Multiple motor point stimulation increases tetanic knee torque versus conventional single- electrode functional electrical stimulation: implications for functional output and neurorehabilitation

doi:10.21203/rs.3.rs-7782510/v1

Download PDF

Research Article

Multiple motor point stimulation increases tetanic knee torque versus conventional single- electrode functional electrical stimulation: implications for functional output and neurorehabilitation

https://doi.org/10.21203/rs.3.rs-7782510/v1

This work is licensed under a CC BY 4.0 License

You are reading this latest preprint version

Background

Functional electrical stimulation (FES) delivers transcutaneous electrical current to motor nerves to artificially evoke muscle contractions and produce joint torque. In neurorehabilitation, FES is commonly applied via a large surface electrode pair placed over a muscle group – an approach that we here refer to as single-electrode stimulation (SES). However, the torque-generating capacity of SES is limited. Targeting specific regions of high electrical excitability, or motor points, may enhance neuromuscular activation and increase joint torque output. Here we tested whether continuous multiple motor point stimulation (mMPS) increases tetanic knee torque compared with SES in the quadriceps and hamstrings. We also quantified quadriceps recruitment overlap as a secondary aim. We evaluated quadriceps and hamstring responses to mMPS and SES in neurologically intact participants, recording tetanic knee torque and assessing recruitment overlap relative to maximal voluntary contraction (MVC).

Results

Stimulating all quadriceps motor points produced approximately 51% greater knee extension torque than SES (33.3% MVC vs. 22.1% MVC). In contrast, stimulating all hamstring motor points did not significantly increase knee flexion torque. Within the quadriceps, proximal and intermediate vastus lateralis motor points contributed the most to knee extension torque, whereas the distal motor point had no significant effect. Discrepancies between observed and predicted MPS torques were primarily associated with rectus femoris stimulation, while vastus medialis contributed the least.

Conclusions

Stimulation of all quadriceps motor points generated 51% greater knee extension torque compared with conventional SES, highlighting the potential of mMPS to improve the effectiveness of FES interventions. Optimization of motor point selection should emphasize proximal and intermediate vastus lateralis sites, while also including vastus medialis. Rectus femoris stimulation should be considered only when channel allocation permits and when the torque benefit outweighs redundancy. In contrast, hamstring stimulation did not yield additional knee flexion torque underscoring muscle-specific limitations. These findings provide practical guidance for electrode placement and channel allocation, suggesting that optimal quadriceps stimulation can be achieved by prioritizing a limited subset of motor points.

functional electrical stimulation

hamstrings

motor point

neuromuscular electrical stimulation

neurorehabilitation

orthotic

quadriceps

spinal cord injury

tetanic

torque

Functional electrical stimulation (FES) is a clinically established neurorehabilitation intervention that delivers transcutaneous electrical currents to skeletal muscles, inducing controlled artificial contractions without the need of voluntary command (1, 2). FES has been applied to improve local and systemic outputs, including cardiorespiratory fitness (3), mitigation of muscle degeneration (4, 5), and the restoration of functional movements such as walking and standing (6–8). Exercise-based modalities such as FES-rowing and FES-cycling leverage the torque-generating capacity of FES to enable aerobic activity (9, 10). The torque produced during FES has been found to be partially influenced by extrinsic parameters governing stimulation delivery, including the spatial configuration and positioning of electrodes, which collectively affect both the quality and quantity of the resulting muscular contractions (11–15).

Conventional FES protocols typically adopt a large electrode pair positioned across a muscle compartment in a generalized configuration. In this study, we refer to this method as single-electrode stimulation (SES), which tends to recruit motor units under the electrodes in a nonspecific and spatially fixed manner. As a result, SES typically produces reduced muscle activation compared to activation of the nerve trunk (i.e., peripheral nerve stimulation) suggesting that SES activates only a limited portion of the muscle (16, 17). Neurophysiological (18) and imaging (19, 20) studies further confirm that SES activates restricted muscle regions compared to peripheral nerve stimulation or voluntary contractions. Such limitations may impair functional performance and reduce clinical utility, especially at higher stimulation intensities. These constraints highlight the need for more targeted stimulation strategies that can optimize motor unit recruitment across the muscle compartment.

Targeting a muscle’s motor point offers a more specific and potentially more effective alternative to SES. Motor point stimulation (MPS) delivers current directly to topographically identified regions of highest electrical excitability of the muscle, engaging neuromuscular pathways more efficiently than SES. Our previous work in the soleus muscle demonstrated that MPS predominantly activates motor nerves and produces activation levels comparable to peripheral nerve stimulation, suggesting more complete recruitment of the muscle (21–23). Beyond the soleus, MPS has been examined in animal preparations (24, 25), in able-bodied individuals (13, 26), and in neurological populations (27–29), supporting its feasibility across models and clinical contexts. To date, only one study has directly compared MPS with SES. Gobbo et al. (30) evaluated the tibialis anterior and vastus lateralis and showed that torque evoked by a single MPS site exceeded that of SES. In line with these findings, two review papers have concluded that MPS is advantageous for rehabilitation applications, where greater torque generation and improved performance are critical (31, 32). Nevertheless, MPS remains underutilized in clinical practice, in part due to the lack of systematic guidance on which motor points to target within specific muscle groups. This issue is particularly critical in the thigh, a primary site for FES-based exercise therapies (9, 33–35), where uncertainty over motor point selection limits therapeutic optimization.

Topographical mapping studies have identified multiple motor points within the anterior and posterior thigh (~ 7 in the quadriceps; ~4 in the hamstrings) (12, 36, 37), indicating that several distinct sites may serve as targets for evoking torques through MPS at the knee. We previously evaluated this concept at the twitch level by systematically testing all combinations of quadriceps motor points and found that activating all sites produced the greatest twitch torque, with the vastus lateralis contributing disproportionately (13). These findings highlight the potential of motor point stimulation, but functional FES requires continuous activation to generate fused, tetanic contractions. Thus, it remains unclear whether the advantages observed at the twitch level persist under tetanic multiple motor point stimulation (mMPS), and how interactions among individual motor points influence overall torque output. Addressing this gap is critical for optimizing electrode placement and channel allocation in motor point-based FES protocols.

Therefore, the purpose of this study was to systematically evaluate the tetanic torque-generating capacity of continuous mMPS applied to multiple motor points in the quadriceps and hamstrings, and to compare these outputs with SES. A secondary aim was to quantify recruitment overlap under mMPS in the quadriceps femoris muscles by contrasting observed torques with predicted values, in order to distinguish unique from redundant contributions and thereby guide electrode placement.

Maximal voluntary contraction knee torque

There was no difference in MVC_post compared to MVC_pre following all quadricep (Wilcoxon signed-rank test: mean change = 5.73 ± 17.11; Z = 0.646, p = 0.519, r = 0.186) and hamstring (mean change = -1.21 ± 4.49 ; t(11) = -0.93, p = 0.371, d_z = 0.269) FES conditions, suggesting that the stimulation protocols did not induce measurable fatigue and was not needed to be considered for subsequent analysis.

Knee torque between motor point and single-electrode stimulation conditions

Group data for normalized iMPS, mMPS, and SES_quads mean peak knee extension torques are summarized in Fig. 2A. Comparison between iMPS and mMPS conditions relative to SES_quads revealed a significant main effect of stimulation (F(14, 153) = 37.67, p < 0.001, η²ₚ = 0.529). Post hoc pairwise comparisons using Dunnett’s test revealed all iMPS conditions (VM_d, VM_p, RF_d, RF_p, VL_d, VL_i, VL_p) (t(11) = -5.96 to -4.10, all p < 0.001, all d_z = -3.66 to -0.27) and one mMPS condition (VM) (t(11) = -3.95, p = 0.001, d_z = -2.20) produced less knee extension torque than SES_quads. Knee extension torque produced during single-muscle (RF, VL) and paired-muscle (VM + RF, VM + VL, RF + VL) stimulation conditions did not differ significantly compared to SES_quads (all p > 0.10, d_z = -0.074 to 0.595). In contrast, ALL_quads produced greater torque than SES_quads in 92% (11/12) of participants. Across all participants, ALL_quads yielded 50.8% (range: -17.5% to 208.6%) more knee extension torque compared to SES_quads (mean: 33.3% MVC vs. 22.1% MVC; t(11) = 3.68, p = 0.004, d_z = 1.06).

