Hemiparesis, defined as unilateral muscle weakness, often occurs in people post-stroke or people with cerebral palsy, however it is difficult to understand how this hemiparesis affects movement ...patterns as it often presents alongside a variety of other neuromuscular impairments. Predictive musculoskeletal modeling presents an opportunity to investigate how impairments affect gait performance assuming a particular cost function. Here, we use predictive simulation to quantify the spatiotemporal asymmetries and changes to metabolic cost that emerge when muscle strength is unilaterally reduced and how reducing spatiotemporal symmetry affects metabolic cost. We modified a 2-D musculoskeletal model by uniformly reducing the peak isometric muscle force unilaterally. We then solved optimal control simulations of walking across a range of speeds by minimizing the sum of the cubed muscle excitations. Lastly, we ran additional optimizations to test if reducing spatiotemporal asymmetry would result in an increase in metabolic cost. Our results showed that the magnitude and direction of effort-optimal spatiotemporal asymmetries depends on both the gait speed and level of weakness. Also, the optimal speed was 1.25 m/s for the symmetrical and 20% weakness models but slower (1.00 m/s) for the 40% and 60% weakness models, suggesting that hemiparesis can account for a portion of the slower gait speed seen in people with hemiparesis. Modifying the cost function to minimize spatiotemporal asymmetry resulted in small increases (~4%) in metabolic cost. Overall, our results indicate that spatiotemporal asymmetry may be optimal for people with hemiparesis. Additionally, the effect of speed and the level of weakness on spatiotemporal asymmetry may help explain the well-known heterogenous distribution of spatiotemporal asymmetries observed in the clinic. Future work could extend our results by testing the effects of other neuromuscular impairments on optimal gait strategies, and therefore build a more comprehensive understanding of the gait patterns observed in clinical populations.
Age-related gait changes may play a critical role in functional limitations of older adults. Despite sizable interest in determining how age alters walking mechanics, small sample sizes and varied ...outcome measures have precluded a comprehensive understanding of the impact of age on lower extremity joint kinematics and kinetics.
The aim of this study was to perform a systematic review and meta-analysis of the aging gait mechanics literature.
The overall standardized effect of age on walking mechanics was computed for 29 studies (200 standardized effects). To account for variation in reported outcome variables, analyses were carried out for comparisons between young and older adult results using all discrete kinematic or kinetic variables reported for the ankle, knee, or hip. Different variables reported for a given joint were then analyzed as separate categorical moderators.
The overall standardized effect of age was large for ground reaction forces, moderate for ankle and small for knee and hip kinematics and ankle and hip kinetics. When the analysis was restricted to studies with similar or matched walking speed, the standardized effects of age remained similar except for hip power generation and knee kinematic variables.
The results of this meta-analysis provide evidence to support moderate standardized effects, with and without consideration of walking speeds, for changes in lower extremity kinematics, joint moments and powers at the ankle, and ground reaction forces. The standardized effects of age for knee mechanics are less conclusive and would benefit from further research.
•Meta-analysis examining 30years of gait biomechanics comparing age groups•Results support the hypothesis that ankle function diminishes with age.•Older adults display altered ankle and hip kinematics through gait cycle.•Propulsive ankle kinetics and ground reaction forces are decreased in older adults.•Differences in knee kinematics are more apparent when walking speeds are matched.
As medical imaging enters its information era and presents rapidly increasing needs for big data analytics, robust pooling and harmonization of imaging data across diverse cohorts with varying ...acquisition protocols have become critical. We describe a comprehensive effort that merges and harmonizes a large-scale dataset of 10,477 structural brain MRI scans from participants without a known neurological or psychiatric disorder from 18 different studies that represent geographic diversity. We use this dataset and multi-atlas-based image processing methods to obtain a hierarchical partition of the brain from larger anatomical regions to individual cortical and deep structures and derive age trends of brain structure through the lifespan (3–96 years old). Critically, we present and validate a methodology for harmonizing this pooled dataset in the presence of nonlinear age trends. We provide a web-based visualization interface to generate and present the resulting age trends, enabling future studies of brain structure to compare their data with this reference of brain development and aging, and to examine deviations from ranges, potentially related to disease.
•Multi-site harmonization method that pools volumetric data from 18 studies, controlling for nonlinear age effects.•Resulting dataset covers ages 3 to 96 and used to derive age trends of brain structure through the lifespan.•Interactive visualization tool provided for exploring age trends and comparing new data.
