Biology subjects

Donelan, J. M.

Publications and source records attributed to Donelan, J. M..

13 recordsLinked to original sources

bioRxiv2025

Controlling a simple model of bipedal walking to adapt to a wide range of target step lengths and step frequencies

We tested whether the same principles of actuation and control that support steady-state walking are sufficient for robust, rapid gait adaptation over a wide range of step lengths and frequencies. We begin by demonstrating that periodic limit cycle gaits exist at combinations of step frequency and step length that span the full range of gaits achievable by humans. We demonstrate that open-loop local stability is not enough to rapidly transition to target gaits because some gaits in the gait space are unstable and the stable gaits have slow convergence rates. Next, we show that actuating with only one push-off and one hip spring of fixed stiffness cannot fully control the walker in the entire gait space. We solve this by adding a second hip spring with an independent stiffness with respect to the first one to actuate the second half of the swing phase. This allowed us to design local feedback controllers that provided rapid convergence to target gaits by making once-per-step adjustments to push-off and hip spring stiffnesses. To adapt to a range of target gaits that vary over time, we interpolated between local controllers. This policy performs well, accurately tracking rapidly varying combinations of target step length and step frequency with human-like response times across a wide range of human achievable gaits. To test whether this policy is biologically plausible, we use it with supervised learning to train an artificial neural network to perform nearly identical control. Author SummaryPeople can rapidly adapt their walking gaits. In this study, we used a modeling approach to study whether control of walking adaptation is identical to control of steady state walking. We first demonstrate that the model can produce human-like gaits over a wide range of step lengths and step frequencies. However, we found that unlike steady state walking, the model does not transition between gaits quickly or reliably. To address this, we introduced an additional actuation to control the swing leg and used feedback control that applies once-per-step adjustments to the actuations. This enabled the model to rapidly converge to target gaits, even when the targets changed from one step to the next. To test whether this policy is biologically plausible, we use it with supervised learning to train an artificial neural network to perform nearly identical control. This work provides insights into the mechanisms of walking adaptation and has potential implications for the design of adaptive control in robotic and wearable assistive systems.

neuroscience↗

bioRxiv2023

Comparing the advantages and disadvantages of physics-based and neural network-based modelling for predicting cycling power

Models of physical phenomena can be developed using two distinct approaches: using expert knowledge of the underlying physical principles, or using experimental data to train a neural network. Here, our aim was to better understand the advantages and disadvantages of these two approaches. We chose to model cycling power because the physical principles are already well understood. Nine participants followed changes in cycling cadence transmitted through a metronome via earphones and we measured their cadence and power. We then developed and trained a physics-based model and a simple neural network model, where both models had cadence, derivative of cadence, and gear ratio as input, and power as output. We found no significant differences in the prediction performance between the models. The advantages of the neural network model were that, for similar performance, it did not require an understanding of the underlying principles of cycling nor did it require measurements of fixed parameters such as system weight or wheel size. These same features also give the physics-based model the advantage of interpretability, which can be important when scientists want to better understand the process being modelled.

bioengineering↗

bioRxiv2023

Neuromuscular fatigue reduces responsiveness when controlling leg external forces

In legged movement, our legs push against the ground, generating external force vectors that enable agile movements. Neuromuscular fatigue can reduce agility by causing physiological changes, such as slowing muscle reaction time, altering proprioception, and delaying neuromuscular control. Fatigue may deteriorate the nervous systems control of leg external forces, contributing to reductions in agility. In this study, we investigated the effect of fatigue on the performance of the nervous system in controlling the vertical component of leg external force ground reaction forces. We hypothesized that increased leg fatigue would lead to declines in both the responsiveness (speed) and accuracy of leg force control. To test this hypothesis, we used an apparatus that allowed participants to exert controlled vertical forces with one leg against a force plate while immobilizing the rest of their bodies. Participants adjusted their leg external force to match step targets displayed on a screen. We induced fatigue by having participants maintain submaximal leg forces, and we measured leg force control performance between fatigue trials. Results showed a significant 26% reduction in mean maximum force production, leading to a substantial decline in leg force control responsiveness, as evidenced by a 23% increase in rise time and a 25% narrowing of bandwidth. However, fatigue did not significantly reduce leg force control accuracy. Understanding the effects of fatigue on leg force control can inform the development of strategies and technologies to sustain agile performance, even in the presence of fatigue. New and NoteworthyWe developed a method to probe the influence of neuromuscular fatigue on the control of leg external forces. Our findings demonstrate that while fatigue significantly diminishes responsiveness (speed), it does not compromise the accuracy of control. These insights enhance our understanding of legged agility and could guide the development of strategies for optimizing leg force control performance. This study paves the way for future research aimed at identifying and employing effective strategies to maintain agility in the face of fatigue.

