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Muscular synchronization and hand-arm fatigue
International Journal of Industrial Ergonomics xxx (2016) 1e4
Contents lists available at ScienceDirect
International Journal of Industrial Ergonomics journal homepage: www.elsevier.com/locate/ergon
Muscular synchronization and hand-arm fatigue Luigi Fattorini a, Angelo Tirabasso b, Alessandro Lunghi b, Raoul Di Giovanni b, Floriana Sacco b, Enrico Marchetti a, b, * di Roma, Department of Physiology and Pharmacology “V. Erspamer”, P.le A. Moro 5, 00185, Roma, Italy Sapienza Universita National Institute for Insurance Against Accidents at Work (INAIL), Department of Environmental and Occupational Medicine, Epidemiology and Hygiene, Via di Fontana Candida 1, 00078, Monte Porzio Catone, Rome, Italy
a
b
a r t i c l e i n f o
a b s t r a c t
Article history: Received 28 January 2016 Received in revised form 6 June 2016 Accepted 29 July 2016 Available online xxx
Muscular fatigue occurs when motor units are no longer able to maintain an established force level. From an electromyographic point of view, fatigue is associated with a decrement of median frequency of contracting fibers. When the muscle is exposed to mechanical vibration, it undergoes a superimposition of voluntary contraction and stretch reflex, latter being synchronized to the mechanical frequency. The present paper is aimed to study the changes of muscular synchronization in long-lasting muscular tasks using a specific index change (DSL). Different frequencies of mechanical vibration (20, 30, 33, 40 Hz) and different levels of muscular task (20, 30, 40, 60% of the maximum) are studied by surface electromyography (sEMG) in prolonged exposures (t ¼ 45 s). Results show a prominence of muscular synchronization (i.e. DSL) for a combination of force-frequency values at 30% MVC - 33 Hz. This is consistent but not identical with the behavior of other sEMG indicators of muscular fatigue, such as median frequency decay (MDFd), as reported in literature, and suggesting that present results could better describe different aspects of the vibration stretch reflex. Using this knowledge may promote more effective vibrating tools for industry, oriented to reduce occupational fatigue. Since some force-frequency combination can stress the hand-arm system more than others, these results may help avoid work-related occupational injury. © 2016 Elsevier B.V. All rights reserved.
Keywords: Hand-arm vibration Muscular fatigue Synchronization Stimulation frequency Tonic vibration reflex
1. Introduction Hand-arm mechanical properties are responsible for transmissibility of vibration induced by externally powered tools maintained with the hand as sanders or drills. These occupational conditions are largely studied in order to prevent or minimize the occurrence of disease. On this regard, ISO standard frequency weighting curves (Wh) based on operator perception of mechanical vibration (MV) have been developed and are commonly used to define the hazard in occupational environments (UNI EN ISO 53491, 2004). In literature, several studies propose some changes to Wh in accordance with the use of special tools as breakers or rammers (Dong et al., 2005, 2006; Tominaga, 2005; Bovenzi, 2012). All those studies were based on a hand-arm purely passive mechanical
* Corresponding author. Via di Fontana Candida 1, 00078, Monte Porzio Catone, Rome, Italy. E-mail addresses: [email protected] (L. Fattorini), [email protected] (A. Tirabasso), [email protected] (A. Lunghi), [email protected] (R. Di Giovanni), fl[email protected] (F. Sacco), [email protected], [email protected] (E. Marchetti).
model of the interaction tool-biological system but it is well known that the biological system is time changing as far fatigue and muscular fine adjustment. Conversely, studying the surface electromyography (sEMG) of the forearm during 45 s long hand-grip task has shown a changing behavior of the hand arm system when elicited by MV (Fattorini et al., 2016). This response shows the relationship between muscular fatigue and stimulus parameters (frequency and grip force). This relationship conflicts with the passive model; indeed, it shows a sEMG power varying with MV frequency and a relative increasing muscular fatigue with time. Recently Dong (Dong et al., 2012) proposed a factorization of the weighting curve that keeps into account with two factors the biodynamic and the biological components. The neuromuscular synchronization could be proposed as a third component. For muscular fatigue assessments, from sEMG recordings, an index called Median Frequency decay (MDFd) is used that represents the decrease of the median frequency over time. This decay has been related to muscular fatigue (De Luca, 1984; Merletti and Parker, 2004); which showed a relative maximum of neuromuscular fatigue at a proper combination of MV force and frequency (i.e. the 30% of maximum and 33 Hz respectively) compared to the
http://dx.doi.org/10.1016/j.ergon.2016.07.009 0169-8141/© 2016 Elsevier B.V. All rights reserved.