Group data for normalized iMPS, mMPS, and SES_hams mean peak knee flexion torques are summarized in Fig. 2B. Comparison between iMPS and mMPS conditions relative to SES_hams revealed a significant main effect of stimulation (F(6,66) = 7.839, p < 0.001, η²ₚ = 0.416). Post hoc pairwise comparisons using Dunnett’s test revealed all iMPS conditions (BF_lh, BF_sh, SM, ST) (t(11) = -7.80 to -4.94, all p < 0.003, all d_z >1.03) and the BF mMPS condition (t(11) = -4.137, p = 0.009, d_z = 0.882) produced less knee flexion torque than SES_hams. Knee flexion torque produced during all paired-muscle (BF + SM, BF + ST, SM + ST) mMPS conditions was not significantly different than SES_hams (all p > 0.054, d_z >0.502). Across all participants, SES_hams produced greater knee flexion torque than ALL_hams (mean: 21.0% MVC vs. 18.4% MVC) in 42% (7/12) of participants; however, the group difference was not significant (t(11) = -0.741, p = 0.933, d_z = 0.098).

Knee torque between multiple motor point stimulation conditions

Figure 2A summarizes the group data on normalized knee extension torques. Repeated measures ANOVA revealed a significant main effect of stimulation across quadricep mMPS conditions (F(6, 66) = 27.247, p < 0.001, η²ₚ = 0.712). Post hoc pairwise comparisons using Bonferroni correction indicated that all single-muscle conditions produced less torque than all paired-muscle and ALL_quads conditions (all t(11) < -1.078, all p < 0.003, all d_z >0.802). ALL_quads produced significantly greater torque than all mMPS conditions (all t(11) > 4.40, all p < 0.030, all d_z >0.67), except for the VM + VL condition, which did not differ significantly (t(11) = 3.146, p = 0.195, d_z = 0.429).

Figure 2B summarizes the group data on normalized knee flexion torque. Repeated measures ANOVA revealed a significant main effect on stimulation across hamstring mMPS conditions (F(6, 66) = 7.838, p < 0.001, η²ₚ = 0.416). Post hoc pairwise comparisons using Bonferroni correction indicated that two single-muscle (SM and ST) conditions produced less torque than ALL_hams (both t(7) > 4.10, both p < 0.026, both d_z >1.030). For paired-muscle mMPS conditions, BF + SM and SM + ST produced less torque than ALL_hams (both t(7) > 4.33, both p < 0.03; both d_z >0.289); however, BF + SM did not produce significantly different knee flexion torque than ALL_hams (t(7) = 0.533, p = 1.000, d_z = 0.079).

Contribution of individual motor points to knee extension torque

Summary data of coefficients for each quadriceps motor point are presented in Fig. 3. The mixed-effects model indicated that all motor points contributed significantly to knee extension torque, except VL_d (p = 0.438). The largest contributions were observed for VL_p and VL_i, followed by RF_d, RF_p, and VM_p, with VM_d showing a smaller but significant effect. Participant-level variability was minimal (variance = 0.003), suggesting consistent torque responses across individuals. These findings highlight the dominant roles of the vastus lateralis and rectus femoris motor points in torque generation.

Differences in observed and expected knee extension joint torque

Group data comparing τ_obs and τ_pre for all quadricep MPS combinations are found in Fig. 4. Paired t tests for single-muscle mMPS condition revealed no significant difference between τ_obs and τ_pre for VM and RF (all t(11) < -1.499, all p > 0.059, all d_z < -0.609), whereas τ_obs was significantly less than τ_pre for VL (t(11) = -2.300, p = 0.042, d_z = -0.664). Repeated measures ANOVA was significant in the main effect on stimulation across τ_obs and τ_pre for VM + RF (F(4, 44) = 5,459, p = 0.001, η²ₚ = 0.332), and VM + VL (F(4, 44) = 4.827, p = 0.003, η²ₚ = 0.305), but no Dunnett post hoc revealed significant between any τ_obs and all τ_pre (all t(11) < -1.602, all p > 0.096, all d_z < -0.462). For RF + VL, there was a significant effect on stimulation across τ_obs and τ_pre (F(4, 44) = 11.746, p < 0.001, η²ₚ = 0.516), with Dunnett post hoc revealing τ_obs being significant less than all (4/4) τ_pre (all t(11) < -3.534, all p < 0.009, all d_z < -1.020). Further, for ALL_quads, there was a significant effect on stimulation across τ_obs and τ_pre (F(14, 154) = 9.452, p < 0.001, η²ₚ = 0.462), with Dunnett post hoc revealing τ_obs being significant less than all (14/14) τ_pre (all t(11) < -2.919, all p < 0.05, all d_z < -0.636)

Linear regressions comparing τ_obs and τ_pre across mMPS conditions are shown in Fig. 5A, with metrics and alignment scores found in Table 1. One-sample t tests of the regression slopes against unity indicated that slopes were generally less than 1, except for [VM + RF] (slope = 0.990, t = -0.828, p = 0.425, R² = 0.819, RMSE = 0.040, F₁,ₙ₋₂ = 45.183) and [VM + VL] (slope = 1.011, t = 1.120, p = 0.287, R² = 0.894, RMSE = 0.037, F₁,ₙ₋₂ = 84.624), indicating that activation of both vastus medialis motor points offsets possible muscle activation overlap stemming from rectus femoris and vastus lateralis MPS. The distribution of slopes was right-skewed, indicating that most mMPS combinations underestimated observed torque relative to theoretical predictions (Fig. 5B). In contrast, intercepts demonstrated an inverse pattern, with positive offsets becoming more prominent as slopes deviated below unity. This compensation effect was confirmed by a significant negative correlation between slopes and intercepts (r = -0.906, p < 0.001), suggesting that under-proportional scaling (slope < 1) was systematically offset by upward shifts in the regression line (Fig. 5B). Calculation of activation scores revealed that τ_obs and τ_pre comparisons involving VM (i.e., stimulation for both vastus medialis motor points) had the best linear agreement, suggesting minimal intermuscular activation overlap, offsetting torque deviation attributed to vastus lateralis and rectus femoris (Table 1).

Table 1
Summary of Linear Regression Slopes and Intercepts for Quadriceps mMPS τ_obs and τ_pre Comparisons
Reference Number	mMPS Condition	τ_pre Combination	Slope	Y-intercept
11	VM + VL	VM, VL	1.011	-0.021	0.032
7	VM + RF	VM, RF	0.994	-0.026	0.032
27	ALL_quads	VM, RF + VL	0.966	-0.008	0.042
9	VM + VL	VM, VL_d, VL_i, VL_p	0.973	-0.045	0.072
26	ALL_quads	VM_d, VM_p, RF + VL VM + VL	0.849	0.018	0.169
3	VL	VL	0.810	0.008	0.198
6	VM + RF	VM, RF, VL	0.740	0.022	0.262
10	VM + VL	VM_d, VM_p, RF	0.751	0.042	0.291
20	ALL_quads	VL, VM + RF	0.688	0.031	0.343
21	ALL_quads	VM, RF, VL_d, VL_i, VL_p	0.646	0.027	0.381
8	VM + VL	VM_d, VM_p, VL_d, VL_i, VL_p	0.654	0.049	0.395
29	ALL_quads	VL, VM + RF	0.659	0.062	0.403
28	ALL_quads	RF, VM + VL	0.645	0.062	0.417
22	ALL_quads	VM_d, VM_p, RF, VL	0.599	0.059	0.460
15	RF + VL	RF, VL	0.589	0.054	0.465
2	RF	RF	0.569	0.041	0.472
24	ALL_quads	VM + RF, VL_d, VL_i, VL_p	0.590	0.069	0.479
5	VM + RF	VM, RF_d, RF_p	0.576	0.055	0.479
18	ALL_quads	VM_d, VM_p, RF, VL_d, VL_i, VL_p	0.546	0.064	0.518
17	ALL_quads	VM, RF_d, RF_p, VL_d, VL_i, VL_p	0.534	0.061	0.527
23	ALL_quads	VM, RF_d, RF_p, VL	0.529	0.082	0.553
25	ALL_quads	VM + VL, RF_d, RF_p	0.516	0.098	0.582
4	VM + RF	VM_d, VM_p, RF_d, RF_p	0.488	0.071	0.583
1	VM	VM	0.463	0.046	0.583
13	RF + VL	RF, VL_d, VL_i, VL_p	0.464	0.079	0.615
14	RF + VL	RF_d, RF_p, VL	0.459	0.082	0.623
16	ALL_quads	VM_d, VM_p, RF_d, RF_p, VL_d, VL_i, VL_p	0.463	0.089	0.626
19	ALL_quads	VM_d, VM_p, RF_d, RF_p, VL	0.474	0.100	0.629
12	RF + VL	RF_d, RF_p, VL_d, VL_i, VL_p	0.420	0.081	0.661

