When we decide to go from one place to another, for the most part, we simply 'get up and go.' While some high-level planning, such as considering obstacles on our path, is necessary, nobody ever gets distracted by calculating how many steps to take or estimating the energy demands of the walk. This is because our walking mechanism is largely governed unconsciously, coarsely controlled by our central nervous system (CNS) and fine-tuned by our brain. But what happens when physical limitations, such as restricted joint functionality, challenge our usual control mechanisms of walking? Our latest research, published in Nature Scientific Data, provides a dataset specifically designed to delve deeper into this question.

In our study, we collected extensive biomechanics and energetics data from 21 neurotypical young adults who walked on a treadmill under 31 different conditions. These included 15 unconstrained (i.e., 'natural') conditions, 15 constrained conditions, and a baseline condition of walking at a self-selected speed (repeated four times over two data collection sessions). The constrained conditions involved a passive orthosis that restrained the mobility of the left knee joint (see the background image above). In both constrained and unconstrained cases, the conditions consisted of all possible combinations of the same three walking speeds and five metronome-guided cadences, defined relative to the preferred cadence at that speed; thus, the only difference between the unconstrained and constrained cases was the orthosis. In our state-of-the-art biomechanics lab (CAREN, Motek), we measured ground reaction forces exerted with each step, joint movements, electrical activity of 16 lower limb muscles, and metabolic energy use during 5 minutes per condition. Our dataset, which provides both raw and segmented data, is now publicly available for further analysis.

What is unique about our research? Unlike previous studies that focused on group averages and trends, our study uniquely involves the same group of participants acting as both 'control' and 'intervention' groups. This innovative study design allows us to closely examine individual adaptations—how each person uniquely adjusts their walking under various conditions. By carefully selecting the constraints, our participants walked in ways that closely resemble those of hemiparetic patients (e.g., stroke survivors, individuals with traumatic brain injuries, or those with incomplete spinal cord injuries), employing strategies like increased hip hiking, excessive circumduction, vaulting, and even step-to-gait. With this approach, we hope our research will help bridging the gap between our understanding of gait in neurotypical individuals and those with impairments, providing insights into the diversity of human walking strategies at an individual level.

As such, the insights this dataset holds will matter to anyone interested in understanding how our bodies adapt to new environments and challenges, and lay the  groundwork for helping those with physical impairments walk more easily and efficiently.