neuroscience↗

bioRxiv2021

Characterizing the performance of human leg external force control

Our legs act as our primary contact with the surrounding environment, generating external forces that enable agile motion. To be agile, the nervous system has to control both the magnitude of the force that the feet apply to the ground and the point of application of this force. The purpose of this study was to characterize the performance of the healthy human neuromechanical system in controlling the force-magnitude and position of an externally applied force. To accomplish this, we built an apparatus that immobilized participants but allowed them to exert variable but controlled external forces with a single leg onto a ground embedded force plate. We provided real-time visual feedback of either the leg force-magnitude or position that participants were exerting against the force platform and instructed participants to best match their real-time signal to prescribed target step functions. We tested target step functions of a range of sizes and quantified the responsiveness and accuracy of the control. For the control of force-magnitude and for intermediate step sizes of 0.45 bodyweights, we found a bandwidth of 1.8{+/-}0.5 Hz, a steady-state error of 2.6{+/-}0.9%, and a steady-state variability of 2.7{+/-}0.9%. We found similar control performance in terms of responsiveness and accuracy across step sizes and between force-magnitude and position control. Increases in responsiveness correlated with reductions in other measures of control performance, such as a greater magnitude of overshooting. We modelled the observed control performance and found that a second-order model was a good predictor of external leg force control. We discuss how benchmarking force control performance in young healthy humans aids in understanding differences in agility between humans, between humans and other animals, and between humans and engineered systems.

physiology↗

bioRxiv2021

The Split-Belt Rimless Wheel

Split-belt treadmill training, common in stroke rehabilitation and motor learning experiments, reveals a mechanism through which energy can be extracted from the environment. People can extract net positive work from a split-belt treadmill by lengthening their step onto the fast belt. To understand how leg angles and belt speed differences affect energy transfer between the treadmill and the person during split-belt walking, we simulated a split-belt rimless wheel that alternates rotating on fast and slow treadmill belts. We found that the split-belt rimless wheel can passively walk steadily forward under a range of conditions, extracting enough energy from the treadmill to overcome losses during collisions. The simulated wheel can tolerate both speed disturbances and ground height variability, and it can even capture enough energy to walk uphill. We also built a physical split-belt rimless wheel robot, demonstrating the feasibility of energy extraction during split-belt treadmill walking. In comparing the wheel solutions to human split-belt gait, we found that humans do not maximize positive work performed by the treadmill; costs associated with balance and free vertical moments likely limit adaptation. This study characterizes the mechanics and energetics of split-belt walking, demonstrating that energy capture through intermittent contacts with the two belts is possible when the belt speed difference is paired with an asymmetry in leg angles at step-to-step transitions. This study demonstrates a novel way of harnessing energy through individual rotations rather than continuous contact and offers a simple model framework for understanding human choices during split-belt walking.

bioengineering↗

bioRxiv2020

ENERGY OPTIMIZATION DURING WALKING CAN BE A PRIMARILY IMPLICIT PROCESS

Gait adaptations, in response to novel environments, devices or changes to the body, can be driven by the continuous optimization of energy expenditure. However, whether energy optimization is primarily an implicit process--occurring automatically and with minimal cognitive attention--or an explicit process--occurring as a result of a conscious, attention-demanding, strategy--remains unclear. Here, we use a dual-task paradigm to test whether energy optimization during walking is primarily an implicit or explicit process. To create our primary energy optimization task, we used lower-limb exoskeletons to shift peoples energetically optimal step frequency to frequencies lower than normally preferred. Our secondary task, designed to draw explicit attention from the optimization task, was an auditory tone discrimination task. We found that adding this secondary task did not disrupt energy optimization during walking; participants in our dual-task experiment adapted their step frequency toward the optima by an amount similar to participants in our previous single-task experiment. We also found that performance on the tone discrimination task did not worsen when participants were optimizing for energetic cost; accuracy scores and reaction times remained unchanged when the exoskeleton altered the energy optimal gaits. Survey responses suggest that dual-task participants were largely unaware of the changes they made to their gait to optimize energy, whereas single-task participants were more aware of their gait changes yet did not leverage this explicit awareness to improve gait optimization. Collectively, our results suggest that energy optimization is primarily an implicit process, allowing attentional resources to be directed toward other cognitive and motor objectives during walking. Summary statementPeople can adapt to energy optimal walking patterns without being consciously aware they are doing so. This allows people to discover energetically efficient gaits while preserving attentional resources for other tasks.