The random forest regression model (Fig. 6) demonstrated strong in-sample performance in predicting the mean quadricep TDI using observed values, achieving an R² of 0.958 and RMSE of 0.020. However, when evaluated using 5-fold cross-validation, the model showed reduced generalizability, with an average R² of 0.509 and RMSE of 0.057. Feature importance analysis revealed that rectus femoris MPS conditions (RF, RF_d, RF_p) were the strongest contributors to TDI variance, suggesting a dominant role of rectus femoris stimulation in driving deviations from linear torque summation. In contrast, vastus medialis MPS conditions (VM_d, VM, VM + VL) contributed the least, indicating a comparatively minor influence on TDI, resulting in better alignment between τ_obs and τ_pre.

Quadriceps mMPS enhances knee extension torque output beyond SES

Stimulation of all quadriceps motor points produced ~ 51% greater knee extension torque compared with conventional SES (33.3% MVC vs. 22.1% MVC) (Fig. 2A). This finding shows that mMPS engages a broader portion of the quadriceps than SES_quads, supporting its potential to improve orthotic performance and exercise-based neurorehabilitation applications. In particular, this enhancement could translate into improved outcomes for FES-cycling and FES-rowing, where torque production from the quadriceps is essential for generating sufficient power and sustaining aerobic workloads (9, 10, 33–35).

Our results extend prior observations at the twitch level, where activating all quadriceps motor points yielded the largest summed torque, disproportionately driven by vastus lateralis (13). Importantly, the present study demonstrates that this advantage persists under sustained tetanic stimulation, which more closely approximates the continuous activation required for functional movements. These findings also corroborate Gobbo et al. (30) who showed that a single motor point in tibialis anterior and vastus lateralis generated greater tetanic torque than SES, thereby reinforcing the generalizable superiority of motor point targeting across muscle groups.

From a mechanistic perspective, the greater torque observed with quadriceps mMPS likely reflects a broader and more distributed motor unit recruitment compared with SES_quads. Single-electrode stimulation activates fibers predominantly beneath the electrode pair in a spatially fixed manner, whereas MPS exploits anatomically defined loci of excitability, enabling recruitment of motor axons that might otherwise remain inaccessible (19, 20, 31, 32). This mechanism is supported by neurophysiological evidence that SES stimulates a restricted subset of the muscle compared with voluntary activation or peripheral nerve stimulation (16–18). Thus, mMPS may more closely approximate physiological recruitment patterns and generate stronger contractions.

Motor point contributions within the quadriceps

The present study identified the proximal and intermediate vastus lateralis motor points (VL_p, VL_i) as the dominant contributors to knee extension torque, consistent with the structural and physiological prominence of the vastus lateralis (Fig. 3). Anatomical and imaging studies have shown that the vastus lateralis accounts for the largest proportion of quadriceps strength (~ 40%) compared with the vastus medialis (~ 25%) and rectus femoris–vastus intermedius (~ 35%) (44, 45). This regional dominance likely explains the disproportionately high knee extension torque observed when stimulating VL_p and VL_i. In contrast, the vastus medialis contributed more modest absolute torque (Fig. 3), which may reflect its smaller cross-sectional area and more oblique fiber orientation (44, 46). Nevertheless, inclusion of vastus medialis motor points consistently enhanced torque generation with minimal redundancy. Its anatomical compartmentalization allows it to activate regions under-recruited by SES_quads (19, 20, 31, 32), complementing the vastus lateralis and improving overall recruitment heterogeneity. This supports the functional importance of VM inclusion despite its smaller individual contribution (45). Rectus femoris, by comparison, contributed inconsistently to torque output, with variable effects (Figs. 4, 5) Given its biarticular structure and smaller proportional role in knee extension, rectus femoris appears to be a less reliable contributor compared with the vastus lateralis and medialis (Fig. 6).

Collectively, these findings align with prior reports that MPS achieves more complete muscle activation than SES, which often under-recruits regions such as the vastus medialis and lateralis (16–18, 30). By optimizing motor point selection, stimulation can engage a broader and more efficient portion of the quadriceps compared with conventional SES, supporting both orthotic performance and potential therapeutic benefits.

Recruitment overlap within the quadriceps

A secondary aim of this study was to assess recruitment overlap by comparing observed torque with linear predictions from individual motor point contributions. This analysis provides insight into the efficiency of channel allocation – whether additional stimulation sites uniquely increase torque or simply activate fibers already recruited by other sites.

The largest discrepancies between observed and predicted torques were observed with rectus femoris stimulation, indicating substantial overlap (Figs. 4–6). This may stem from current spread into neighboring quadriceps motor point domains or complex intertendinous coupling between quadriceps heads and the quadriceps tendon (47, 48), which may contribute to redundant torque output Such overlap reduces the efficiency of stimulation, as additional channels contribute less unique torque relative to their cost in complexity and participant burden. In contrast, vastus medialis stimulation was associated with minimal redundancy, suggesting that it engages a relatively distinct pool of motor units not accessed by vastus lateralis or rectus femoris stimulation.

These findings carry practical implications. When optimizing channel allocation for MPS, priority should be given to motor point sites that both contribute significant torque and minimize overlap – namely proximal and intermediate vastus lateralis, together with vastus medialis. Rectus femoris stimulation should be considered only when additional channels are available and when its incremental torque benefits outweigh the cost of redundancy. Such a selective approach aligns with recommendations from prior work emphasizing that maximizing efficiency is as important as maximizing torque when designing mMPS stimulation protocols (13, 30).

Hamstrings response to mMPS

In contrast to the quadriceps, stimulation of all hamstring motor points did not significantly increase knee flexion torque relative to SES (Fig. 2B). This limited effect likely reflects both physiological and methodological constraints. Motor point mapping has demonstrated that the hamstrings possess fewer and more variably located sites compared to the quadriceps (36), with deeper locations of the semimembranosus and biceps femoris short head requiring higher stimulation currents for motor point identification in the present study, suggesting less accessible access using transcutaneous stimulation. This may have limited the torque-generating potential of these sites before participant tolerance was reached. Further, in the current study, participants were seated such that the stimulating electrodes were compressed between the seating surface and the skin, which may have altered electrode-tissue contact. Additionally, deformation of the underlying hamstrings could have influenced current distribution, thereby affecting the effective stimulation delivered to the muscle in both MPS and SES_hams conditions, limiting knee flexion torque production from both FES methods.

Limitations

Several limitations should be acknowledged. First, the present study was conducted in neurologically intact participants, and it remains uncertain whether the same torque gains and recruitment patterns would generalize to individuals with neurological impairments, where muscle atrophy, spasticity, and altered excitability may influence outcomes (27–29). Second, we used a finite number of surface electrodes, which constrained the spatial resolution of motor point targeting. Although we attempted to identify and stimulate all accessible motor points, deeper sites or those with high interindividual variability may have been missed (36). Third, we evaluated tetanic contractions under isometric conditions, which may not fully capture the dynamic demands of functional FES applications such as cycling, walking, or standing. Finally, we normalized torque to maximal voluntary contraction, which provides a useful benchmark in neurologically intact participants but may not directly translate to clinical populations with impaired voluntary control.

