Experimental Validation of a New Dynamic Muscle Fatigue Model (original) (raw)
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Validation of a New Dynamic Muscle Fatigue Model and DMET Analysis
International Journal of Virtual Reality
Automation in industries reduced the human effort, but still there are many manual tasks in industries which lead to musculo-skeletal disorder (MSD). Muscle fatigue is one of the reasons leading to MSD. The objective of this article is to experimentally validate a new dynamic muscle fatigue model taking cocontraction factor into consideration using electromyography (EMG) and Maximum voluntary contraction (MVC) data. A new model (Seth's model) is developed by introducing a co-contraction factor 'n' in R. Ma's dynamic muscle fatigue model. The experimental data of ten subjects are used to analyze the muscle activities and muscle fatigue during extension-flexion motion of the arm on a constant absolute value of the external load. The findings for co-contraction factor shows that the fatigue increases when co-contraction index decreases. The dynamic muscle fatigue model is validated using the MVC data, fatigue rate and co-contraction factor of the subjects. It has been f...
A new simple dynamic muscle fatigue model and its validation
2009
Musculoskeletal disorder (MSD) is one of the major health problems in mechanical work especially in manual handling jobs. Muscle fatigue is believed to be the main reason for MSD. Posture analysis techniques have been used to expose MSD risks of the work, but most of the conventional methods are only suitable for static posture analysis. Meanwhile the subjective influences from the inspectors can result differences in the risk assessment. Another disadvantage is that the evaluation has to be taken place in the workshop, so it is impossible to avoid some design defects before data collection in the field environment and it is time consuming. In order to enhance the efficiency of ergonomic MSD risk evaluation and avoid subjective influences, we develop a new muscle fatigue model and a new fatigue index to evaluate the human muscle fatigue during manual handling jobs in this paper. Our new fatigue model is closely related to the muscle load during working procedure so that it can be used to evaluate the dynamic working process. This muscle fatigue model is mathematically validated and it is to be further experimental validated and integrated into a virtual working environment to evaluate the muscle fatigue and predict the MSD risks quickly and objectively. Relevance to industry Muscle fatigue is one of the main reasons causing MSDs in industry, especially for mechanical work. Correct evaluation of muscle fatigue is necessary to determine work-rest regimens and reduce the risks of MSD.
Electromyographic models to assess muscle fatigue
Journal of Electromyography and Kinesiology, 2012
Muscle fatigue is a common experience in daily life. Many authors have defined it as the incapacity to maintain the required or expected force, and therefore, force, power and torque recordings have been used as direct measurements of muscle fatigue. In addition, the measurement of these variables combined with the measurement of surface electromyography (sEMG) recordings (which can be measured during all types of movements) during exercise may be useful to assess and understand muscle fatigue. Therefore, there is a need to develop muscle fatigue models that relate changes in sEMG variables with muscle fatigue. However, the main issue when using conventional sEMG variables to quantify fatigue is their poor association with direct measures of fatigue. Therefore, using different techniques, several authors have combined sets of sEMG parameters to assess muscle fatigue. The aim of this paper is to serve as a state-of-the-art summary of different sEMG models used to assess muscle fatigue. This paper provides an overview of linear and non-linear sEMG models for estimating muscle fatigue, their ability to assess power loss and their limitations due to neuromuscular changes after a training period.
Measurement of human muscle fatigue
Human muscle fatigue has been studied using a wide variety of exercise models, protocols and assessment methods. Based on the definition of fatigue as 'any reduction in the maximal capacity to generate force or power output', the different methods to measure fatigue are discussed. It is argued that reliable and valid measures must include either assessment of maximal voluntary contraction force or power, or the force generated by electrical stimulation. By comparing tetanic stimulation and maximal voluntary contraction force one may reveal whether fatigue is of central origin, or whether peripheral mechanisms are involved. Adequate use of twitch interpolation provides an even more sensitive measure for central fatigue. Indirect methods as endurance times and electromyography show variable responses during exercise and no close relationship to fatigue. Hence these methods are of limited value in measurement of human muscle fatigue. © 1997 Elsevier Science B.V.
Human Muscle Fatigue Model in Dynamic Motions
Latest Advances in Robot Kinematics, 2012
Human muscle fatigue is considered to be one of the main reasons for Musculoskeletal Disorder (MSD). Recent models have been introduced to define muscle fatigue for static postures. However, the main drawbacks of these models are that the dynamic effect of the human and the external load are not taken into account. In this paper, each human joint is assumed to be controlled by two muscle groups to generate motions such as push/pull. The joint torques are computed using Lagrange's formulation to evaluate the dynamic factors of the muscle fatigue model. An experiment is defined to validate this assumption and the result for one person confirms its feasibility. The evaluation of this model can predict the fatigue and MSD risk in industry production quickly.