Please cite this article in press as: Fattorini, L., et al., Muscular synchronization and hand-arm fatigue, International Journal of Industrial Ergonomics (2016), http://dx.doi.org/10.1016/j.ergon.2016.07.009
2
L. Fattorini et al. / International Journal of Industrial Ergonomics xxx (2016) 1e4
absence of MV using MDFd (Fattorini et al., 2016). They argued that this could be due to changes in articular stiffness induced by the muscular contraction. It is self-evident that in usual working conditions tools are handled for prolonged time, so the onset of muscular fatigue will be very likely. Moreover, as postulated in (Fattorini et al., 2005), muscular recruitment pattern would change if elicited by a MV for a long time. Studying the same phenomenon, Martin and Park (1997) proposed an index, derived from sEMG, to account for the quantity of muscular recruitment synchronized with MV: the normalized synchronization index (SL). This index is related to the sEMG power around MV frequency divided by the total sEMG power, and it takes into consideration that a repetitive stimulus may induce a neuromuscular response with similar frequency characteristics of MV. This is because the stimulus elicited a mono-synaptic loop from skin mechanoreceptors and muscular fibers, which is known in physiology as a reflex arc and in this particular case, as the Tonic Vibration Reflex (TVR). As stated above, (Fattorini et al., 2016) showed that the change of MDFd was a consequence of MV. The MDFd is the frequency that divides in two the EMG power spectrum and is a parameter that reveals the change in muscle recruitment pattern, but it is unfit to explain the reason of such changes. On the other hand, the SL is a parameter that is related to the muscular response to the MV only; and, although it is unsuitable to detect the muscular fatigue, it could reveal if muscle activation is modified by the MV. Thus, present study is aimed to assess the muscular response to MV over time (i.e. TVR changes) in prolonged hand-grip task with different MV frequencies. As a TVR index it will be used the SL index and, given its characteristics, it will be compared with other sEMG parameters present in literature. Present findings could be useful to characterize specific occupational situations that may induce an early muscular fatigue or a neuromuscular inefficiency and result in work injury. For this reason a standard experimental condition has been adopted similar to those met in the field. 2. Materials and methods 2.1. Experimental design The experimental setup has been shaped to assess the muscular activity, for a prolonged time, while the subject was exposed to mechanical vibration as he performed a specific motor task. This setup needed the standardization of multiple aspects, which are detailed in the following paragraphs. The general description of the setup is as follows: the subject had a given posture, typical of most working conditions, and was exposed to mechanical vibration of different given frequencies. He/ she had to hold posture and force level for the duration of the experiment. The sEMG signal of two muscles of the forearm was recorded for an extended duration of time, in order to acquire the signal of a fatiguing muscle. For each subject all measurements were performed on the same day, so it was needed and granted adequate rest-time between sessions. The study was conducted according to the declaration of Helsinki and followed the guidelines established by the ethics committee of the University Sapienza of Roma and the indications of INAIL. From the sEMG signal the difference of synchronization of the late motor task signal minus the early motor task signal (DSL) and the median frequency decay (MDFd) was analyzed.
weight 70 ± 11 kg, height 1.73 ± 0.08 m). None of the subjects had history of muscular or bone injuries, diseases, nor previous professional exposure to vibration. All subjects signed a preliminary informed consent to the experiment. 2.3. Vibration signals Mechanical vibration exposure was provided by a handle (first resonant frequency at 800 Hz) linked to the electrodynamic shaker (RMS SW 1508, Germany, EU). The shaker was driven by a controller (Vibration Research VR 7500-2, Germany, EU) at 20, 30, 33 and 40 Hz. The vibration control loop was closed by an accelerometer (PCB, 353M197, NY, USA) on the baseplate of the handle. The signal had a constant velocity amplitude of 27$103 ms1. The sequence of vibration imposed to the handle was randomly administered to each subject. 2.4. Motor task The motor task consisted of holding with the dominant hand (subjects' declaration) the instrumented handle at a preestablished force values for at least 45 s with a prefixed grip force. The handle had strain gauges for grip force measurement (Fig. 1). To measure both components of grip force (i.e. push and pull) the handle is divided in two halves, connected by bridged strain gauges. This configuration allowed, both, zeroing the Wheatstone bridge before every measurement and continuous checking of push and pull forces. Temperature and humidity conditions, having great influence over strain gauge response, were kept stable during measurements with air conditioning. The grip force exerted was expressed in terms of percentage of Maximum Voluntary Contraction (MVC). The MVC was the maximal force exerted on the handle over three repetitions, each lasting 5 s. The MVC value adopted was the highest of these reiterations. The force values requested during the motor tasks were 20e30e40e60 percent of MVC. Both components of grip force were continuously recorded and displayed to the subject by an oscilloscope (Hewlett & Packard, 54603B, CA, USA) to help maintain the given level of force and balancing between push and pull (see Fig. 1). Absolute grip forces (balancing push and pull) were in the range 220e800 N. After each measure the subject was given a rest period of 15e30 min, depending on the force exertion during the test. 2.5. Subject posture The subject's forearm was directed along the shaker axis defining the Z axis (Fig. 1). The elbow formed an angle of 90 , and did not to touch the body during the measurements. This posture was standardized following the (UNI EN ISO 10819, 1998) for glove testing. The subject was asked to stand upright, on an adjustable
2.2. Subjects Thirty-four experimental subjects have been selected from healthy volunteers: 16 females and 18 males (age 22 ± 5 years,
Fig. 1. Posture and experimental setup.
Please cite this article in press as: Fattorini, L., et al., Muscular synchronization and hand-arm fatigue, International Journal of Industrial Ergonomics (2016), http://dx.doi.org/10.1016/j.ergon.2016.07.009
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3
footboard that corrected for different subject's height. 2.6. Muscular activity assessment The muscular activity was assessed by sEMG of extensor carpi radialis longus (ECRL) and the flexor carpi ulnaris (FCU) muscles of the forearm. After preparation of the subject's skin, the positioning of electrodes, diameter 0.01 m, occurred on the belly of the selected muscles with an inter-electrodes distance of 0.02 m. Preparation and positioning was performed in accordance with SENIAM guidelines [http://www.seniam.org/]. All measurements on the same subject were done on the same day to prevent repositioning error of electrodes. The sEMG signal was acquired by Zero Wire (Cometa, Italy, EU) with a bandpass filter (10 Hze1 kHz) and sampled at 2 kHz. At last, EMG signals were transmitted and filtered with a 0.35 Hz high pass filter to a 16-bit digital analyzer OROS OR38 (Oros, France, EU). 2.7. Data analysis
Fig. 2. DSL related to vibration frequencies expressed in terms of grip force. Data are reported as mean and standard error.