This study demonstrates that stimulation of all quadriceps motor points generated 51% greater torque compared with conventional SES, highlighting the potential of mMPS to improve the effectiveness of FES interventions. Second, the largest torque contributions were derived from proximal and intermediate vastus lateralis sites, together with vastus medialis, indicating that these should be prioritized for optimized motor point selection. Third, rectus femoris stimulation produced torque but also introduced substantial overlap, suggesting it should be considered only when channel allocation permits and when the torque benefit outweighs redundancy. In contrast, stimulation of all hamstring motor points did not yield additional torque, highlighting muscle-specific constraints. These findings provide practical guidance for electrode placement and channel allocation, suggesting that optimal quadriceps stimulation can be achieved by prioritizing a limited subset of motor points. Taken together, they establish a framework for refining FES strategies to maximize torque generation, minimize redundancy, and ultimately improve functional outcomes in neurorehabilitation.

Participants

Twelve neurologically intact participants (9 males, 3 females; age: 25.5 ± 4.3 yrs, body mass: 72.3 ± 15.3 kg, height: 175.8 ± 6.7 cm) took part in this study. All participants self-reported no peripheral or central neuromuscular, osteological, or cardiovascular conditions. To avoid any confounding effects from fatigue or delayed-onset muscle soreness on artificially- or voluntarily induced muscle contractions, participants were asked to abstain from any intensive exercise of the lower limbs a minimum of 48 hours prior to undergoing experimental procedures. All participants provided written and verbal informed consent prior to participation. The experimental procedures were approved by the Institutional Research Ethics Board.

Motor point identification

Prior to experimental procedures, motor points for the right anterior and posterior thigh were identified. In total, up to seven and four motor points were expected to be identified for the quadriceps femoris and for the biceps femoris, respectively (36). To account for interindividual differences in motor point positions (13, 38, 39), locations were initially estimated using bony and soft tissue anatomical landmarks and confirmed by tracking the skin with a cathodic pen electrode (contact surface: 2 mm²) (Chattanooga Physio, DJO Global, Chattanooga, TN, United States) delivering a low-intensity (< 15 mA) pulse at 2 Hz. The corresponding anode (5 cm x 10 cm; Axelgaard Manufacturing Co. Ltd., Fallbrook, CA, United States) was centered about the antagonist group. Motor points were tracked and their locations confirmed through manual palpation of the surrounding musculature and visual inspection of the largest skin deformation from muscle contracture in response to the smallest delivered electrical current (31, 36, 39). All quadriceps motor points were identified on the right thigh with the participant positioned in 80° of hip flexion and 90° of knee flexion (anatomical position = 0°), as measured relative to the anatomical axes of rotation using an analog goniometer. Up to seven motor points were located for the superficial quadriceps femoris muscles: two for the vastus medialis (distal, VM_d; and proximal, VM_p), two for the rectus femoris (distal, RF_d; and proximal, RF_p), and three for the vastus lateralis (distal, VL_d; intermediate, VL_i; and proximal, VL_p) (36). For hamstring motor point identification, participants were positioned prone with the knee flexed to 70° relative to full extension (0°). Up to four motor points were located: two for the biceps femoris (long head, BF_lh; and short head, BF_sh), one for the semimembranosus (SM), and one for the semitendinosus (ST) (36). All motor points were marked on the skin using indelible ink. Motor point locations for all quadriceps (seven total) and hamstrings (four total) muscles were identified for 12/12 participants.

Stimulating electrode placements: quadriceps configuration

Prior to surface electrode fixation, the skin was cleaned using alcohol swabs (70% v/v), being carful not to remove the motor point markings. For the MPS conditions, individual self-adhesive cathode-anode electrode pairs (two 5 x 5 cm) were adopted for each motor point (Fig. 1A). The cathode was centered over the motor point, while the anode was positioned, in parallel, either slightly proximal or distal to the cathode over the respective muscle. An edge-to-edge interelectrode distance of approximately 2 cm was aimed for; however, this spacing was not always feasible due to limited surface area on the thigh, particularly without encroaching on the adductor or hamstring muscle groups. In total, seven cathode-anode pairs were adopted (14 total electrodes). For the quadricep SES (SES_quads) condition across the anterior thigh, a large self-adhesive electrode pair (7.5 cm × 10 cm) was placed in a proximal-distal configuration (Fig. 1B). The proximal cathode was oriented transversely, with its superior margin positioned approximately 10 cm distal to the inguinal groove and slightly lateral, positioned over the proximal bodies of the vastus lateralis and rectus femoris muscles, while avoiding the femoral triangle. The distal anode was also oriented transversely, with the inferior margin positioned approximately 5 cm proximal to the base of the patella (17). To minimize potential bias in experimenter placement of SES_quads electrodes relative to participants’ motor points, markings indicating motor point locations were erased using rubbing alcohol until no visible pigment remained. These motor point locations were not referenced during SES_quads electrode placement.

Stimulating electrode placements: hamstrings configuration

For the MPS condition, individual cathode-anode electrode pairs (5 × 5 cm each) were assigned to each motor point (Fig. 1A). As the hamstring muscles are biarticular that feature a pelvic origin, changes in hip angle can lengthen their muscle fibers (40), which may inadvertently migrate the motor point relative to the joint angle they were initially searched for (26, 41). To account for potential superior motor point migration due to differences in hip angle between motor point screening (anatomically neutral) and experimental evaluation (80° flexion) in the present study, the cathode was centered approximately 1 cm superior to the identified motor point and aligned to follow the respective muscle fiber orientation as closely as possible. The anode was positioned either proximally or distally along the same muscle, based on available space. In total, four cathode-anode pairs were adopted (eight total electrodes). For the hamstring SES (SES_hams) condition across the posterior thigh, a large (7.5 cm × 10 cm) cathode-anode pair was positioned proximally and distally (Fig. 1B). The proximal cathode was oriented transversely, immediately distal to the inferior gluteal fold along the midline of the thigh. The distal anode was also oriented transversely, with its inferior margin positioned approximately 3 cm superior to the center of popliteal fossa, superimposing the surface impressions of the distal hamstring tendons. Markings denoting motor point locations were erased and not considered when positioning the SES_hams electrodes.

Pre-experimental interventions

In order to evaluate artificially induced knee extension and knee flexion isometric tetanic torques induced from FES (MPS and SES) of the thigh, participants were comfortably seated with their right knee joint aligned with the center of rotation of a joint dynamometer (Biodex System 3, Biodex Medical Inc., Shirly, NY, United States). For quadricep FES conditions, the hip was flexed at 80° and knee flexed at 90° (anatomical position = 0° reference) in order to position the quadriceps in an advantageous muscle length to evoke larger torques (42). For hamstring FES conditions, the hip was flexed at 80° and knee flexed 70°. Inelastic cushioned restraints were applied across the torso and thigh to stabilize the body and mitigate any extraneous joint motion that might confound the assessment of knee torque output during experimental procedures. The leg was secured to the dynamometer attachment arm with a cushioned restraint positioned above the ankle joint, with the foot allowed to hang freely. To enable interindividual comparisons of FES-induced knee torque, participants performed two maximal voluntary contractions (MVCs) of knee extension and flexion for 5 seconds, with strong verbal encouragement, each separated by a 1-minute rest. Participants were instructed to ‘contract as strong and as fast as possible’ while minimizing hip involvement, ensuring that the movement was isolated to knee extension and flexion. Real-time torque traces were displayed on a computer monitor to participants to facilitate maximal effort during contractions. The average maximal knee torque from the steady-state torque profile across both MVC trials was used to normalize all FES-induced torque values.

