was 67% REF, however, the overshoot ratio showed opposite results. This study provided evidence proving that motor control strategies adopted for force release were affected by both duration and step-down magnitude. In particular, it implies that different control strategies are required according to the level of step-down magnitude with a relatively short ramp duration.

Electrical Stimulation Frequency and Skeletal Muscle Characteristics: Effects on Force and Fatigue

This investigation aimed to determine the force and muscle surface electromyography (EMG) responses to different frequencies of electrical stimulation (ES) in two groups of muscles with different size and fiber composition (fast- and slow-twitch fiber proportions) during a fatigue-inducing protocol. Progression towards fatigue was evaluated in the abductor pollicis brevis (APB) and vastus lateralis (VL) when activated by ES at three frequencies (10, 35, and 50Hz). Ten healthy adults (mean age: 23.2 ± 3.0 years) were recruited; participants signed an IRB approved consent form prior to participation. Protocols were developed to 1) identify initial ES current intensity required to generate the 25% maximal voluntary contraction (MVC) at each ES frequency and 2) evaluate changes in force and EMG activity during ES-induced contraction at each frequency while progressing towards fatigue. For both muscles, stimulation at 10Hz required higher current intensity of ES to generate the initial force. There was a significant decline in force in response to ES-induced fatigue for all frequencies and for both muscles (p<0.05). However, the EMG response was not consistent between muscles. During the progression towards fatigue, the APB displayed an initial drop in force followed by an increase in EMG activity and the VL displayed a decrease in EMG activity for all frequencies. Overall, it appeared that there were some significant interactions between muscle size and fiber composition during progression towards fatigue for different ES frequencies. It could be postulated that muscle characteristics (size and fiber composition) should be considered when evaluating progression towards fatigue as EMG and force responses are not consistent between muscles.

Spike shape analysis of electromyography for parkinsonian tremor evaluation

INTRODUCTION

Standard electromyography (EMG) parameters have limited utility for evaluation of Parkinson disease (PD) tremor. Spike shape analysis (SSA) EMG parameters are more sensitive than standard EMG parameters for studying motor control mechanisms in healthy subjects. SSA of EMG has not been used to assess parkinsonian tremor. This study assessed the utility of SSA and standard time and frequency analysis for electromyographic evaluation of PD-related resting tremor.

METHODS

We analyzed 1-s periods of EMG recordings to detect nontremor and tremor signals in relaxed biceps brachii muscle of seven mild to moderate PD patients.

RESULTS

SSA revealed higher mean spike amplitude, duration, and slope and lower mean spike frequency in tremor signals than in nontremor signals. Standard EMG parameters (root mean square, median, and mean frequency) did not show differences between the tremor and nontremor signals.

CONCLUSIONS

SSA of EMG data is a sensitive method for parkinsonian tremor evaluation.