Metabolic cost minimization is thought to underscore the neural control of locomotion. Yet, avoiding high muscle activation, a cause of fatigue, often outperforms energy minimization in computational predictions of human gait. Discerning the relative importance of these criteria in human walking has proved elusive, in part, because they have not been empirically decoupled. Here, we explicitly decouple whole-body metabolic cost and ‘fatigue-like' muscle activation costs (estimated from electromyography) by pitting them against one another using two distinct gait tasks. When experiencing these competing costs, participants ( n = 10) chose the task that avoided overburdening muscles (fatigue avoidance) at the expense of higher metabolic power ( p < 0.05). Muscle volume-normalized activation more closely models energy use and was also minimized by the participants' decision ( p < 0.05), demonstrating that muscle activation was, at best, an inaccurate signal for metabolic energy. Energy minimization was only observed when there was no adverse effect on muscle activation costs. By decoupling whole-body metabolic and muscle activation costs, we provide among the first empirical evidence of humans embracing non-energetic optimality in favour of a clearly defined neuromuscular objective. This finding indicates that local muscle fatigue and effort may well be key factors dictating human walking behaviour and its evolution.

Metabolic cost minimization is widely regarded as the principal optimality criterion that governs walking. Minimizing muscle activation has, nevertheless, outperformed energy optimization in simulating human gait and predicting certain gait behaviors. The highly coupled nature of metabolic and muscle activation costs makes it difficult to empirically discern the interrelationship between these objectives. We implemented a unique experimental design that pits metabolic cost against muscle activation costs estimated from electromyography of seven lower limb muscles. Healthy adults (N=10) selected between walking on a treadmill incline versus walking in a crouched posture (that disproportionately affected activation cost), forcing a choice between minimizing metabolic cost or activation cost. When experiencing these Competing-Cost-Pairs, participants systematically protected their activation cost at the expense of high metabolic power (19% penalty, p<0.05). This held true when activation cost was expressed as the sum of the muscle activations squared (66% saving, p<0.05) and as the maximal activation across muscles (44% saving, p<0.05), both of which penalize overburdening any individual muscle and thus indicate fatigue avoidance. Activation cost, expressed as the sum of muscle volume-normalized activation, more closely models energy use and was also protected by the participants' decision (23% saving, p<0.05) demonstrating that activation was, at best, an inaccurate proxy signal for metabolic energy. Energy minimization was only observed when there was no adverse effect on muscle activation. By decoupling metabolic and activation costs, we provide the first empirical evidence of humans embracing non-energetic optimality in favor of a clearly defined alternate neuromuscular objective.