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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.

Background Prosthetic feet are spring-like, and their stiffness critically affects the wearer’s stability, comfort, and energetic cost of walking. Despite the importance of stiffness in ambulation, the prescription process often entails testing a limited number of prostheses, which may result in patients receiving a foot with suboptimal mechanics. To understand the resolution with which prostheses should be individually optimized, we sought to characterize below-knee prosthesis users’ psychophysical sensitivity to prosthesis stiffness. Methods We used a novel variable-stiffness ankle prosthesis to measure the repeatability of user-selected preferred stiffness, and implemented a psychophysical experiment to characterize the just noticeable difference of stiffness during locomotion. Results All eight subjects with below-knee amputation exhibited high repeatability in selecting their Preferred Stiffness (mean coefficient of variation: 14.2 ± 1.7%) and were able to correctly identify a 7.7 ± 1.3% change in ankle stiffness (with 75% accuracy). Conclusions This high sensitivity suggests prosthetic foot stiffness should be tuned with a high degree of precision on an individual basis. These results also highlight the need for a pairing of new robotic prescription tools and mechanical characterizations of prosthetic feet.

Lower-limb exoskeletons have the potential to transform the way we move 1 – 14 , but current state-of-the-art controllers cannot accommodate the rich set of possible human behaviours that range from cyclic and predictable to transitory and unstructured. We introduce a task-agnostic controller that assists the user on the basis of instantaneous estimates of lower-limb biological joint moments from a deep neural network. By estimating both hip and knee moments in-the-loop, our approach provided multi-joint, coordinated assistance through our autonomous, clothing-integrated exoskeleton. When deployed during 28 activities, spanning cyclic locomotion to unstructured tasks (for example, passive meandering and high-speed lateral cutting), the network accurately estimated hip and knee moments with an average R 2 of 0.83 relative to ground truth. Further, our approach significantly outperformed a best-case task classifier-based method constructed from splines and impedance parameters. When tested on ten activities (including level walking, running, lifting a 25 lb (roughly 11 kg) weight and lunging), our controller significantly reduced user energetics (metabolic cost or lower-limb biological joint work depending on the task) relative to the zero torque condition, ranging from 5.3 to 19.7%, without any manual controller modifications among activities. Thus, this task-agnostic controller can enable exoskeletons to aid users across a broad spectrum of human activities, a necessity for real-world viability. A task-agnostic controller assists the user on the basis of instantaneous estimates of lower-limb biological joint moments from a deep neural network so exoskeletons can aid users across a broad spectrum of human activities.

The biological ankle dorsiflexes several degrees during swing to provide adequate clearance between the foot and ground, but conventional energy storage and return (ESR) prosthetic feet remain in their neutral position, increasing the risk of toe scuffs and tripping. We present a new prosthetic ankle intended to reduce fall risk by dorsiflexing the ankle joint during swing, thereby increasing the minimum clearance between the foot and ground. Unlike previous approaches to providing swing dorsiflexion such as powered ankles or hydraulic systems with dissipative yielding in stance, our ankle device features a spring-loaded linkage that adopts a neutral angle during stance, allowing ESR, but adopts a dorsiflexed angle during swing. The ankle unit was designed, fabricated, and assessed in level ground walking trials on a unilateral transtibial prosthesis user to experimentally validate its stance and swing phase behaviors. The assessment consisted of three conditions: the ankle in an operational configuration, the ankle in a locked configuration (unable to dorsiflex), and the subject’s daily use ESR prosthesis. When the ankle was operational, minimum foot clearance (MFC) increased by 13 mm relative to the locked configuration and 15 mm relative to his daily use prosthesis. Stance phase energy return was not significantly impacted in the operational configuration. The increase in MFC provided by the passive dorsiflexing ankle prosthesis may be sufficient to decrease the rate of falls experienced by prosthesis users in the real world.

When fitting prosthetic feet, prosthetists fuse information from their visual assessment of patient gait with the patient’s communicated perceptions and preferences. In this study, we sought to simultaneously and independently assess patient and prosthetist preference for prosthetic foot stiffness using a custom variable-stiffness prosthesis. In the first part of the experiment, seven subjects with below-knee amputation walked on the variable-stiffness prosthetic foot set to a randomized stiffness, while several prosthetist subjects simultaneously observed their gait. After each trial, the amputee subjects and prosthetist subjects indicated the change to stiffness that they would prefer (increase or decrease). This paradigm allowed us to simultaneously measure amputee subject and prosthetist subject preferences, and provided a reliability index indicating the consistency of their preferences. In the second part of the experiment, amputee subjects were instructed to communicate verbally with one prosthetist subject to arrive at a mutually preferred stiffness. On average, prosthetist subjects preferred a 26% higher stiffness than amputee subjects ( p  < 0.001), though this depended on the amputee subject ( p  < 0.001). Prosthetist subjects were also considerably less consistent than amputee subjects in their preferences (CV of 5.6% for amputee subjects, CV of 23% for prosthetist subjects; p  = 0.014). Mutual preference seemed to be dictated by the specific patient-prosthetist dynamic, and no clear trends emerged.

