The aim of this study was to compare the power output and fatigue properties of spatially distributed sequential stimulation (SDSS) against conventional single electrode stimulation (SES) in an isokinetic knee extension task simulating knee movement during recumbent cycling.
Although less stimulation was applied, the SDSS setup showed a significantly higher power output P
mean overall as well as during the final 20 extensions. The initial power output was not significantly different. Scaling the power output using pulse width, P
mean,s showed substantially larger differences and significance levels during the initial and final phases and overall, which highlights its significantly higher efficiency. The SDSS setup was significantly more fatigue resistant than the conventional SES stimulation setup.
Power output development
Looking at the time course of
P
mean (Fig.
3a), the highest power output produced in both setups was reached during the first ten extensions. The muscles are not yet fatigued and it can be assumed that
P
mean in the initial phase is the maximum possible tolerated power output for the corresponding electrode setup and muscle group (Bickel et al.
2011). Although subjects tolerated a higher pulse width during SES,
P
mean was lower, but not significantly, in the initial phase. All subjects used significantly lower pulse widths during SDSS and this might lead to the expectation of higher maximal power outputs for SES, given that an increasing pulse width usually corresponds to increased power output at a constant frequency (Baldwin et al.
2006; Gregory et al.
2007). Finding no significant differences during the initial extensions indicates that both setups recruit and activate, in sum, a similar number of motor units during one movement cycle (Hodson-Tole and Wakeling
2009).
Considering the power output development over the 6 min of stimulation, the two setups were performed completely in a different manner. With SES,
P
mean dropped by a third in the first 60 extensions and further decreased to 50% of the initial power output. In contrast,
P
mean decreased in the SDSS setup much more slowly during the first 60 extensions and flattened out towards the end of the stimulation phase at a level of about 66% of the initial
P
mean (Figs.
3a,
4). This better fatigue resistance confirms previous observations from Nguyen et al. (
2011), Sayenko et al. (
2014) and Popovic and Malesevic (
2009). With a group of healthy subjects, Sayenko et al. (
2014) observed bigger differences when focusing on the activation curve and the fatigue of the m. soleus. In contrast to those studies, the protocol used in the present study is three times longer and the m. quadriceps is stimulated during a concentric dynamic movement.
The separation of one large electrode with 35 Hz stimulation frequency into four small electrodes, each stimulating with a much lower frequency of 8.75 Hz per electrode, seems to have many benefits. The influence of stimulation frequency on fatigue has been investigated by many other investigators. It has been shown that low frequencies have lower ATP costs per contraction (Bergstrom and Hultman
1988; Fitts
1994), and thus are more efficient in binding cross-bridges. Additionally, an increase in inorganic phosphate and pH factors (Russ et al.
2002) and problems in Ca
2+ release at higher frequencies are factors that cause muscle fatigue (Westerblad et al.
1990,
2000). On the one hand, it can be held that increasing the frequency accentuates muscle fatigue while decreasing the frequency reduces muscle fatigue. On the other hand, the lower frequency is usually linked with a decrease in power output (Binder-Macleod and Guerin
1990; Chou et al.
2008; Chou and Binder-Macleod
2007; Dreibati et al.
2010; Gorgey et al.
2009; Kesar et al.
2008), which can be disadvantageous for functional tasks.
Based on previous publications (Nguyen et al.
2011; Sayenko et al.
2014), we expected a higher fatigue resistance, but not necessarily the significantly higher power output with the SDSS setup. Although lower pulse widths and lower frequencies were applied on a single SDSS electrode, all except two subjects showed a higher
P
mean in the initial phase with SDSS and just one of them stayed lower with SES in the final phase (Figs.
3b, c,
5a, b). Low pulse width combined with low frequencies is usually directly linked with a decreased power output (Baldwin et al.
2006; Gorgey et al.
2006,
2009), so the significant differences (viz. higher power output with SDSS) in our measurements can not be due only to frequency, but must result from the combination of the spatially and sequentially distributed electrodes. Sayenko et al. (
2014) found with EMG measurements partial activation of different parts of the stimulated muscle depending on the placement of the small electrodes. This supports the theory that different motor units are stimulated with the different sub-electrodes and they are allowed more time to recover between subsequent activations.
The low frequency of 8.75 Hz is sufficient to activate muscle fibres in the m. quadriceps (Fig.
3) but fibres activated around 10 Hz would not be expected to generate high forces (Roos et al.
1999; Wessberg and Kakuda
1999). So, how can the higher power output of the SDSS setup be explained? During voluntary contractions, force is increased by recruiting more motor units and increased cross-bridge bindings, based on increased firing rates (Bellemare et al.
1983; Roos et al.
1999; Rubinstein and Kamen
2005). Here, stimulation with SDSS leads to a higher current density on specific points on the muscle (Kuhn et al.
