Informing Ankle-Foot Prosthesis Prescription through Haptic Emulation of Candidate Devices

Understanding patient preference in prosthetic ankle stiffness

BACKGROUND

User preference has the potential to facilitate the design, control, and prescription of prostheses, but we do not yet understand which physiological factors drive preference, or if preference is associated with clinical benefits.

METHODS

Subjects with unilateral below-knee amputation walked on a custom variable-stiffness prosthetic ankle and manipulated a dial to determine their preferred prosthetic ankle stiffness at three walking speeds. We evaluated anthropomorphic, metabolic, biomechanical, and performance-based descriptors at stiffness levels surrounding each subject's preferred stiffness.

RESULTS

Subjects preferred lower stiffness values at their self-selected treadmill walking speed, and elected to walk faster overground with ankle stiffness at or above their preferred stiffness. Preferred stiffness maximized the kinematic symmetry between prosthetic and unaffected joints, but was not significantly correlated with body mass or metabolic rate.

CONCLUSION

These results imply that some physiological factors are weighted more heavily when determining preferred stiffness, and that preference may be associated with clinically relevant improvements in gait.

A hip–knee–ankle exoskeleton emulator for studying gait assistance

Lower-limb exoskeletons could improve the mobility of people with disabilities, older adults, workers, first responders, and military personnel. Despite recent advances, few products are commercially available and exoskeleton research is still often limited by hardware constraints. Many promising multi-joint assistance strategies, especially those with high-torque and high-power components, have yet to be tested because they are beyond the capabilities of current devices. To study these untested assistance strategies, we present a hip–knee–ankle exoskeleton emulator that can apply high torques and powers that match or exceed those observed in uphill running. The system has powerful off-board motors that actuate a 13.5 kg exoskeleton end effector worn by the user. It can apply up to 200 Nm of torque in hip flexion, hip extension, and ankle plantarflexion, 250 Nm of torque in knee extension, and 140 Nm of torque in knee flexion, with over 4.5 kW of power at each joint and a closed-loop torque bandwidth of at least 18 Hz in each direction of actuation. The exoskeleton is compliant in unactuated directions, adjustable for a wide range of users and comfortable during walking and running. When paired with human-in-the-loop optimization, we expect that this system will identify new assistance strategies to improve human mobility. A complete computer-aided design (CAD) model of the exoskeleton and a bill of materials are included and available for download.

Predictive Simulation of Human Walking Augmented by a Powered Ankle Exoskeleton

The human ankle provides significant positive power during the stance phase of walking, which has resulted in studies focusing on methods to reduce the energetic walking cost by augmenting the ankle with exoskeletons. Recently, a few devices have successfully reduced the metabolic cost of walking by replacing part of the biological ankle plantar flexor torque. Despite these achievements, development of assistive ankle devices remains challenging, partly because the current practice of design and control of powered exoskeletons is highly time and effort consuming, which prevents quickly exploring different design and control parameters. Predictive simulations using musculoskeletal models coupled with robotic devices may facilitate the process of design and control of assistive devices. In this study, we simulate human walking augmented by a powered ankle exoskeleton. The walking problem was formulated as a predictive dynamic optimization in which both the optimal assistive device torque and the gait were solved simultaneously. Cases with exoskeletons assisting one ankle and both ankles were considered. The results showed that the energetic cost of walking could be reduced by 45% with one ankle augmented, and by 52% with both ankles augmented. This study contributes towards the goal of providing optimal assistive torque through external devices and theoretical peak reductions that could be expected from such devices.

Human-in-the-loop Bayesian optimization of wearable device parameters

The increasing capabilities of exoskeletons and powered prosthetics for walking assistance have paved the way for more sophisticated and individualized control strategies. In response to this opportunity, recent work on human-in-the-loop optimization has considered the problem of automatically tuning control parameters based on realtime physiological measurements. However, the common use of metabolic cost as a performance metric creates significant experimental challenges due to its long measurement times and low signal-to-noise ratio. We evaluate the use of Bayesian optimization-a family of sample-efficient, noise-tolerant, and global optimization methods-for quickly identifying near-optimal control parameters. To manage experimental complexity and provide comparisons against related work, we consider the task of minimizing metabolic cost by optimizing walking step frequencies in unaided human subjects. Compared to an existing approach based on gradient descent, Bayesian optimization identified a near-optimal step frequency with a faster time to convergence (12 minutes, p < 0.01), smaller inter-subject variability in convergence time (± 2 minutes, p < 0.01), and lower overall energy expenditure (p < 0.01).

Sensitivity of biomechanical outcomes to independent variations of hindfoot and forefoot stiffness in foot prostheses

Many studies have reported the effects of different foot prostheses on gait, but most results cannot be generalized because the prostheses' properties are seldom reported. We varied hindfoot and forefoot stiffness in an experimental foot prosthesis, in increments of 15N/mm, and tested the parametric effects of these variations on treadmill walking in unilateral transtibial amputees, at speeds from 0.7 to 1.5m/s. We computed outcomes such as prosthesis energy return, center of mass (COM) mechanics, ground reaction forces, and joint mechanics, and computed their sensitivity to component stiffness. A stiffer hindfoot led to reduced prosthesis energy return, increased ground reaction force (GRF) loading rate, and greater stance-phase knee flexion and knee extensor moment. A stiffer forefoot resulted in reduced prosthetic-side ankle push-off and COM push-off work, and increased knee extension and knee flexor moment in late stance. The sensitivity parameters obtained from these tests may be useful in clinical prescription and further research into compensatory mechanisms of joint function.

Continuous sweep versus discrete step protocols for studying effects of wearable robot assistance magnitude

BACKGROUND

Different groups developed wearable robots for walking assistance, but there is still a need for methods to quickly tune actuation parameters for each robot and population or sometimes even for individual users. Protocols where parameters are held constant for multiple minutes have traditionally been used for evaluating responses to parameter changes such as metabolic rate or walking symmetry. However, these discrete protocols are time-consuming. Recently, protocols have been proposed where a parameter is changed in a continuous way. The aim of the present study was to compare effects of continuously varying assistance magnitude with a soft exosuit against discrete step conditions.

METHODS

Seven participants walked on a treadmill wearing a soft exosuit that assists plantarflexion and hip flexion. In Continuous-up, peak exosuit ankle moment linearly increased from approximately 0 to 38% of biological moment over 10 min. Continuous-down was the opposite. In Discrete, participants underwent five periods of 5 min with steady peak moment levels distributed over the same range as Continuous-up and Continuous-down. We calculated metabolic rate for the entire Continuous-up and Continuous-down conditions and the last 2 min of each Discrete force level. We compared kinematics, kinetics and metabolic rate between conditions by curve fitting versus peak moment.

RESULTS

Reduction in metabolic rate compared to Powered-off was smaller in Continuous-up than in Continuous-down at most peak moment levels, due to physiological dynamics causing metabolic measurements in Continuous-up and Continuous-down to lag behind the values expected during steady-state testing. When evaluating the average slope of metabolic reduction over the entire peak moment range there was no significant difference between Continuous-down and Discrete. Attempting to correct the lag in metabolics by taking the average of Continuous-up and Continuous-down removed all significant differences versus Discrete. For kinematic and kinetic parameters, there were no differences between all conditions.

CONCLUSIONS

The finding that there were no differences in biomechanical parameters between all conditions suggests that biomechanical parameters can be recorded with the shortest protocol condition (i.e. single Continuous directions). The shorter time and higher resolution data of continuous sweep protocols hold promise for the future study of human interaction with wearable robots.