Data analysis was performed off-line with ad-hoc applications developed with MatLab software, Release 2008a (Mathworks, Massachusets, USA). Firstly, the sEMG signal was digitally filtered with a band pass filter (10e350 Hz). Hence, the RMS was assessed. The SL values were computed as percentage of the ratio of the signal power around MV frequency (±2 Hz) and the total power of the whole filtered signal, as reported in (Martin and Park, 1997). The SL was worked out in 1 s windows on all 45 s duration in order to have the trend. The difference of synchronization index (DSL) was then computed, making the difference of the average of last 5 s of the tendency minus the average of first 5 s. 2.8. Statistical analysis Evaluation of data norms was performed using the Shapiro-Wilk test. A two-way repeated measures analysis of variance (ANOVA) was used to examine the change from all MV frequencies and between conditions (force exerted) for all parameters. When the twoway ANOVA showed a significant difference between conditions or over MV frequency, a post-hoc fisher's LSD analysis was used to compare the values (p < 0.05). Statistical computations were performed using SPSS software (v.11, 2001, SPSS Lead Technologies Inc., Chicago, IL, USA). 3. Results
DSL results are presented in two figures and one table. In Fig. 2 the DSL is reported as a histogram of the percentage in function of the mechanical frequency of stimulation, where different colors represent various grip force levels. It can be seen that, for all frequencies, the difference of synchronization increases with force, except for the 30% MVCe33 Hz value. Fig. 3 report the same data showing the tendency of each force level with varying frequency. Data at 40 Hz are more similar to each other, than between different force levels, than for all the other frequencies. There is even a coincidence of the values of 30% and 20%. ANOVA analysis (Table 1) highlight significant differences between 33 vs 40 Hz at 30% of force level. From Fig. 3, DSL behavior at MV 40 Hz reveals a sort of convergence for different forces. The statistical analysis confirmed this observation but for the external force value of 20% and 60%. Indeed, at this MV frequency only 20% of force resulted different from the 60% one. The remaining MV frequencies showed a greater variance (Table 1).
Fig. 3. DSL tendency of each force level (%) with varying frequency.
Table 1 Statistical analysis of synchronization differences between initial and late exposure stage. Exposure condition
Statistical significant
P value
20% 30% 40% 60% 20 Hz 20 Hz 20 Hz 20 Hz 30 Hz 30 Hz 30 Hz 33 Hz 33 Hz 33 Hz 40 Hz
Nothing 33 Hz vs 40 Hz 20 Hz vs 33 Hz 30 Hz vs 40 Hz 20% vs 40% 20% vs 60% 30% vs 40% 30% vs 60% 20% vs 60% 30% vs 60% 40% vs 60% 20% vs 30% 20% vs 60% 40% vs 60% 20% vs 60%
e 0.065 0.0375 0.053 <0.01 <0.001 <0.05 <0.01 <0.001 <0.01 <0.01 <0.05 <0.001 <0.05 <0.05
4. Discussion The majority of papers studying the relationship between handarm and vibrating tools considered hand-arm system (HAS) as a purely passive model, composed by spring, mass and dumper. Nevertheless, as pointed out in (Fattorini et al., 2016) the muscle is an active component capable to adjust to the elicitation. This active
Please cite this article in press as: Fattorini, L., et al., Muscular synchronization and hand-arm fatigue, International Journal of Industrial Ergonomics (2016), http://dx.doi.org/10.1016/j.ergon.2016.07.009
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role could be evaluated also by means of the Motor Units synchronization induced by external stimuli (Fattorini et al., 2005). Finally, present work was aimed to assess whether the time-related neuromuscular response accompanying MV during prolonged contractions is influenced by MV frequency or force exerted. Synchronization index difference (DSL) was adopted to measure this muscular response, because this parameter is related over time to the muscle perception of the mechanical stimulus. It is evident in Fig. 2 that the DSL increases with force, irrespective of stimulus frequency, except at 33 Hz. This result is expected due the greater is the force exerted and bigger will be the muscular activation. This increases the number of MUs available to synchronize with MV. It is noteworthy that the ratio of increment with force is different among various frequencies, as evidenced in Fig. 3. This fact is likely due to the nonlinear behavior of the active system (i.e. muscle), and it denies the adoption of pure passive models to study the HAS. Moreover, data represented in Fig. 3 show some peculiarities as diminished values manifest at 40 Hz of MV, and a higher relative value of DSL at 30% of MVC and 33 Hz of MV are present. In Fig. 3 ANOVA analysis revealed significant differences between 33 vs 40 Hz at 30% of force level. Moreover, present results show that MV at 33 Hz is the frequency that induce stronger effects on the neuromuscular control than other force-frequency combinations, this is in agreement with the literature (Marchetti et al., 2011). It is well known that in the range around 33 Hz there is one of the HAS resonances (Marchetti et al., 2007). This MV frequency, concurrent with a force of 30% MVC, was suggested to cause more muscular fatigue than others (Fattorini et al., 2016). From Fig. 3, it can be seen that at 40 Hz only 20% MVC resulted different from 60% MVC, whilst at other MV frequencies statistical analysis revealed additional differences (Table 1). In order to explain this result we need to recall the DSL meaning. SL is the parameter that quantifies the power of the signal synchronized with the MV over the total sEMG power (Martin and Park, 1997). In other