neuroscience↗

bioRxiv2020

Increasing the gradient of energetic cost does not initiate adaptation in human walking

When in a new situation, the nervous system may benefit from adapting its control policy. In determining whether or not to initiate this adaptation, the nervous system may rely on some features of the new situation. Here we tested whether one such feature is salient cost savings. We changed cost saliency by manipulating the gradient of participants energetic cost landscape during walking. We hypothesized that steeper gradients would cause participants to spontaneously adapt their step frequency to lower costs. To manipulate the gradient, a mechatronic system applied controlled fore-aft forces to the waist of participants as a function of their step frequency as they walked on a treadmill. These forces increased the energetic cost of walking at high step frequencies and reduced it at low step frequencies. We successfully created three cost landscapes of increasing gradients, where the natural variability in participants step frequency provided cost changes of 3.6% (shallow), 7.2% (intermediate) and 10.2% (steep). Participants did not spontaneously initiate adaptation in response to any of the gradients. Using metronome-guided walking-- a previously established protocol for eliciting initiation of adaptation--participants next experienced a step frequency with a lower cost. Participants then adapted by -1.41{+/-}0.81 (p=0.007) normalized units away from their originally preferred step frequency obtaining cost savings of 4.80{+/-}3.12%. That participants would adapt under some conditions, but not in response to steeper cost gradients, suggests that the nervous system does not solely rely on the gradient of energetic cost to initiate adaptation in novel situations.

neuroscience↗

bioRxiv2020

Using asymmetry to your advantage: learning to acquire and accept external assistance during prolonged split-belt walking

People often adapt their coordination patterns during walking to reduce energy cost by using sources of external assistance in the environment. Adaptation to walking on a split-belt treadmill, where one belt moves faster than the other, provides an opportunity for people to acquire positive work from the treadmill to reduce metabolic cost by modifying where they step on the faster belt. Though we know what people should do to acquire this assistance, this strategy is not observed during typical adaptation studies. Here, by extending the duration of adaptation, we show that people continuously optimize energetic cost by adjusting foot placement to acquire positive work from the treadmill and reduce the work performed by the legs. These results demonstrate that learning to acquire and take advantage of assistance to reduce energetic cost is central in shaping adaptive locomotion, but this process occurs over timescales longer than those used in typical studies.

neuroscience↗

bioRxiv2019

Spasticity reduction in children with cerebral palsy is not associated with reduced energy consumption during walking

BackgroundThe average energy consumption during walking of children with cerebral palsy (CP) is over two times of that of typically developing (TD) children and fatigue is one of the top complaints of children with CP and their families. Spasticity has been theorized to contribute to increased energy consumption during walking in CP, but its role remains unclear.\n\nMethodsWe retrospectively compared the energy consumption of walking in children with diplegic CP before and after selective dorsal rhizotomy (SDR), a surgery that reduces spasticity. A control group of participants with CP who also underwent gait analysis but did not undergo SDR was matched to the SDR group by pre-surgery age, spasticity, and energy consumption. Energy consumption and spasticity were compared at baseline and follow-up for both groups.\n\nFindingsAs expected, the SDR group has a significantly greater decrease (-44%) in spasticity compared to matched peers with CP who did not undergo SDR (-16%, P<0.001). While both groups had a reduction in energy consumption between visits (12 % SDR and 14% no-SDR), there was no difference in the change in energy consumption between groups (P=0.4).\n\nInterpretation: Reducing spasticity did not contribute to greater reductions in energy consumption, suggesting that spasticity has minimal impact on elevated energy consumption during walking for children with CP. Energy consumption and spasticity decrease with age among children with CP. Identifying matched control groups of peers with CP is critical for research involving children with CP to account for changes due to development.\n\nHighlightsO_LIEnergy consumption is not reduced after rhizotomy compared to matched peers\nC_LIO_LISpasticity has minimal contribution to elevated energy during walking\nC_LIO_LIMatched control groups are critical in cerebral palsy research\nC_LI