To establish the current amplitude for FES conditions, the maximal tolerable stimulation intensity (MTSI) was individually determined for each individual motor point and SES electrode configurations and subsequently used for experimental evaluations. A designated neuromuscular electrical stimulation device (Chattanooga Continuum, Wilmington, DE, United States) delivered an asymmetric, charge-balanced cathodic waveform (50 Hz frequency, 400 µs pulse width) for all FES sites. Stimulation was manually triggered and carefully controlled by the experimenter using an external push button. The MTSI for each FES site was determined by gradually increasing stimulation from 5 mA in 5 mA steps, applied for 3 s at each increment, until the participant’s tolerance threshold was reached. The intensity was then adjusted in ± 1 mA increments to precisely establish the MTSI. The experimenter continually assessed the participant's ability and willingness to tolerate higher currents before increasing the stimulation intensity. To limit transient fatigue and discomfort from influencing stimulation tolerance, FES conditions were conducted in a pseudorandom order, ensuring that motor points from the same muscle were not evaluated in immediate succession. Participants were instructed to consider the determination of the MTSI at each FES site independently, without using the sensations from other sites to influence their judgment for another. For the successful application of the final MTSI in experimental testing, the following criteria had to be met: (1) the MTSI induced a fused, nonfasciculated muscle state (visually confirmed), in which a steady-state torque profile was registered; (2) no exogenous joint movement, either voluntary or FES-induced, was observed, as confirmed through visual inspection and manual palpation of adjacent or antagonistic muscles (e.g., flexion/extension of the torso, hamstring contraction during quadriceps stimulation, quadriceps contraction during hamstring stimulation); and (3) the stimulation amplitude was tolerated by the participant. If exogenous joint movement was visually observed (e.g., hip extension/flexion), the stimulation intensity was finely adjusted about the MTSI until only extension (quadricep FES) or flexion (hamstring FES) of the knee was produced, with minimal adjacent joint movement. If all criteria were satisfied, the designated current was recorded for each FES site and were adopted for all experimental conditions thereafter. In the current study, two participants reached the maximal stimulator output (100 mA) for several motor points, which was then adopted for testing. Consequently, it remains uncertain whether the final 100 mA represented their true tolerations for those sites.

Experimental procedures

To evaluate the potential of FES-induced tetanic torque production at the motor points of the thigh, ‘individual MPS’ (i.e., direct stimulation of each motor point separately, iMPS), and inter- and intramuscular ‘multiple MPS’ (i.e., direct stimulation of more than one motor point, mMPS) conditions were assessed. The theoretical number of motor point combinations for the quadriceps and hamstrings are 127 (2⁷ – 1) and 15 (2⁴ – 1), respectively. However, practical limitations – including testing duration, FES-induced muscle fatigue, and participant burden –made it infeasible to evaluate all possible tetanic stimulation combinations within a single session, particularly given day-to-day variations in tolerance and performance across sex and session number (43). Therefore, to evaluate the tetanic torque-generating potential of mMPS, we restricted our analysis to muscle-specific motor point configurations. This included stimulation of individual motor points, all motor points within a single muscle, paired muscles, and compartmental activation. This framework enabled investigation of torque recruitment dynamics in response to mMPS.

For the quadriceps, 13 total MPS conditions were evaluated, comprising both iMPS and mMPS protocols. The iMPS conditions involved the independent stimulation of the seven motor points (VM_d, VM_p, RF_d, RF_p, VL_d, VL_i, VL_p). The mMPS conditions included: (1) single-muscle MPS, defined as the simultaneous stimulation of all motor points within a single muscle (e.g., VM_d and VM_p for vastus medialis), for a total of three conditions (VM, RF, VL); (2) paired-muscle MPS, defined as the simultaneous stimulation of all motor points from two muscles (e.g., VM_d, VM_p, RF_d, and RF_p for vastus medialis and rectus femoris), for a total of three conditions (VM + RF, VM + VL, RF + VL); and (3) ALL_quads MPS, involving the simultaneous stimulation of all seven quadriceps motor points, comprising one condition.

For the hamstrings, nine total MPS conditions were evaluated, consisting of both iMPS and mMPS protocols. The iMPS conditions involved the independent stimulation of four single motor points (BF_lh, BF_sh SM, ST). The mMPS conditions included: (1) single-muscle MPS, for a total of three conditions; here, only the biceps femoris contained more than one motor point, yielding one condition. Because semimembranosus and semitendinosus each have only one motor point (36), their evaluations were categorized under single-muscle MPS rather than iMPS; (2) paired-muscle MPS, for a total of three conditions (BF + SM, BF + ST, SM + ST); and (3) ALL_hams MPS, comprising one condition.

The iMPS conditions were administered in a block-randomized order, with the constraint that no two motor points from the same muscle were tested consecutively. For the mMPS conditions, stimulation began with single-muscle MPS, followed by paired-muscle MPS (randomized within their respective block), and concluded with stimulating all motor points. To minimize fatigue-related bias, single-muscle MPS was tested before paired-muscle MPS. This sequence was chosen to reduce the risk of underestimating knee torque due to potential fatigue carry-over from conditions involving a greater number of stimulated motor points. The overall sequence – iMPS followed by mMPS – was kept consistent across all participants to ensure standardization. Each FES condition consisted of two continuous stimulation trials, delivered using a 1:2:1 stimulation duty cycle: 6 seconds of stimulation, followed by 12 seconds of rest (no voluntary or FES-induced contractions), and then another 6 seconds of stimulation (total condition duration = 24 seconds), resulting in two submaximal steady-state torque outputs (Fig. 1C). This stimulation protocol was standardized across all quadriceps and hamstring locations for iMPS, mMPS, and SES conditions. A 2-minute rest period was provided between each FES condition. After completing all MPS conditions, the same stimulation sequence was applied using the respective SES configuration. All quadriceps FES trials were completed first, followed by all hamstring trials, with a minimum 5-minute rest period separating the two muscle groups. Following all respective quadriceps MPS and hamstring MPS conditions, one final MVC (MVC_post) was performed for knee extension and knee flexion and compared to MVC_pre to assess whether fatiguing effects took place over the course of the experimental session.

Data collection and analysis

All participant knee torque data were collected using LabChart software (LabChart Pro Modules 2018, version 8). Knee torque signals (N·m) were recorded and sampled at 2000 Hz using a 12-bit analog-to-digital data acquisition system (PowerLab System 16/30, ADInstruments, Bella Vista, Australia). Evoked knee torque was evaluated by identifying the peak torque within a 3- to 4-second window of steady-state output, and then geometrically averaging these values from both 6-second contractions for each FES condition. All mean knee torque values were normalized to each participant’s mean preintervention MVC (MVC_pre) and expressed as a percentage (% MVC) to be used for group comparisons.

To estimate the contribution of individual quadriceps motor points to knee extension torque, we fitted a linear mixed-effects model with normalized knee extension torque (% MVC) as the dependent variable. The seven quadricep motor points (VM_d, VM_p, RF_d, RF_p, VL_d, VL_i, VL_p) were entered as binary fixed effects (1 = activated, 0 = not), and participant was included as a random intercept to account for repeated measures. Model coefficients were interpreted as average motor point contributions conditional on the others, with 95% confidence intervals reported. For presentation, coefficients were expressed as percentage contributions by dividing each motor point coefficient by the sum of all motor point coefficients plus the intercept and multiplying by 100.

Previous studies have reported discrepancies between observed torque (τ_obs) from artificially-induced contractions and the theoretically predicted torque (τ_pre) when multiple quadricep motor points were simultaneously activated (13, 25). In the current study, under the assumption that FES selectively and independently recruits nonoverlapping muscle subdomains during continuous delivery, knee extension torque output from iMPS and mMPS quadricep conditions was compared against τ_pre defined as the linear sum of τ_obs from any combination of conditions activating the same set of motor points as the target mMPS condition. Each stimulation condition – whether targeting an individual motor point, single-muscle, paired-muscle, or all motor points – was encoded in a binary activation matrix A ∈ {0,1}^mxn, where m is the total number of stimulation conditions (including both iMPS and mMPS) and n is the number of topographically distinct quadricep motor points (7 total). Each row of A corresponds to a stimulation condition, and each column indicates whether a specific motor point was activated (1) or not (0). For a given composite stimulation condition i, all possible subsets C_i ⊆ {1,…, m} of stimulation conditions were generated such that their combined motor point activations exactly matched those of condition i, without double-counting any motor point. This constraint can be expressed as:

$$\:\left(1\right)\:\:\sum\:_{j=1}^{n}{A}_{ij}=\:\sum\:_{k\in\:{C}_{i}}\sum\:_{j=1}^{n}{A}_{kj}\:\left(2\right)\:\:\sum\:_{k\in\:{C}_{i}}{A}_{kj\:}\le\:1\:\:\forall\:j=1,\:\dots\:,\:n$$