Statistical Investigation of Muscle Fatigue using Multi- Sensors
International Journal of Mechanical & Mechatronics Engineering IJMME-IJENS, 2016
The aim of this work is to find the relationship between EMG, MMG and AMG during muscle fatigue. To achieve the goal of this work, 3 different myograms (EMG, MMG and AMG) were recorded from the biceps femoris during the isometric contraction using bipolar surface EMG electrodes, accelerometers and cardio microphone. Nine statistical features were extracted from time and frequency domain. The extracted features were tests using Pearson Correlation and Linear Regression, to find the relationship between the features and behavior of the feature due to muscle fatigue. Based on the Pearson correlation result, there are relationships between these 3 myograms. In this paper, we also have discussed the behavior of myograms due to muscle fatigue. Index Term-EMG, MMG, AMG, Muscle Fatigue.
The Importance of Electromyography and Contraction Mechanogram in the Study of Muscular Fatigue
2000
Introduction: A controversial topic in physiology is muscular fatigue, raising still unanswered questions regarding its causes and mechanisms. Aims: To investigate the role of electromyography and contraction mechanogram in the evaluation of muscular fatigue and to establish the circumstances that ensures a greater physical effort with a lesser degree of muscular fatigue. Materials: Ten healthy subjects in whom we recorded the global surface electromyogram (SEMG) and muscular contraction mechanogram using a Medicore (type MG 42) electromyograph (produced in Hungary), respectively a BIOPAC system (USA). Muscular recordings were stored and subsequently processed using two personal computers. Methods: The study was performed on ten healthy subjects, of both genders and similar ages, and consisted in the recording of global surface electromyography (SEMG) and mechanogram of the voluntary maximal isometric contractions of the finger flexor in two different sessions of physical effort:-voluntary maximal isometric contractions of short duration (high frequency-Hi)-4 sec, followed by rest intervals of 6 sec-30 contractions in 5 min;-voluntary maximal isometric contractions of longer duration (low frequency-Lo)-40 sec, with rest intervals of 60 sectotal 3 contractions in 5 minutes. In both cases, during the 5-minute sessions, the subjects contracted the finger flexor for 120 sec, while the total rest period was 180 seconds. Results: The results are synthetically represented in several tables. Conclusions: When the muscular contractions and the resting intervals are shorter, the total global physical effort performed in the same unit of time is 32% greater and with less fatigue, than when muscular contractions and resting intervals are longer.
The Fatigue Vector: A New Bi-dimensional Parameter for Muscular Fatigue Analysis
IFMBE Proceedings, 2014
The aim of this study is to introduce a new parameter for fatigue investigations, which relies on a bidimensional analysis of sEMG signals in temporal and spectral domains. The new parameter, the Fatigue Vector, is defined in a space domain whose coordinates are the amplitude and the mean spectral frequency of the sEMG signal. The performance of the Fatigue Vector has been compared to those of classical parameters. The analysis has been carried on signals recorded from Rectus Femoris, Vastus Lateralis and Vastus Medialis during knee extension repetitions performed until exhaustion. The task was repeated twice with different biomechanical loads in order to test the muscular activity variations with respect to the different force demands.
An alternative approach in muscle fatigue evaluation from the surface EMG signal
2010
The aim of this study was to compare the intervals of time between adjacent zero crossings (ZCI), an alternative frequency-temporal parameter, with the root-mean-square (RMS) value and the median frequency (Fmed) from the surface EMG (sEMG) signal in muscle fatigue analysis. Twenty right-handed volunteers performed isometric contractions of right biceps brachii muscle while sEMG signals were collected from it at three different and arbitrary load levels until fatigue. The mean ZCI presented a significant correlation with Fmed but not with RMS value and it also presented lower coefficients of variation than others. The results pointed that mean ZCI properties can contribute more than Fmed and RMS value on the interpretation of the muscle function under fatigue conditions.
Journal of Electromyography and Kinesiology, 1997
The purpose of the current study was to determine the validity of quantifying biceps brachii fatigue with dynamic measures of surface electromyographic (EMG) mean power frequency (MPF) through comparisons with the well-established isometric methodology. Subjects performed repetitive elbow flexion<xtension movements with a hand held load of 7 kg until volitional exhaustion. Elbow joint angle and biceps brachii EMG signals were recorded continuously during the fatiguing movement (in 250-ms segments) and during isometric, isotonic contractions (in IOOO-ms segments) performed at a 90" flexion angle before and after the trial. The MPF and average EMG amplitude (AEMG) were also calculated with each sample, and a polynomial regression analysis was used to characterize the time history of changes and to determine the rested and fatigued values for the dynamic EMG with: (a) all dynamic samples above 5% MVC and (b) only samples where the elbow joint was between 80' and 100" of flexion. There was a significant increase in AEMG and a decrease in MPF for the isometric contractions and both dynamic methods. When compared to dynamic values at rest and fatigue, the isometric AEMG and MPF were substantially lower and slightly higher, respectively. No significant differences were observed between the AEMG or MPF results from the two methods of processing the dynamic EMG. The decreases in MPF ranged from 25% to 29% and did not differ between methods. The absolute and relative increases in isometric AEMG were substantially lower than with both dynamic methods. The current results support the use of MPF values from surface EMG signals recorded during dynamic contractions to quantify fatigue of the biceps brachii muscle. The proposed methodology can be used to monitor fatigue continuously throughout a dynamic movement with minimal disturbance to the task being performed and without the need to monitor joint angles. 0 1997 Elsevier Science Ltd.