Individuals with lower limb amputation experience reduced ankle push-off work in the absence of functional muscles spanning the joint, leading to decreased walking performance. Conventional energy storage and return (ESR) prostheses partially compensate by storing mechanical energy during midstance and returning this energy during the terminal stance phase of gait. These prostheses can provide approximately 30% of the push-off work performed by a healthy ankle–foot during walking. Novel prostheses that return more normative levels of mechanical energy may improve walking performance. In this work, we designed a Decoupled ESR (DESR) prosthesis which stores energy usually dissipated at heel-strike and loading response, and returns this energy during terminal stance, thus increasing the mechanical push-off work done by the prosthesis. This decoupling is achieved by switching between two different cam profiles that produce distinct, nonlinear torque–angle mechanics. The cams automatically interchange at key points in the gait cycle via a custom magnetic switching system. Benchtop characterization demonstrated the successful decoupling of energy storage and return. The DESR mechanism was able to capture energy at heel-strike and loading response, and return it later in the gait cycle, but this recycling was not sufficient to overcome mechanical losses. In addition to its potential for recycling energy, the DESR mechanism also enables unique mechanical customizability, such as dorsiflexion during swing phase for toe clearance, or increasing the rate of energy release at push-off.

Wearable exoskeletons are a promising tool for augmenting balance and reducing fall risk. Recent work suggests that active ankle exoskeletons need to act faster than the human to improve reactive balance control. However, the magnitude of exoskeleton torque that is best for improving reactive balance remains unknown. Drawing from the optimal torque for minimizing metabolic expenditure, we hypothesized that reactive balance would improve with increased exoskeleton torque. Participants wearing bilateral ankle exoskeletons were instructed to maintain standing balance during 15cm backward support-surface perturbations. Three exoskeleton plantarflexion torque conditions were tested: NO (Off), LOW (15Nm), or HIGH (30Nm). LOW torque improved balance performance compared to NO torque ( <0.001), with a 7±3% decrease in peak center of mass (CoM) displacement. Although HIGH torque caused a 9±11% decrease in peak CoM displacement compared to NO torque ( =0.12), it was not significant due to high intersubject variability. Whereas LOW torque decreased peak CoM displacement in all (range: -0.2 to -1.6cm), HIGH torque only decreased it in some (range = 1.2 to -2.6cm). The change in CoM displacement from LOW to HIGH torque was associated with balance ability, quantified by the narrowing beam test (R =0.29, p=0.06), while this relationship didn't meet conventional statistical significance, likely due to the small sample size, it suggests that higher levels of exoskeleton torque may hinder balance performance in individuals with better balance ability. Taken together, more exoskeleton torque is not always better for balance, highlighting a potential need to personalize exoskeleton torque for balance augmentation.

Lower limb exoskeletons show promise to assist human movement, but their utility is limited by controllers designed for discrete, predefined actions in controlled environments, restricting their real-world applicability. We present an uncertainty-aware control framework that enables ankle exoskeletons to operate safely across diverse scenarios by automatically disengaging when encountering unfamiliar movements. Our approach uses an uncertainty estimator to classify movements as similar (in-distribution) or different (out-of-distribution) relative to actions in the training set. We evaluated three architectures (model ensembles, autoencoders, and generative adversarial networks) on an offline dataset and tested the strongest performing architecture (ensemble of gait phase estimators) online. The online test demonstrated the ability of our uncertainty estimator to turn assistance on and off as the user transitioned between in-distribution and out-of-distribution tasks (F1: 89.2). This new framework provides a path for exoskeletons to safely and autonomously support human movement in unstructured, everyday environments.

Lower limb exoskeletons show promise to assist human movement, but their utility is limited by controllers designed for discrete, predefined actions in controlled environments, restricting their real-world applicability. We present an uncertainty-aware control framework that enables ankle exoskeletons to operate safely across diverse scenarios by automatically disengaging when encountering unfamiliar movements. Our approach uses an uncertainty estimator to classify movements as similar (in-distribution) or different (out-of-distribution) relative to actions in the training set. We evaluated three architectures (model ensembles, autoencoders, and generative adversarial networks) on an offline dataset and tested the strongest performing architecture (ensemble of gait phase estimators) online. The online test demonstrated the ability of our uncertainty estimator to turn assistance on and off as the user transitioned between in-distribution and out-of-distribution tasks (F1: 89.2). This new framework provides a path for exoskeletons to safely and autonomously support human movement in unstructured, everyday environments.

Data on the detailed clinical progression of COVID-19 in conjunction with epidemiological and virological characteristics are limited. In this case series, we describe the first 12 US patients confirmed to have COVID-19 from 20 January to 5 February 2020, including 4 patients described previously 1 – 3 . Respiratory, stool, serum and urine specimens were submitted for SARS-CoV-2 real-time reverse-transcription polymerase chain reaction (rRT-PCR) testing, viral culture and whole genome sequencing. Median age was 53 years (range: 21–68); 8 patients were male. Common symptoms at illness onset were cough ( n  = 8) and fever ( n  = 7). Patients had mild to moderately severe illness; seven were hospitalized and demonstrated clinical or laboratory signs of worsening during the second week of illness. No patients required mechanical ventilation and all recovered. All had SARS-CoV-2 RNA detected in respiratory specimens, typically for 2–3 weeks after illness onset. Lowest real-time PCR with reverse transcription cycle threshold values in the upper respiratory tract were often detected in the first week and SARS-CoV-2 was cultured from early respiratory specimens. These data provide insight into the natural history of SARS-CoV-2. Although infectiousness is unclear, highest viral RNA levels were identified in the first week of illness. Clinicians should anticipate that some patients may worsen in the second week of illness. Detailed clinical and virologic characteristics of the first 12 individuals with COVID-19 in the United States from the US Centers for Disease Control and Prevention.