Here, Eq. (1) ensures that the combined stimulation conditions activate exactly the same number of motor points as the composite condition i. Eq. (2) prevents any motor point from being counted more than once when summing MPS conditions, thereby avoiding double-counting motor points. The τ_pre for condition i was then calculated as the sum of τ_obs, such that:

$$\:{\tau\:}_{\text{pre}}^{\left(i\right)}={\sum\:}_{k\in\:{C}_{i}}{\tau\:}_{\text{obs}}^{\left(k\right)}$$

As an example, consider the mMPS condition VM + RF, which simultaneously activates four distinct motor points: VM_d, VM_p, RF_d, and RF_p. The τ_pre for this condition, $\:{\tau\:}_{\text{pre}}^{\left(\text{VM}\text{+}\text{RF}\right)}$, was estimated by summing τ_obs from all valid subsets of conditions whose combined motor point activations were topographically equivalent with respect to VM + RF. Specifically, four distinct combinations are possible from the combination of individual, single-muscle, and paired-muscle MPS conditions evaluated in the current study:

all relevant iMPS conditions:

$$\:{\tau\:}_{\text{pre}}^{\left(\text{VM}\text{+}\text{RF}\right)}={\tau\:}_{\text{obs}}^{\left({\text{VM}}_{\text{p}}\right)}+{\tau\:}_{\text{obs}}^{\left({\text{VM}}_{\text{d}}\right)}+{\tau\:}_{\text{obs}}^{\left({\text{RF}}_{\text{p}}\right)}+{\tau\:}_{\text{obs}}^{\left({\text{RF}}_{\text{d}}\right)}$$

single-muscle VM mMPS and rectus femoris iMPSs:

$$\:{\tau\:}_{\text{pre}}^{\left(\text{VM}\text{+}\text{RF}\right)}={\tau\:}_{\text{obs}}^{\left(\text{VM}\right)}+{\tau\:}_{\text{obs}}^{\left({\text{RF}}_{\text{p}}\right)}+{\tau\:}_{\text{obs}}^{\left({\text{RF}}_{\text{d}}\right)}$$

single-muscle RF mMPS and vastus medialis iMPSs:

$$\:{\tau\:}_{\text{pre}}^{\left(\text{VM}\text{+}\text{RF}\right)}={\tau\:}_{\text{obs}}^{\left(\text{RF}\right)}+{\tau\:}_{\text{obs}}^{\left({\text{VM}}_{\text{p}}\right)}+{\tau\:}_{\text{obs}}^{\left({\text{VM}}_{\text{d}}\right)}$$

single-muscle VM and RF mMPSs:

$$\:{\tau\:}_{\text{pre}}^{\left(\text{VM}\text{+}\text{RF}\right)}={\tau\:}_{\text{obs}}^{\left(\text{VM}\right)}+{\tau\:}_{\text{obs}}^{\left(\text{RF}\right)}$$

Each combination satisfies the constraint that all motor points activated during the VM + RF stimulation are represented exactly once, with no redundancy across constituent subsets. This procedure was applied across all mMPS conditions to generate corresponding τ_pre estimates for comparison against the respective experimentally measured τ_obs values. In total, 29 τ_pre combinations were evaluated for the quadriceps, comprising:

3 for single-muscle MPS (3 condition x 1 τ_pre, each);
12 for paired-muscle MPS (3 conditions x 4 τ_pre, each), and;
14 for ‘all motor point’ stimulation (1 condition x 14 τ_pre)

Next, to quantify the deviation between τ_obs and τ_pre, a torque discrepancy index (TDI) was calculated for each pair of τ_obs and τ_pre, such that $\:TDI\:=\:1-\frac{{\tau\:}_{\text{pre}}^{\left(i\right)}}{{\tau\:}_{\text{obs}}^{\left(i\right)}}$, where values closer to zero indicate stronger agreement between τ_obs and predicted linear sums (τ_pre). The TDI was used as a proxy to quantify discrepancies between τ_obs and τ_pre, attributed to potential activation overlap from FES and/or mechanical interactions arising from unique muscle geometries and properties. To explore the discrepancy between τ_obs and τ_pre, a machine learning approach was used to assess the relative contribution of each stimulation condition (including iMPS and mMPS conditions) for the quadriceps. Torque discrepancy index values were used to train a random forest regression model (100 estimators, random state = 42) based on one-hot encoded representations of each stimulation condition. Each MPS combination was decomposed into its constituent MPS condition, forming a binary feature matrix, and the model was trained to predict the mean normalized TDI associated with each combination. To ensure generalizability, 5-fold cross-validation was performed. Feature importance scores were extracted from the trained model to identify the MPS conditions most strongly driving TDI, thereby providing insight into the contributions underlying deviations from linear torque summation. Additionally, to evaluate the agreement between τ_pre and τ_obs torque responses, linear regression models were fitted for each quadricep mMPS combination. From each regression, the slope and y-intercept were extracted and compared against the ideal case of slope = 1 (perfect proportionality) and intercept = 0 (no systematic offset). To provide a single quantitative measure of agreement, we calculated an alignment score, defined as the Euclidean distance from the optimal point (slope = 1, intercept = 0):

$$\:\text{A}\text{l}\text{i}\text{g}\text{n}\text{m}\text{e}\text{n}\text{t}\:\text{S}\text{c}\text{o}\text{r}\text{e}\:=\:\sqrt{{\left(slope\:-\:1\right)}^{2}+\:{\left(Y-intercept\right)}^{2}}$$

This metric integrates both proportional accuracy (slope) and systematic bias (intercept), with lower values reflecting closer alignment between τ_pre and τ_obs. In this framework, mMPS combinations with the smallest alignment scores were interpreted as providing better linear alignment between τ_pre and τ_obs.

We estimated additive motor point contributions with a linear mixed-effects model. Linear agreement between τ_pre and τ_obs was assessed via simple regression (slope, intercept, alignment score), and factors associated with TDI were examined using a random forest regressor with 5-fold cross-validation.

Statistical analysis

Prior to statistical analysis, neuromechanical data were assessed for normality using the Shapiro–Wilk test, with appropriate parametric or nonparametric tests subsequently applied. To evaluate whether participant fatigue occurred as a result of the experimental interventions, a paired-samples t test was used to compare pre- and postexperimental MVC values (MVCₚ_rₑ vs. MVCₚₒₛₜ). These normalized torques were analyzed separately for knee extension and knee flexion.

Prior to all repeated-measures analyses of variance (ANOVA), the assumption of sphericity was assessed using Mauchly’s test. When sphericity was violated, Greenhouse-Geisser corrections were applied to adjust the degrees of freedom accordingly. To compare torque outputs between mMPS and conventional SES, separate repeated-measures ANOVAs with Dunnett-adjusted post hoc comparisons were conducted for the quadriceps and hamstrings. These analyses evaluated differences in normalized peak knee torque across 13 quadriceps MPS conditions (seven iMPS and six mMPS) and eight hamstring MPS conditions (four iMPS and four mMPS), with each condition compared to its respective SES control. To further assess differences among the mMPS conditions, additional repeated-measures ANOVAs with Bonferroni-adjusted pairwise comparisons were performed separately for each muscle group. This two-tiered analytic approach was implemented to preserve statistical power while appropriately controlling for multiple comparisons. Conducting a single omnibus ANOVA with all possible pairwise comparisons (105 for quadriceps, 45 for hamstrings) would have substantially inflated the risk of Type I error and reduced the sensitivity to detect meaningful effects.

