Persons post-stroke can walk with more symmetric step lengths, but this does not change the cost of transport
Participants walked with asymmetric step lengths during preferred walking (Figure 1B, left) and successfully adjusted their step lengths during the symmetric stepping condition (Figure 1B, right) to reduce step length asymmetry (t(9)=3.41, p<0.01; Figure 1C). We replicated prior findings16,21 showing that restoring step length symmetry with visual feedback had no significant effect on cost of transport (t(9)=-0.05, p=0.96; Figure 1D).
Persons post-stroke exhibit marked interlimb asymmetry even when walking with symmetric step lengths
A conceptual illustration of how we expected interlimb asymmetry may differ between healthy symmetric walking and symmetric stepping after stroke is shown in Figure 2A. We hypothesized that healthy walking consists of symmetric step lengths and similar contributions of each segment to step lengths bilaterally, resulting in small interlimb asymmetry (Figure 2A, left). On the contrary, we expected that symmetric stepping after stroke consists of symmetric step lengths but asymmetric segment contributions, resulting in high interlimb asymmetry (Figure 2A, right).
We show the limb segment orientations during representative steps of symmetric stepping for each participant (Figure 2B). We observed a significant reduction in interlimb asymmetry during symmetric stepping as compared to preferred walking (t(9)=2.34, p=0.04; Figure 2C). However, interlimb asymmetry during symmetric stepping remained markedly increased when compared to healthy gait (for reference, data from eight healthy adults (age: 26±5 years) walking at 1.25 m/s are shown in Figure 2C). Interlimb asymmetry during preferred walking correlated strongly with interlimb asymmetry during symmetric stepping (r=0.99, n=10, p<0.01; Figure 2D, left) and, qualitatively, the data fell near the unity line (Figure 2D, left), suggesting that persons post-stroke showed similar interlimb asymmetry during preferred walking and symmetric stepping. Interlimb asymmetry was significantly associated with cost of transport during preferred walking (r=0.71, n=10, p=0.02) and symmetric stepping (r=0.83, n=10, p<0.01; Figure 2D, right), revealing that kinematic asymmetries are related to cost of transport regardless of step length asymmetry.
We next considered that interlimb asymmetry could remain similar across conditions while individual segment asymmetries could be reorganized. We did not find this to be the case. We compared the individual segment asymmetries (e.g., ) across segments and between conditions. ANOVA revealed a significant main effect of segment (F(1,9)=4.84, p=0.013). Post hoc analyses revealed that segment asymmetry was significantly larger in pelvic rotation (d+e) than trailing pelvis translation (c) (p=0.036). We did not observe a significant main effect of condition (F(1,9)=2.69, p=0.135; Figure 3A) or segment x condition interaction (F(1,9)=0.78, p=0.46). Figures 3B and 3C show how the segment asymmetries contribute to interlimb asymmetry for each participant during each condition. When we compared segment asymmetries after ordering them by which contributed most-to-least strongly to interlimb asymmetry (during preferred walking) between conditions, we also did not observe a significant main effect of condition (F(1,9)=2.69, p=0.135; Figure 3D) or segment x condition interaction (F(1,9)=1.93, p=0.175). As expected, we observed a significant main effect of segment (F(1,9)=23.9, p<0.001).
Asymmetries in AP GRFs, ML GRFs, and vertical COM velocities observed during preferred walking persist during symmetric stepping
We then aimed to identify the features of these asymmetric walking patterns that influence the elevated cost of transport regardless of step length asymmetry. We investigated whether these features were similar in both preferred walking and symmetric stepping, or whether the costs of transport were similarly high in these conditions but resulted from different underlying mechanics. Asymmetric kinematics at heel-strike should result in asymmetric mechanical work done on the COM by each leg, and previous studies demonstrated that mechanical work done on the COM is related to cost of transport in healthy adults26,30. Furthermore, prior studies identified periods of the gait cycle where excessive positive work is often observed post-stroke, contributing to an elevated mechanical energetic cost7,8,31.