words, SL is closely related with the amount of neuromuscular activation due solely to MV. As clearly stated in literature, a mechanical stimulus eliciting mechanical receptors located on the skin and on the tendons makes a reflex arc that can generate a forearm muscular contraction (Tonic Vibration Reflex) (Haghbart et al., 1976). Obviously, electrical muscular response and mechanical are spectrally coherent, with a coherence value in relationship with the transfer function of the biological system (i.e. mechanical € et al., 1976), and the DSL coupling) (Marchetti et al., 2011; Pyykko will represent the time related variations of this coupling. Hence, statistical results on MV at 40 Hz could be explained as a capability of the MV to guide the MUs, irrespective to the descending motor pattern needs to generate voluntary force or other physiological factors as fatigue. Conversely, Table 1 shows that for the other MV frequencies the force levels exerted were able to change the DSL. Consequently, it is possible to assert that for most of the MV frequencies investigated, the central motor drive needed to generate the force is able to modify the effects of MV on the monosynaptic reflex arc, but this is not observed at MV 40 Hz. Present findings are not totally in agreement with those the literature (Fattorini et al., 2016). Indeed, in similar experimental conditions these authors found a higher muscular time-related stress at 33 Hz than other frequencies. However, those authors made use of the sEMG median frequency that is a parameter closely related to the muscular fatigue (Merletti and Parker, 2004). For this
reason, present findings are novel and facilitate a better understanding of the MV influence on the HAS especially in industrial environments. 5. Conclusion This paper was aimed to evaluate the muscular behavior of the forearm in extended grip motor tasks, and in the presence of mechanical vibration as well as induced by vibrating tools. Previous papers studying the MV influence on fatigue reported that a higher stress is obtained when the subject performed a task with 30% MVC of force and 33 Hz as MV frequency. In the present paper using the trend of synchronized Motor Unit (DSL), those findings were partially confirmed. Indeed, statistical results showed that 33 Hz external mechanical vibration was able to modify the central motor pattern, but 40 Hz has proved to be an experimental condition capable to recruit the same MUs, irrespective to the force exerted. Finally, present findings add knowledge on muscular response to MV, and it can be effectively used to design professional tools. It will be the aim of a future study to verify the role of synchronization on muscular fatigue. References Bovenzi, M., 2012. Epidemiological evidence for new frequency weightings of handtransmitted vibrations. Ind. Health 50, 377e387. De Luca, C.J., 1984. Myoelectric manifestations of localized muscular fatigue in humans. Crit. Rev. Biomed. Eng. 11 (4), 251e279. Dong, R.G., Welcome, W.E., McDowell, T.W., Wu, J.Z., Schopper, A.V., 2006. Frequency weighting derived from power absorption of fingers-hand-arm system under zeaxis vibration. J. Biomech. 39, 2311e2324. Dong, R.G., Welcome, W.E., McDowell, T.W., Xu, X.S., Krajnak, K., Wu, J.Z., 2012. A proposed theory on biodynamic frequency weighting for hand-transmitted vibration exposure. Ind. Health 50, 412e424. Dong, R.G., Welcome, W.E., Wu, J.Z., 2005. Frequency weighting based on biodynamics of fingers-hand-arm system. Ind. Health 43, 516e526. Fattorini, L., Tirabasso, A., Lunghi, A., Di Giovanni, R., Sacco, F., Marchetti, E., 2016. Muscular forearm activation in hand-grip tasks with superimposition of mechanical vibrations. J. Electromyogr. Kinesiol. 26, 143e148. http://dx.doi.org/ 10.1016/j.jelekin.2015.10.015. Fattorini, L., Felici, F., Filligoi, G.C., Traballesi, M., Farina, D., 2005. Influence of high motor unit synchronization levels on non-linear and spectral variables of the surface EMG. J. Neurosci. Methods 143 (2), 133e139. Haghbart, K.E., Burke, D., Wallin, G., Lofstedt, L., 1976. Single unit spindle responses to muscle vibration in man. Prog. Brain Res. 44, 281e289. Marchetti E, Lunghi A, Fattorini L, Nataletti P, Morgia F. Difference between men and women in hand-transmitted vibration power absorption. 2007, 11th International Conference on Hand Arm Vibration, Bologna. Marchetti, E., Morgia, F., Filligoi, G., Lunghi, A., Fattorini, L., 2011. VPA-based weighting curve: preliminary assessment of gender difference. Can. Acoust. 39 (2), 100e101. Martin, B.J., Park, H.S., 1997. Analysis of the tonic vibration reflex: influence of vibration variables on motor unit synchronization and fatigue. Eur. J. Appl. Physiol. 75 (6), 504e511. Merletti, F., Parker, P.A., 2004. Electromyography. Physiology, Engineering and Non Invasive Applications. IEEE Press & John Wiley & Sons, New Jersey. € , I., Fa €rkkila €, M., Toivanen, J., Korhonen, O., Hyva €rinen, J., 1976. Transmission Pyykko of vibration in the hand-arm system with special reference to changes in compression force and acceleration. Scand. J. Work Environ. Health 2 (2), 87e95. SENIAM Guidelines. http://www.seniam.org/. Tominaga, Y., 2005. New frequency weighting of hand-arm vibration. Ind. Health 43, 503e515. UNI EN ISO 10819, 1998. Mechanical Vibration and Shock. Method for the Measurement and Evaluation of the Vibration Transmissibility of Gloves at the Palm of the Hand. UNI-Ente Nazionale Italiano di Unificazione, Milano. UNI EN ISO 5349-1, 2004. Mechanical Vibration. Measurement and Evaluation of Human Exposure to Hand-transmitted Vibration Part 1: General Requirements. UNI-Ente Nazionale Italiano di Unificazione, Milano.