Observed and predicted torques were compared to assess the degree of nonlinearity in torque summation and the relative contribution of mMPS conditions to gauge activation overlaps. For single-muscle mMPS conditions, which each comprised only one τₚ_rₑ condition, paired t tests were performed comparing their respective τ_obs and τₚ_rₑ. For paired-muscle and ALL_quads mMPS conditions, repeated-measures ANOVA was conducted to assess whether τₚ_rₑ combinations significantly differed from the corresponding τ_obs, with Dunnett post hoc tests used to compare each τₚ_rₑ combination directly against its respective τ_obs. Linear regression models were fitted for each τₚ_rₑ against τ_obs using a leave-one-out approach, where each data point was sequentially omitted and the slope recalculated. Slope coefficients were tested against 1 to evaluate proportional agreement, and y-intercepts were examined for systematic offsets. Model performance was further quantified using R², indicating the proportion of variance in τ_obs explained by the τₚ_rₑ, and the root mean square error (RMSE), reflecting the average prediction error. Statistical significance was defined as α = 0.05 (two-tailed). Descriptive data in text and table are reported as geometric mean ± standard deviation. Effect sizes were reported as partial eta squared (η²ₚ) for repeated-measures ANOVA, Cohen’s d_z for paired-samples and pairwise comparisons, and r for Wilcoxon signed-rank test. All t tests, repeated-measures ANOVA, Bonferroni post hoc tests, effect size calculations, linear mixed-modeling, and Random Forest analyses were conducted using custom Python scripts (version 3.11.4), while Dunnett post hoc tests were performed in R (version 4.4.3).

ALL_hams, all hamstring motor points

ALL_quads, all quadricep motor points

ANOVA, analysis of variance

BF, biceps femoris

BF_lh, biceps femoris – long head

BF_sh, biceps femoris – short head

FES, functional electrical stimulation

iMPS, individual motor point stimulation

MPS, motor point stimulation

mMPS, multiple motor point stimulation

MTSI, maximal tolerable stimulation intensity

MVC, maximal voluntary contraction

R², coefficient of determination

RF, rectus femoris

RF_d, rectus femoris – distal

RF_p, rectus femoris – proximal

RMSE, root mean squared error

SES, single-electrode stimulation

SES_hams, single-electrode stimulation – hamstrings

SES_quads, single-electrode stimulation – quadriceps

SM, semimembranosus

ST, semitendinosus

TDI, torque deviation index

VL, vastus lateralis

VL_d, vastus lateralis – distal

VL_i, vastus lateralis – intermediate

VL_p, vastus lateralis – proximal

VM, vastus medialis

VM_d, vastus medialis – distal

VM_p, vastus medialis – proximal

η²ₚ, partial eta squared

τ_obs, observed torque

τ_pre, predicted torque

Ethics approval and consent to participate

The studies involving human participants were reviewed and approved by University Health Network (21-5946) Research Ethics Boards. The participants provided their written informed consent to participate in accordance with the Declaration of Helsinki.

Consent for publication

All authors read and approved the final manuscript for submission for publication.

Funding

This study was supported by the New Frontiers in Research Fund (grant no. NFRFE-2022-00620). Benjamin Kozlowski was supported by the Canadian Graduate Scholarship – Masters from the Natural Sciences and Engineering Research Council of Canada.

Author Contribution

B.K., D.L., and K.M. conceptualized and designed the study. B.K. and M.G. collected the data and performed analyses. B.K., D.L., and K.M. curated, analyzed, and interpreted the data. B.K. and prepared the figures and table. B.K. and K.M. drafted the manuscript. K.M. and A.A. provided funding support and supervision. All authors reviewed and approved the final manuscript.

Acknowledgement

The authors would like to thank all those who participated in the study. The authors would also like to thank Azim Rashidi for his technical support.

Data Availability

The datasets generated and analyzed during the current study are available from the corresponding author, Kei Masani, upon reasonable request.