2010) but since the small electrodes are placed quite close to each other, the generated electrical field is assumed to be overlaid in some muscular parts, thus some motor neurons may still be stimulated at 35 Hz. This summation of different action potentials might be one mechanism to increase the number of cross-bridges and, accordingly, the produced force compared to the force produced by the lower density currents of the larger active electrode. The higher force might also be explained in part by increased intramuscular coordination with more and different motor units involved in the contraction cycle. The mechanism in SDSS whereby the electric field is changed constantly (phase shift together with the spatial shift) might activate other neural circuits, which again activate some other muscle parts in the same muscle group. This complementary activation of different parts of the stimulated muscle results in a stronger total muscle contraction and less fatigue (Fig.
3). This is comparable to a voluntary contraction, where neuromuscular circuits with motor unit inhibitions and low firing rates, together with phase shifts, provide smooth contractions (Broman et al.
1985; De Luca et al.
1982).
Methodology/scaling/electrode setting
A familiarisation session was used to define stimulation tolerance and parameters. Based on individual tolerance levels, soft tissue and muscle constitution, each subject and leg needs its own specific stimulation parameters (Keller and Kuhn
2008). It can be assumed that an approximately linear relationship exists between stimulation intensity and force production at moderate stimulation levels. By stimulating here at 80% of the individual tolerance level, the aim was to remain in this linear phase (Adam and De Luca
2003; Bickel et al.
2004; Hillegass and Dudley
1999). Our primary strategy in this study was to compare the two different electrode setups and we tried to change as few of the other parameters as possible to reduce confounding factors. The basic stimulation frequency was chosen here to be 35 Hz, which is known to be a good trade-off between fatigue resistance and force generation (Hunt et al.
2012). Changing pulse width and keeping pulse amplitude constant at 40 mA means that the difference in current density between SES and SDSS stayed the same for all subjects. It would have been possible to stimulate with lower amplitude and longer pulse widths, but since amplitude together with the electrode size is mainly responsible for the current density (Alon et al.
1994), it might have been that the more different reaction of the subjects to wide pulse width, high frequency stimulation as investigated by Wegrzyk et al. (
2015) would have influenced the results more than the different electrode setup (see low occurrence of responders (40%) in Wegrzyk et al. (
2015)). The maximal tolerable stimulation should be used but without influencing the movement. Post hoc, transferring the upper pain level to a numeric pain rating scale (1–10) (McCaffery and Beebe
1994), the familiarisation was stopped at the level of approximately 6–7 for each subject. The pain level during measurement would not have exceeded level 5 (moderate pain), which does not interfere with movement. This was asked during the measurement but without referring to a pain scale. Therefore, the generated power output in this study is always related to 80% of the maximal tolerated stimulation intensity. The lower mean pulse width found with the SDSS electrode configuration shows that this setup is generally more painful for able-bodied subjects. This is in line with previous observations by Kuhn et al. (
2010), where smaller electrodes caused more pain. The variation of pulse widths among the subjects reflects variations in soft tissue composition and pain tolerance.
The scaled power output takes account of the different pulse widths and normalises the stimulation intensity between the setups. Scaling the input pulse widths to a notional 100 µs highlights the differences between the two setups at equal inputs and provides values to compare the efficiency of the two setups. P
mean,s obtained with the SDSS electrode configuration showed substantially larger differences and significance levels during the initial and final phases and overall, which emphasises the higher efficiency of the SDSS setup compared to the SES configuration.
Nguyen et al. (
2011) and Sayenko et al. (
2014) used a symmetrical arrangement for the SDSS setup, where the electrodes covered exactly the same surface as in SES. In the present study, both setups covered the same skin area, but over a slightly different part of the stimulated muscle. SDSS electrode positioning was chosen dependent on the prior motor point (MP) detection and on the size and shape of the muscle (Fig.
1c). This is because the goal of the positioning was to be as close as possible to the MP and to cover the stimulating muscle as well as possible to optimise the power output (Gobbo et al.
2014; Maffiuletti
2010).
This study showed some major benefits of the SDSS setup compared to SES regarding fatigue resistance and power output but the study has some limitations which are discussed here. One limitation is that the measurements were conducted with able-bodied subjects, where the influence of volitional movement cannot be fully excluded. The stimulation intensity was based on subjective and individual pain tolerance, obtained informally from each subject for each leg and pattern during familiarisation. For better uniformity and comparability among the subjects, an established pain scale should be used in future studies. A further limitation is that, while the dynamometer provided a good basis for assessment of a dynamic knee extension task, it is still a simplification of a real cycling movement. The influence of hip flexion and the coordinated activation of the hamstrings were not considered in the dynamometer setup. The experimental setup used, together with the applied stimulation parameters, is just one possibility and the results obtained are strongly linked with these configurations. The influence of changing pulse width, amplitude and/or frequency in conjunction with specific electrode configurations is a further subject for future research studies.