We investigated GRF and COM velocity profiles between legs and conditions, as these contribute to the work done over the gait cycle (Figure 4). ANOVA revealed a main effect of leg on the AP GRF peak (F(1,9)=10.97, p<0.01), ML GRF peak (F(1,9)=9.71, p=0.01), and vertical COM velocity peak (F(1,9)=7.68, p=0.02). Post hoc analyses revealed that the AP GRF peak was significantly larger in the nonparetic leg than the paretic leg (p<0.01), the ML GRF peak was significantly larger in the paretic leg than the nonparetic leg (p=0.01), and the vertical COM velocity peak was significantly larger during paretic late stance as compared to nonparetic late stance (p=0.02). There were no significant effects of leg on the vertical GRF peak (F(1,9)=1.25, p=0.29), AP COM velocity peak (F(1,9)=4.29, p=0.07), ML COM velocity peak (F(1,9)=2.90, p=0.12). We did not observe significant effects of condition on GRF or COM velocity variables (all p>0.08) or leg x condition interactions (all p>0.41).
The nonparetic leg does more positive work than the paretic leg during preferred walking and symmetric stepping
We next investigated the work done on the COM by each leg across conditions. We first calculated COM power for each leg during preferred walking and symmetric stepping (Figure 5A). We calculated COM work by integrating COM power over each of the four time periods described in the methods (Figure 5B and C). ANOVA revealed a significant main effect of leg on positive work done 1) by the paretic leg during the first period (step-to-step transition, nonparetic leg trailing) vs. the nonparetic leg during the third period (step-to-step transition, paretic leg trailing; F(1,9)=10.46, p=0.01), and 2) by the paretic leg during the second period (paretic single support) vs. the nonparetic leg during the fourth period (nonparetic single support; F(1,9)=14.10, p<0.01). Post hoc analyses revealed that the nonparetic leg did significantly more positive work during the third period than the paretic leg did during the first period (p=0.01). The nonparetic leg also did significantly more positive work during the fourth period than the paretic leg did during the second period (p<0.01).
ANOVA also revealed a significant main effect of leg on negative work done 1) by the paretic leg during the first period (step-to-step transition, nonparetic leg trailing) vs. the nonparetic leg during the third period (step-to-step transition, paretic leg trailing; F(1,9)=8.67, p=0.02), and 2) by the paretic leg during the third period vs. the nonparetic leg during the first period (F(1,9)=6.63, p=0.03). Post hoc analyses revealed that the paretic leg did significantly more negative work during the first period than the nonparetic leg did during the third period (p=0.02). However, the nonparetic leg did significantly more negative work during the first period than the paretic leg did during the third period (p=0.03).
We did not observe a significant main effect of condition on work done over any of the time periods (all p>0.07). We did observe a significant leg x condition interaction for the positive work done during the fourth period (nonparetic single support; F(1,9)=9.54, p=0.01). Post hoc analyses revealed that the nonparetic leg did significantly more positive work during the fourth period when symmetric stepping as compared to preferred walking (p=0.03).
A separate ANOVA revealed a significant main effect of leg on positive (but not negative; F(1,9)=0.15, p=0.71) work done across all time periods (F(1,9)=7.95, p=0.02). We did not observe a significant main effect of condition on positive or negative work done across all time periods (both p>0.30) but did observe a significant leg x condition interaction on positive work done across all periods (F(1,9)=5.26, p=0.048; F(1,9)=0.68, p=0.43 for negative work). Post hoc analyses revealed that the nonparetic leg did significantly more total positive work than the paretic leg (p=0.02).
Less positive work done by the paretic leg is associated with higher cost of transport, slower walking, and increased interlimb asymmetry
We then assessed whether the positive and negative work done by each leg across the gait cycle were related to cost of transport, gait speed, or interlimb asymmetry during preferred walking and symmetric stepping. Positive paretic work was significantly associated with decreased cost of transport during both conditions (preferred walking: r=-0.84, p<0.01; symmetric stepping: r=-0.82, p<0.01; Figure 6A, left); positive nonparetic work was not (both p>0.60, Figure 6A, right). Positive paretic work was also significantly associated with increased walking speed (preferred walking: r=0.90, p<0.01; symmetric stepping: r=0.84, p<0.01; Figure 6B, left) whereas positive nonparetic work was not (both p>0.63, Figure 6B, right). Finally, positive paretic work was significantly associated with decreased interlimb asymmetry during symmetric stepping (preferred walking: r=-0.60, p=0.06; symmetric stepping: r=-0.67, p=0.03; Figure 6C, left). Positive nonparetic work was not significantly associated with interlimb asymmetry during either condition (both p>0.48; Figure 6C, right). We did not observe significant associations between negative paretic or nonparetic work and cost of transport, walking speed, or interlimb asymmetry during either condition (all p>0.09).