Please cite this article in press as: Fattorini, L., et al., Muscular synchronization and hand-arm fatigue, International Journal of Industrial Ergonomics (2016), http://dx.doi.org/10.1016/j.ergon.2016.07.009
Contents lists available at ScienceDirect
International Journal of Industrial Ergonomics journal homepage: www.elsevier.com/locate/ergon
Muscular synchronization and hand-arm fatigue Luigi Fattorini a, Angelo Tirabasso b, Alessandro Lunghi b, Raoul Di Giovanni b, Floriana Sacco b, Enrico Marchetti a, b, * di Roma, Department of Physiology and Pharmacology “V. Erspamer”, P.le A. Moro 5, 00185, Roma, Italy Sapienza Universita National Institute for Insurance Against Accidents at Work (INAIL), Department of Environmental and Occupational Medicine, Epidemiology and Hygiene, Via di Fontana Candida 1, 00078, Monte Porzio Catone, Rome, Italy
a
b
a r t i c l e i n f o
a b s t r a c t
Article history: Received 28 January 2016 Received in revised form 6 June 2016 Accepted 29 July 2016 Available online xxx
Muscular fatigue occurs when motor units are no longer able to maintain an established force level. From an electromyographic point of view, fatigue is associated with a decrement of median frequency of contracting fibers. When the muscle is exposed to mechanical vibration, it undergoes a superimposition of voluntary contraction and stretch reflex, latter being synchronized to the mechanical frequency. The present paper is aimed to study the changes of muscular synchronization in long-lasting muscular tasks using a specific index change (DSL). Different frequencies of mechanical vibration (20, 30, 33, 40 Hz) and different levels of muscular task (20, 30, 40, 60% of the maximum) are studied by surface electromyography (sEMG) in prolonged exposures (t ¼ 45 s). Results show a prominence of muscular synchronization (i.e. DSL) for a combination of force-frequency values at 30% MVC - 33 Hz. This is consistent but not identical with the behavior of other sEMG indicators of muscular fatigue, such as median frequency decay (MDFd), as reported in literature, and suggesting that present results could better describe different aspects of the vibration stretch reflex. Using this knowledge may promote more effective vibrating tools for industry, oriented to reduce occupational fatigue. Since some force-frequency combination can stress the hand-arm system more than others, these results may help avoid work-related occupational injury. © 2016 Elsevier B.V. All rights reserved.
Keywords: Hand-arm vibration Muscular fatigue Synchronization Stimulation frequency Tonic vibration reflex
1. Introduction Hand-arm mechanical properties are responsible for transmissibility of vibration induced by externally powered tools maintained with the hand as sanders or drills. These occupational conditions are largely studied in order to prevent or minimize the occurrence of disease. On this regard, ISO standard frequency weighting curves (Wh) based on operator perception of mechanical vibration (MV) have been developed and are commonly used to define the hazard in occupational environments (UNI EN ISO 53491, 2004). In literature, several studies propose some changes to Wh in accordance with the use of special tools as breakers or rammers (Dong et al., 2005, 2006; Tominaga, 2005; Bovenzi, 2012). All those studies were based on a hand-arm purely passive mechanical
* Corresponding author. Via di Fontana Candida 1, 00078, Monte Porzio Catone, Rome, Italy. E-mail addresses: [email protected] (L. Fattorini), [email protected] (A. Tirabasso), [email protected] (A. Lunghi), [email protected] (R. Di Giovanni), fl[email protected] (F. Sacco), [email protected], [email protected] (E. Marchetti).
model of the interaction tool-biological system but it is well known that the biological system is time changing as far fatigue and muscular fine adjustment. Conversely, studying the surface electromyography (sEMG) of the forearm during 45 s long hand-grip task has shown a changing behavior of the hand arm system when elicited by MV (Fattorini et al., 2016). This response shows the relationship between muscular fatigue and stimulus parameters (frequency and grip force). This relationship conflicts with the passive model; indeed, it shows a sEMG power varying with MV frequency and a relative increasing muscular fatigue with time. Recently Dong (Dong et al., 2012) proposed a factorization of the weighting curve that keeps into account with two factors the biodynamic and the biological components. The neuromuscular synchronization could be proposed as a third component. For muscular fatigue assessments, from sEMG recordings, an index called Median Frequency decay (MDFd) is used that represents the decrease of the median frequency over time. This decay has been related to muscular fatigue (De Luca, 1984; Merletti and Parker, 2004); which showed a relative maximum of neuromuscular fatigue at a proper combination of MV force and frequency (i.e. the 30% of maximum and 33 Hz respectively) compared to the
http://dx.doi.org/10.1016/j.ergon.2016.07.009 0169-8141/© 2016 Elsevier B.V. All rights reserved.