bioengineering↗

bioRxiv2019

Scaling of inertial delays in terrestrial mammals

As part of its response to a perturbation, an animal often needs to reposition its body. Inertia acts to oppose motion, delaying the completion of the movement--we refer to this additional elapsed time as inertial delay. As animal size increases, muscle moment arms also increase, but muscles are proportionally weaker, and limb inertia is proportionally larger. Consequently, the scaling of inertial delays is complex. Here, we quantify it using two biomechanical models representing common scenarios in animal locomotion: a distributed mass pendulum approximating swing limb repositioning (swing task), and an inverted pendulum approximating whole body posture recovery (posture task). We parameterized the anatomical, muscular, and inertial properties of these models using literature scaling relationships, then determined inertial delay for each task across a large range of movement magnitudes and the full range of terrestrial mammal sizes. We found that inertial delays scaled with an average of M0.28 in the swing task and M0.35 in the posture task across movement magnitudes--larger animals require more absolute time to perform the same movement as small animals. The time available to complete a movement also increases with animal size, but less steeply. Consequently, inertial delays comprise a greater fraction of swing duration and other characteristic movement times in larger animals. We also compared inertial delays to the other component delays within the stimulus-response pathway. As movement magnitude increased, inertial delays exceeded these sensorimotor delays, and this occurred for smaller movements in larger animals. Inertial delays appear to be a challenge for motor control, particularly for bigger movements in larger animals.

neuroscience↗

bioRxiv2018

Energy Optimization is a Major Objective in the Real-Time Control of Step Width in Human Walking

People prefer to move in energetically optimal ways during walking. We have recently found that this preference arises not just through evolution and development, but that the nervous system will continuously optimize step frequency in response to new energetic cost landscapes. Here we test whether energy optimization is also a major objective in the nervous system s real-time control of step width. To accomplish this, we use a device that can reshape the relationship between step width and energetic cost, shifting the energy optimal width wider than that initially preferred. We find that the nervous system doesn t spontaneously initiate energy optimization, but instead requires experience with a lower energetic cost step width. After initiating optimization, people converge towards their new energy optimal width within hundreds of steps and update this as their new preferred width, rapidly returning to it when perturbed away. However, energy optimization was incomplete as this new preferred width was slightly narrower than the energetically optimal width. This suggests that the nervous system may determine its preferred width by optimizing energy simultaneously with other objectives such as stability or maneuverability. Collectively, these findings indicate that the nervous systems of able-bodied people continuously optimize energetic cost to determine preferred step width.

neuroscience↗

bioRxiv2018

Taking advantage of external mechanical work to reduce metabolic cost: the mechanics and energetics of split-belt treadmill walking

In everyday tasks such as walking and running, we exploit the work performed by external sources such as gravity to reduce the work performed by muscles. There has been considerable recent effort to design devices capable of performing mechanical work to improve walking function or reduce effort. The success of these devices relies on the user adapting their natural control strategies to take advantage of assistance provided by the device. Although locomotor adaptation is central to this process, the study of adaptation is often done using approaches that on the surface, seem to have little in common with the use of external assistance. Here, we show that one of the most common approaches for studying this process, which is adaptation to walking on a split-belt treadmill, can be understood from a perspective in which people learn to take advantage of mechanical work performed by the treadmill. During adaptation, people systematically adjust their step lengths, defined as the distance between the feet at heel strike, from one step to the next. Initially, the step length on the slow belt is longer than the step length on the fast belt, measured as a negative step length asymmetry, but people naturally reduce this asymmetry with practice. Here, we demonstrate that these modifications of step length asymmetry allow people to extract positive work from the treadmill belts to reduce the positive work performed by the legs and simultaneously reduce metabolic cost. Moreover, we show that walking with a positive step length asymmetry minimizes metabolic cost, and people prefer to walk in this manner when allowed to select their walking pattern. Together, our results suggest that split-belt adaptation can be interpreted as a process by which people learn to take advantage of mechanical work performed by an external device to improve walking economy.

neuroscience↗

bioRxiv2018

A mechatronic system for studying energy optimization during walking.

A general principle of human movement is that our nervous system is able to learn optimal coordination strategies. However, how our nervous system performs this optimization is not well understood. Here we design, build, and test a mechatronic system to probe the algorithms underlying optimization of energetic cost in walking. The system applies controlled fore-aft forces to a hip-belt worn by a user, decreasing their energetic cost by pulling forward or increasing it by pulling backward. The system controls the forces, and thus energetic cost, as a function of how the user is moving. In testing, we found that the system can quickly, accurately, and precisely apply target forces within a walking step. We next controlled the forces as a function of the users step frequency and found that we could predictably reshape their energetic cost landscape. Finally, we tested whether users adapted their walking in response to the new cost landscapes created by our system, and found that users shifted their step frequency towards the new energetic minima. Our system design appears to be effective for reshaping energetic cost landscapes in human walking to study how the nervous system optimizes movement.

neuroscience↗