Popovic MR, Masani K, Milosevic M. Functional Electrical stimulation therapy: mechanisms for recovery of function following spinal cord injury and stroke. In: Reinkensmeyer DJ, Marchal-Crespo L, Dietz V, editors. Neurorehabilitation Technology [Internet]. Cham: Springer International Publishing; 2022. p. 401–27.
Masani K, Yoo P. Neural engineering. In: Rehabilitation Engineering. CRC Press; 2022.
Máté S, Sinan-Fornusek C, Dhopte P, Singh MF, Hackett D, Fornusek C. Effects of functional electrical stimulation cycling combined with arm cranking exercise on cardiorespiratory fitness in people with central nervous system disorders: a systematic review and meta-analysis. Arch Phys Med Rehabil. 2023;104(11):1928–40.
Kern H, Rossini K, Carraro U, Mayr W, Vogelauer M, Hoellwarth U, et al. Muscle biopsies show that FES of denervated muscles reverses human muscle degeneration from permanent spinal motoneuron lesion. J Rehabil Res Dev. 2005;42(3 Suppl 1):43–53.
Kern H, Salmons S, Mayr W, Rossini K, Carraro U. Recovery of long-term denervated human muscles induced by electrical stimulation. Muscle & Nerve. 2005;31(1):98–101.
Dantas MTAP, Fernani DCGL, Silva TD da, Assis ISA de, Carvalho AC de, Silva SB, et al. Gait training with functional electrical stimulation improves mobility in people post-stroke. Int J Environ Res Public Health. 2023;20(9):5728.
Popovic MR, Curt A, Keller T, Dietz V. Functional electrical stimulation for grasping and walking: indications and limitations. Spinal Cord. 2001;39(8):403–12.
Hong Z, Sui M, Zhuang Z, Liu H, Zheng X, Cai C, et al. Effectiveness of neuromuscular electrical stimulation on lower limbs of patients with hemiplegia after chronic stroke: a systematic review. Arch Phys Med Rehabil. 2018;99(5):1011–1022.e1.
Marquez-Chin C, Popovic MR. Functional electrical stimulation therapy for restoration of motor function after spinal cord injury and stroke: a review. Biomed Eng Online. 2020;19(1):34.
Ye G, Grabke EP, Pakosh M, Furlan JC, Masani K. Clinical benefits and system design of fes-rowing exercise for rehabilitation of individuals with spinal cord injury: a systematic review. Arch Phys Med Rehabil. 2021;102(8):1595–605.
Estigoni EH, Fornusek C, Smith RM, Davis GM. Evoked EMG and muscle fatigue during isokinetic FES-cycling in individuals with SCI. Neuromodulation. 2011;14(4):349–55; discussion 355.
Flodin J, Juthberg R, Ackermann PW. Effects of electrode size and placement on comfort and efficiency during low-intensity neuromuscular electrical stimulation of quadriceps, hamstrings and gluteal muscles. BMC Sports Sci Med Rehabil. 2022;14(1):11.
Lim D, Castillo MD, Bergquist AJ, Milosevic M, Masani K. Contribution of each motor point of quadriceps femoris to knee extension torque during neuromuscular electrical stimulation. IEEE Trans Neural Syst Rehabil Eng. 2021;29:389–96.
Barss TS, Sallis BWM, Miller DJ, Collins DF. Does increasing the number of channels during neuromuscular electrical stimulation reduce fatigability and produce larger contractions with less discomfort? Eur J Appl Physiol. 2021 Sept;121(9):2621–33.
Ackermann PW, Juthberg R, Flodin J. Unlocking the potential of neuromuscular electrical stimulation: achieving physical activity benefits for all abilities. Front Sports Act Living. 2024;6:1507402.
Rodriguez-Falces J, Place N. Recruitment order of quadriceps motor units: femoral nerve vs. direct quadriceps stimulation. Eur J Appl Physiol. 2013;113(12):3069–77.
Rodriguez-Falces J, Maffiuletti NA, Place N. Spatial distribution of motor units recruited during electrical stimulation of the quadriceps muscle versus the femoral nerve. Muscle Nerve. 2013;48(5):752–61.
Okuma Y, Bergquist AJ, Hong M, Chan KM, Collins DF. Electrical stimulation site influences the spatial distribution of motor units recruited in tibialis anterior. Clin Neurophysiol. 2013;124(11):2257–63.
Ogino M, Shiba N, Maeda T, Iwasa K, Tagawa Y, Matsuo S, et al. MRI quantification of muscle activity after volitional exercise and neuromuscular electrical stimulation. Am J Phys Med Rehabil. 2002 June;81(6):446–51.
Simoneau-Buessinger E, Leteneur S, Bisman A, Gabrielli F, Jakobi J. Ultrasonographic quantification of architectural response in tibialis anterior to neuromuscular electrical stimulation. J Electromyogr Kinesiol. 2017;36:90–5.
Nakagawa K, Bergquist AJ, Yamashita T, Yoshida T, Masani K. Motor point stimulation primarily activates motor nerve. Neurosci Lett. 2020 Sept 25;736:135246.
Nakagawa K, Fok KL, Masani K. Neuromuscular recruitment pattern in motor point stimulation. Artif Organs. 2023;47(3):537–46.
Kaneko N, Sasaki A, Fok KL, Yokoyama H, Nakazawa K, Masani K. Motor point stimulation activates fewer Ia-sensory nerves than peripheral nerve stimulation in human soleus muscle. J Neurophysiol. 2024;132(4):1142–55.
Lau HK, Liu J, Pereira BP, Kumar VP, Pho RW. Fatigue reduction by sequential stimulation of multiple motor points in a muscle. Clin Orthop Relat Res. 1995;(321):251–8.
Liu J, Lau HK, Min WX, Pereira BP, Kumar VP, Pho RW. Contractile characteristics on electrical stimulation of muscle with multiple motor points. An in vivo study in rabbits. Clin Orthop Relat Res. 1995;(313):231–8.
Crochetiere WJ, Vodovnik L, Reswick JB. Electrical stimulation of skeletal muscle–a study of muscle as an actuator. Med Biol Eng. 1967;5(2):111–25.
Schmoll M, Le Guillou R, Lobato Borges D, Fattal C, Fachin-Martins E, Azevedo Coste C. Standardizing fatigue-resistance testing during electrical stimulation of paralysed human quadriceps muscles, a practical approach. J Neuroeng Rehabil. 2021;18(1):11.
Laubacher M, Aksoez EA, Brust AK, Baumberger M, Riener R, Binder-Macleod S, et al. Stimulation of paralysed quadriceps muscles with sequentially and spatially distributed electrodes during dynamic knee extension. J NeuroEngineering Rehabil. 2019;16(1):5.
Bochkezanian V, Newton RU, Trajano GS, Blazevich AJ. Effects of neuromuscular electrical stimulation in people with spinal cord injury. Med Sci Sports Exerc. 2018 Sept;50(9):1733–9.
Gobbo M, Gaffurini P, Bissolotti L, Esposito F, Orizio C. Transcutaneous neuromuscular electrical stimulation: influence of electrode positioning and stimulus amplitude settings on muscle response. Eur J Appl Physiol. 2011;111(10):2451–9.
Gobbo M, Maffiuletti NA, Orizio C, Minetto MA. Muscle motor point identification is essential for optimizing neuromuscular electrical stimulation use. J Neuroeng Rehabil. 2014;11:17.
Arhos EK, Ito N, Hunter-Giordano A, Nolan TP, Snyder-Mackler L, Silbernagel KG. Who’s afraid of electrical stimulation? Let’s revisit the application of NMES at the knee. J Orthop Sports Phys Ther. 2024;54(2):1–6.
Kapadia N, Masani K, Catharine Craven B, Giangregorio LM, Hitzig SL, Richards K, et al. A randomized trial of functional electrical stimulation for walking in incomplete spinal cord injury: Effects on walking competency. J Spinal Cord Med. 2014 Sept;37(5):511–24.
Tajali S, Iwasa SN, Sin V, Atputharaj S, Desai Kapadia N, Musselman KE, et al. The orthotic effects of different functional electrical stimulation protocols on walking performance in individuals with incomplete spinal cord injury: a case series. Top Spinal Cord Inj Rehabil. 2023;29(Suppl):142–52.
Vieira TM, Cerone GL, Stocchi C, Lalli M, Andrews B, Gazzoni M. Timing and Modulation of Activity in the Lower Limb Muscles During Indoor Rowing: What Are the Key Muscles to Target in FES-Rowing Protocols? Sensors (Basel). 2020;20(6):1666.
Botter A, Oprandi G, Lanfranco F, Allasia S, Maffiuletti NA, Minetto MA. Atlas of the muscle motor points for the lower limb: implications for electrical stimulation procedures and electrode positioning. Eur J Appl Physiol. 2011;111(10):2461–71.
Flodin J, Amiri P, Juthberg R, Ackermann PW. Motorpoint heatmap of the hamstring muscles to facilitate neuromuscular electrical stimulation. Ann Biomed Eng. 2025;53(3):612–21.
Flodin J, Juthberg R, Ackermann PW. Motor point heatmap guide for neuromuscular electrical stimulation of the quadriceps muscle. J Electromyogr Kinesiol. 2023 June;70:102771.
Bowden JL, McNulty PA. Mapping the motor point in the human tibialis anterior muscle. Clin Neurophysiol. 2012;123(2):386–92.
Lunnen JD, Yack J, LeVeau BF. Relationship between muscle length, muscle activity, and torque of the hamstring muscles. Phys Ther. 1981;61(2):190–5.
Gonzalez EJ, Downey RJ, Rouse CA, Dixon WE. Influence of elbow flexion and stimulation site on neuromuscular electrical stimulation of the biceps brachii. IEEE Trans Neural Syst Rehabil Eng. 2018;26(4):904–10.
Cavalcante JGT, Ribeiro VH de S, Marqueti R de C, Paz I de A, Bastos JAI, Vaz MA, et al. Effect of muscle length on maximum evoked torque, discomfort, contraction fatigue, and strength adaptations during electrical stimulation in adult populations: A systematic review. PLoS One. 2024;19(6):e0304205.
Alon G, V Smith G. Tolerance and conditioning to neuro-muscular electrical stimulation within and between sessions and gender. J Sports Sci Med. 2005;4(4):395–405.
Maughan RJ, Watson JS, Weir J. Strength and cross-sectional area of human skeletal muscle. J Physiol. 1983;338:37–49.
Farahmand F, Sejiavongse W, Amis AA. Quantitative study of the quadriceps muscles and trochlear groove geometry related to instability of the patellofemoral joint. Journal of Orthopaedic Research. 1998;16(1):136–43.
Hori M, Suga T, Terada M, Miyake Y, Nagano A, Isaka T. Torque-producing capacity is affected by moment arm in the human knee extensors. BMC Res Notes. 2020 July 20;13(1):343.
Olewnik Ł, Ruzik K, Szewczyk B, Podgórski M, Aragonés P, Karauda P, et al. The relationship between additional heads of the quadriceps femoris, the vasti muscles, and the patellar ligament. Biomed Res Int. 2022;2022:9569101.
Grob K, Manestar M, Filgueira L, Ackland T, Gilbey H, Kuster MS. New insight in the architecture of the quadriceps tendon. J Exp Orthop. 2016;3(1):32.

No competing interests reported.

Download PDF

Editorial decision: Revision requested
20 Nov, 2025
Reviews received at journal
18 Nov, 2025
Reviews received at journal
04 Nov, 2025
Reviews received at journal
29 Oct, 2025
Reviewers agreed at journal
15 Oct, 2025
Reviewers agreed at journal
15 Oct, 2025
Reviewers agreed at journal
14 Oct, 2025
Reviewers agreed at journal
14 Oct, 2025
Reviewers invited by journal
14 Oct, 2025
Editor assigned by journal
09 Oct, 2025
Submission checks completed at journal
08 Oct, 2025
First submitted to journal
04 Oct, 2025

You are reading this latest preprint version

Multiple motor point stimulation increases tetanic knee torque versus conventional single- electrode functional electrical stimulation: implications for functional output and neurorehabilitation

Status:

Version 1

Abstract

Background

Results

Conclusions

Figures

Background

Results

Maximal voluntary contraction knee torque

Knee torque between motor point and single-electrode stimulation conditions

Knee torque between multiple motor point stimulation conditions

Contribution of individual motor points to knee extension torque

Differences in observed and expected knee extension joint torque

Discussion

Quadriceps mMPS enhances knee extension torque output beyond SES

Motor point contributions within the quadriceps

Recruitment overlap within the quadriceps

Hamstrings response to mMPS

Limitations

Conclusions

Methods

Participants

Motor point identification

Stimulating electrode placements: quadriceps configuration

Stimulating electrode placements: hamstrings configuration

Pre-experimental interventions

Experimental procedures

Data collection and analysis

Statistical analysis

Abbreviations

Declarations

Funding

Author Contribution

Acknowledgement

Data Availability

References

Additional Declarations

Status:

Version 1