Please cite this article in press as: Fattorini, L., et al., Muscular synchronization and hand-arm fatigue, International Journal of Industrial Ergonomics (2016), http://dx.doi.org/10.1016/j.ergon.2016.07.009
2
L. Fattorini et al. / International Journal of Industrial Ergonomics xxx (2016) 1e4
absence of MV using MDFd (Fattorini et al., 2016). They argued that this could be due to changes in articular stiffness induced by the muscular contraction. It is self-evident that in usual working conditions tools are handled for prolonged time, so the onset of muscular fatigue will be very likely. Moreover, as postulated in (Fattorini et al., 2005), muscular recruitment pattern would change if elicited by a MV for a long time. Studying the same phenomenon, Martin and Park (1997) proposed an index, derived from sEMG, to account for the quantity of muscular recruitment synchronized with MV: the normalized synchronization index (SL). This index is related to the sEMG power around MV frequency divided by the total sEMG power, and it takes into consideration that a repetitive stimulus may induce a neuromuscular response with similar frequency characteristics of MV. This is because the stimulus elicited a mono-synaptic loop from skin mechanoreceptors and muscular fibers, which is known in physiology as a reflex arc and in this particular case, as the Tonic Vibration Reflex (TVR). As stated above, (Fattorini et al., 2016) showed that the change of MDFd was a consequence of MV. The MDFd is the frequency that divides in two the EMG power spectrum and is a parameter that reveals the change in muscle recruitment pattern, but it is unfit to explain the reason of such changes. On the other hand, the SL is a parameter that is related to the muscular response to the MV only; and, although it is unsuitable to detect the muscular fatigue, it could reveal if muscle activation is modified by the MV. Thus, present study is aimed to assess the muscular response to MV over time (i.e. TVR changes) in prolonged hand-grip task with different MV frequencies. As a TVR index it will be used the SL index and, given its characteristics, it will be compared with other sEMG parameters present in literature. Present findings could be useful to characterize specific occupational situations that may induce an early muscular fatigue or a neuromuscular inefficiency and result in work injury. For this reason a standard experimental condition has been adopted similar to those met in the field. 2. Materials and methods 2.1. Experimental design The experimental setup has been shaped to assess the muscular activity, for a prolonged time, while the subject was exposed to mechanical vibration as he performed a specific motor task. This setup needed the standardization of multiple aspects, which are detailed in the following paragraphs. The general description of the setup is as follows: the subject had a given posture, typical of most working conditions, and was exposed to mechanical vibration of different given frequencies. He/ she had to hold posture and force level for the duration of the experiment. The sEMG signal of two muscles of the forearm was recorded for an extended duration of time, in order to acquire the signal of a fatiguing muscle. For each subject all measurements were performed on the same day, so it was needed and granted adequate rest-time between sessions. The study was conducted according to the declaration of Helsinki and followed the guidelines established by the ethics committee of the University Sapienza of Roma and the indications of INAIL. From the sEMG signal the difference of synchronization of the late motor task signal minus the early motor task signal (DSL) and the median frequency decay (MDFd) was analyzed.
weight 70 ± 11 kg, height 1.73 ± 0.08 m). None of the subjects had history of muscular or bone injuries, diseases, nor previous professional exposure to vibration. All subjects signed a preliminary informed consent to the experiment. 2.3. Vibration signals Mechanical vibration exposure was provided by a handle (first resonant frequency at 800 Hz) linked to the electrodynamic shaker (RMS SW 1508, Germany, EU). The shaker was driven by a controller (Vibration Research VR 7500-2, Germany, EU) at 20, 30, 33 and 40 Hz. The vibration control loop was closed by an accelerometer (PCB, 353M197, NY, USA) on the baseplate of the handle. The signal had a constant velocity amplitude of 27$103 ms1. The sequence of vibration imposed to the handle was randomly administered to each subject. 2.4. Motor task The motor task consisted of holding with the dominant hand (subjects' declaration) the instrumented handle at a preestablished force values for at least 45 s with a prefixed grip force. The handle had strain gauges for grip force measurement (Fig. 1). To measure both components of grip force (i.e. push and pull) the handle is divided in two halves, connected by bridged strain gauges. This configuration allowed, both, zeroing the Wheatstone bridge before every measurement and continuous checking of push and pull forces. Temperature and humidity conditions, having great influence over strain gauge response, were kept stable during measurements with air conditioning. The grip force exerted was expressed in terms of percentage of Maximum Voluntary Contraction (MVC). The MVC was the maximal force exerted on the handle over three repetitions, each lasting 5 s. The MVC value adopted was the highest of these reiterations. The force values requested during the motor tasks were 20e30e40e60 percent of MVC. Both components of grip force were continuously recorded and displayed to the subject by an oscilloscope (Hewlett & Packard, 54603B, CA, USA) to help maintain the given level of force and balancing between push and pull (see Fig. 1). Absolute grip forces (balancing push and pull) were in the range 220e800 N. After each measure the subject was given a rest period of 15e30 min, depending on the force exertion during the test. 2.5. Subject posture The subject's forearm was directed along the shaker axis defining the Z axis (Fig. 1). The elbow formed an angle of 90 , and did not to touch the body during the measurements. This posture was standardized following the (UNI EN ISO 10819, 1998) for glove testing. The subject was asked to stand upright, on an adjustable
2.2. Subjects Thirty-four experimental subjects have been selected from healthy volunteers: 16 females and 18 males (age 22 ± 5 years,
Fig. 1. Posture and experimental setup.
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footboard that corrected for different subject's height. 2.6. Muscular activity assessment The muscular activity was assessed by sEMG of extensor carpi radialis longus (ECRL) and the flexor carpi ulnaris (FCU) muscles of the forearm. After preparation of the subject's skin, the positioning of electrodes, diameter 0.01 m, occurred on the belly of the selected muscles with an inter-electrodes distance of 0.02 m. Preparation and positioning was performed in accordance with SENIAM guidelines [http://www.seniam.org/]. All measurements on the same subject were done on the same day to prevent repositioning error of electrodes. The sEMG signal was acquired by Zero Wire (Cometa, Italy, EU) with a bandpass filter (10 Hze1 kHz) and sampled at 2 kHz. At last, EMG signals were transmitted and filtered with a 0.35 Hz high pass filter to a 16-bit digital analyzer OROS OR38 (Oros, France, EU). 2.7. Data analysis
Fig. 2. DSL related to vibration frequencies expressed in terms of grip force. Data are reported as mean and standard error.
Data analysis was performed off-line with ad-hoc applications developed with MatLab software, Release 2008a (Mathworks, Massachusets, USA). Firstly, the sEMG signal was digitally filtered with a band pass filter (10e350 Hz). Hence, the RMS was assessed. The SL values were computed as percentage of the ratio of the signal power around MV frequency (±2 Hz) and the total power of the whole filtered signal, as reported in (Martin and Park, 1997). The SL was worked out in 1 s windows on all 45 s duration in order to have the trend. The difference of synchronization index (DSL) was then computed, making the difference of the average of last 5 s of the tendency minus the average of first 5 s. 2.8. Statistical analysis Evaluation of data norms was performed using the Shapiro-Wilk test. A two-way repeated measures analysis of variance (ANOVA) was used to examine the change from all MV frequencies and between conditions (force exerted) for all parameters. When the twoway ANOVA showed a significant difference between conditions or over MV frequency, a post-hoc fisher's LSD analysis was used to compare the values (p < 0.05). Statistical computations were performed using SPSS software (v.11, 2001, SPSS Lead Technologies Inc., Chicago, IL, USA). 3. Results
DSL results are presented in two figures and one table. In Fig. 2 the DSL is reported as a histogram of the percentage in function of the mechanical frequency of stimulation, where different colors represent various grip force levels. It can be seen that, for all frequencies, the difference of synchronization increases with force, except for the 30% MVCe33 Hz value. Fig. 3 report the same data showing the tendency of each force level with varying frequency. Data at 40 Hz are more similar to each other, than between different force levels, than for all the other frequencies. There is even a coincidence of the values of 30% and 20%. ANOVA analysis (Table 1) highlight significant differences between 33 vs 40 Hz at 30% of force level. From Fig. 3, DSL behavior at MV 40 Hz reveals a sort of convergence for different forces. The statistical analysis confirmed this observation but for the external force value of 20% and 60%. Indeed, at this MV frequency only 20% of force resulted different from the 60% one. The remaining MV frequencies showed a greater variance (Table 1).
Fig. 3. DSL tendency of each force level (%) with varying frequency.
Table 1 Statistical analysis of synchronization differences between initial and late exposure stage. Exposure condition
Statistical significant
P value
20% 30% 40% 60% 20 Hz 20 Hz 20 Hz 20 Hz 30 Hz 30 Hz 30 Hz 33 Hz 33 Hz 33 Hz 40 Hz
Nothing 33 Hz vs 40 Hz 20 Hz vs 33 Hz 30 Hz vs 40 Hz 20% vs 40% 20% vs 60% 30% vs 40% 30% vs 60% 20% vs 60% 30% vs 60% 40% vs 60% 20% vs 30% 20% vs 60% 40% vs 60% 20% vs 60%
e 0.065 0.0375 0.053 <0.01 <0.001 <0.05 <0.01 <0.001 <0.01 <0.01 <0.05 <0.001 <0.05 <0.05
4. Discussion The majority of papers studying the relationship between handarm and vibrating tools considered hand-arm system (HAS) as a purely passive model, composed by spring, mass and dumper. Nevertheless, as pointed out in (Fattorini et al., 2016) the muscle is an active component capable to adjust to the elicitation. This active
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role could be evaluated also by means of the Motor Units synchronization induced by external stimuli (Fattorini et al., 2005). Finally, present work was aimed to assess whether the time-related neuromuscular response accompanying MV during prolonged contractions is influenced by MV frequency or force exerted. Synchronization index difference (DSL) was adopted to measure this muscular response, because this parameter is related over time to the muscle perception of the mechanical stimulus. It is evident in Fig. 2 that the DSL increases with force, irrespective of stimulus frequency, except at 33 Hz. This result is expected due the greater is the force exerted and bigger will be the muscular activation. This increases the number of MUs available to synchronize with MV. It is noteworthy that the ratio of increment with force is different among various frequencies, as evidenced in Fig. 3. This fact is likely due to the nonlinear behavior of the active system (i.e. muscle), and it denies the adoption of pure passive models to study the HAS. Moreover, data represented in Fig. 3 show some peculiarities as diminished values manifest at 40 Hz of MV, and a higher relative value of DSL at 30% of MVC and 33 Hz of MV are present. In Fig. 3 ANOVA analysis revealed significant differences between 33 vs 40 Hz at 30% of force level. Moreover, present results show that MV at 33 Hz is the frequency that induce stronger effects on the neuromuscular control than other force-frequency combinations, this is in agreement with the literature (Marchetti et al., 2011). It is well known that in the range around 33 Hz there is one of the HAS resonances (Marchetti et al., 2007). This MV frequency, concurrent with a force of 30% MVC, was suggested to cause more muscular fatigue than others (Fattorini et al., 2016). From Fig. 3, it can be seen that at 40 Hz only 20% MVC resulted different from 60% MVC, whilst at other MV frequencies statistical analysis revealed additional differences (Table 1). In order to explain this result we need to recall the DSL meaning. SL is the parameter that quantifies the power of the signal synchronized with the MV over the total sEMG power (Martin and Park, 1997). In other words, SL is closely related with the amount of neuromuscular activation due solely to MV. As clearly stated in literature, a mechanical stimulus eliciting mechanical receptors located on the skin and on the tendons makes a reflex arc that can generate a forearm muscular contraction (Tonic Vibration Reflex) (Haghbart et al., 1976). Obviously, electrical muscular response and mechanical are spectrally coherent, with a coherence value in relationship with the transfer function of the biological system (i.e. mechanical € et al., 1976), and the DSL coupling) (Marchetti et al., 2011; Pyykko will represent the time related variations of this coupling. Hence, statistical results on MV at 40 Hz could be explained as a capability of the MV to guide the MUs, irrespective to the descending motor pattern needs to generate voluntary force or other physiological factors as fatigue. Conversely, Table 1 shows that for the other MV frequencies the force levels exerted were able to change the DSL. Consequently, it is possible to assert that for most of the MV frequencies investigated, the central motor drive needed to generate the force is able to modify the effects of MV on the monosynaptic reflex arc, but this is not observed at MV 40 Hz. Present findings are not totally in agreement with those the literature (Fattorini et al., 2016). Indeed, in similar experimental conditions these authors found a higher muscular time-related stress at 33 Hz than other frequencies. However, those authors made use of the sEMG median frequency that is a parameter closely related to the muscular fatigue (Merletti and Parker, 2004). For this
reason, present findings are novel and facilitate a better understanding of the MV influence on the HAS especially in industrial environments. 5. Conclusion This paper was aimed to evaluate the muscular behavior of the forearm in extended grip motor tasks, and in the presence of mechanical vibration as well as induced by vibrating tools. Previous papers studying the MV influence on fatigue reported that a higher stress is obtained when the subject performed a task with 30% MVC of force and 33 Hz as MV frequency. In the present paper using the trend of synchronized Motor Unit (DSL), those findings were partially confirmed. Indeed, statistical results showed that 33 Hz external mechanical vibration was able to modify the central motor pattern, but 40 Hz has proved to be an experimental condition capable to recruit the same MUs, irrespective to the force exerted. Finally, present findings add knowledge on muscular response to MV, and it can be effectively used to design professional tools. It will be the aim of a future study to verify the role of synchronization on muscular fatigue. References Bovenzi, M., 2012. Epidemiological evidence for new frequency weightings of handtransmitted vibrations. Ind. Health 50, 377e387. De Luca, C.J., 1984. Myoelectric manifestations of localized muscular fatigue in humans. Crit. Rev. Biomed. Eng. 11 (4), 251e279. Dong, R.G., Welcome, W.E., McDowell, T.W., Wu, J.Z., Schopper, A.V., 2006. Frequency weighting derived from power absorption of fingers-hand-arm system under zeaxis vibration. J. Biomech. 39, 2311e2324. Dong, R.G., Welcome, W.E., McDowell, T.W., Xu, X.S., Krajnak, K., Wu, J.Z., 2012. A proposed theory on biodynamic frequency weighting for hand-transmitted vibration exposure. Ind. Health 50, 412e424. Dong, R.G., Welcome, W.E., Wu, J.Z., 2005. Frequency weighting based on biodynamics of fingers-hand-arm system. Ind. Health 43, 516e526. Fattorini, L., Tirabasso, A., Lunghi, A., Di Giovanni, R., Sacco, F., Marchetti, E., 2016. Muscular forearm activation in hand-grip tasks with superimposition of mechanical vibrations. J. Electromyogr. Kinesiol. 26, 143e148. http://dx.doi.org/ 10.1016/j.jelekin.2015.10.015. Fattorini, L., Felici, F., Filligoi, G.C., Traballesi, M., Farina, D., 2005. Influence of high motor unit synchronization levels on non-linear and spectral variables of the surface EMG. J. Neurosci. Methods 143 (2), 133e139. Haghbart, K.E., Burke, D., Wallin, G., Lofstedt, L., 1976. Single unit spindle responses to muscle vibration in man. Prog. Brain Res. 44, 281e289. Marchetti E, Lunghi A, Fattorini L, Nataletti P, Morgia F. Difference between men and women in hand-transmitted vibration power absorption. 2007, 11th International Conference on Hand Arm Vibration, Bologna. Marchetti, E., Morgia, F., Filligoi, G., Lunghi, A., Fattorini, L., 2011. VPA-based weighting curve: preliminary assessment of gender difference. Can. Acoust. 39 (2), 100e101. Martin, B.J., Park, H.S., 1997. Analysis of the tonic vibration reflex: influence of vibration variables on motor unit synchronization and fatigue. Eur. J. Appl. Physiol. 75 (6), 504e511. Merletti, F., Parker, P.A., 2004. Electromyography. Physiology, Engineering and Non Invasive Applications. IEEE Press & John Wiley & Sons, New Jersey. € , I., Fa €rkkila €, M., Toivanen, J., Korhonen, O., Hyva €rinen, J., 1976. Transmission Pyykko of vibration in the hand-arm system with special reference to changes in compression force and acceleration. Scand. J. Work Environ. Health 2 (2), 87e95. SENIAM Guidelines. http://www.seniam.org/. Tominaga, Y., 2005. New frequency weighting of hand-arm vibration. Ind. Health 43, 503e515. UNI EN ISO 10819, 1998. Mechanical Vibration and Shock. Method for the Measurement and Evaluation of the Vibration Transmissibility of Gloves at the Palm of the Hand. UNI-Ente Nazionale Italiano di Unificazione, Milano. UNI EN ISO 5349-1, 2004. Mechanical Vibration. Measurement and Evaluation of Human Exposure to Hand-transmitted Vibration Part 1: General Requirements. UNI-Ente Nazionale Italiano di Unificazione, Milano.
Please cite this article in press as: Fattorini, L., et al., Muscular synchronization and hand-arm fatigue, International Journal of Industrial Ergonomics (2016), http://dx.doi.org/10.1016/j.ergon.2016.07.009