Predictive simulation based on dynamic optimization using musculoskeletal models is a powerful approach for studying human gait. Predictive musculoskeletal simulation may be used for a variety of ...applications from designing assistive devices to testing theories of motor control. However, the underlying cost function for the predictive optimization is unknown and is generally assumed a priori. Alternatively, the underlying cost function can be determined from among a family of possible cost functions, representing an inverse optimal control problem that may be solved using a bilevel optimization approach. In this study, a nested evolutionary approach is proposed to solve the bilevel optimization problem. The lower level optimization is solved by a direct collocation method, and the upper level is solved by a genetic algorithm. We demonstrate our approach to solve different bilevel optimization problems, including finding the weights among three common performance criteria in the cost function for normal human walking. The proposed approach was found to be effective at solving the bilevel optimization problems. This approach should provide practical utility in designing assistive devices to aid mobility, and could yield insights about the control of human walking.
Musculoskeletal modeling is currently a preferred method for estimating the muscle forces that underlie observed movements. However, these estimates are sensitive to a variety of assumptions and ...uncertainties, which creates difficulty when trying to interpret the muscle forces from musculoskeletal simulations. Here, we describe an approach that uses Bayesian inference to identify plausible ranges of muscle forces for a simple motion while representing uncertainty in the measurement of the motion and the objective function used to solve the muscle redundancy problem.
We generated a reference elbow flexion-extension motion and computed a set of reference forces that would produce the motion while minimizing muscle excitations cubed via OpenSim Moco. We then used a Markov Chain Monte Carlo (MCMC) algorithm to sample from a posterior probability distribution of muscle excitations that would result in the reference elbow motion. We constructed a prior over the excitation parameters which down-weighted regions of the parameter space with greater muscle excitations. We used muscle excitations to find the corresponding kinematics using OpenSim, where the error in position and velocity trajectories (likelihood function) was combined with the sum of the cubed muscle excitations integrated over time (prior function) to compute the posterior probability density.
We evaluated the muscle forces that resulted from the set of excitations that were visited in the MCMC chain (seven parallel chains, 500,000 iterations per chain). The estimated muscle forces compared favorably with the reference forces generated with OpenSim Moco, while the elbow angle and velocity from MCMC matched closely with the reference (average RMSE for elbow angle = 2°; and angular velocity = 32°/s). However, our rank plot analyses and potential scale reduction statistics, which we used to evaluate convergence of the algorithm, indicated that the chains did not fully mix.
While the results from this process are a promising step towards characterizing uncertainty in muscle force estimation, the computational time required to search the solution space with, and the lack of MCMC convergence indicates that further developments in MCMC algorithms are necessary for this process to become feasible for larger-scale models.
NASA’s InSight mission to Mars will measure seismic signals to determine the planet’s interior structure. These highly sensitive seismometers are susceptible to corruption of their measurements by ...environmental changes. Magnetic fields, atmosphere pressure changes, and local winds can all induce apparent changes in the seismic records that are not due to propagating ground motions. Thus, InSight carries a set of sensors called the Auxiliary Payload Sensor Suite (APSS) which includes a magnetometer, an atmospheric pressure sensor, and a pair of wind and air temperature sensors. In the case of the magnetometer, knowledge of the amplitude of the fluctuating magnetic field at the InSight lander will allow the separation of seismic signals from potentially interfering magnetic signals of either natural or spacecraft origin. To acquire such data, a triaxial fluxgate magnetometer was installed on the deck of the lander to obtain magnetic records at the same cadence as the seismometer. Similarly, a highly sensitive pressure sensor is carried by InSight to enable the removal of local ground-surface tilts due to advecting pressure perturbations. Finally, the local winds (speed and direction) and air temperature are estimated using a hot-film wind sensor with heritage from REMS on the Curiosity rover. When winds are too high, seismic signals can be ignored or discounted. Herein we describe the APSS sensor suite, the test programs for its components, and the possible additional science investigations it enables.
Humans walk with an upright posture on extended limbs during stance and with a double-peaked vertical ground reaction force. Our closest living relatives, chimpanzees, are facultative bipeds that ...walk with a crouched posture on flexed, abducted hind limbs and with a single-peaked vertical ground reaction force. Differences in human and bipedal chimpanzee three-dimensional (3D) kinematics have been well quantified, yet it is unclear what the independent effects of using a crouched posture are on 3D gait mechanics for humans, and how they compare with chimpanzees. Understanding the relationships between posture and gait mechanics, with known differences in morphology between species, can help researchers better interpret the effects of trait evolution on bipedal walking. We quantified pelvis and lower limb 3D kinematics and ground reaction forces as humans adopted a series of upright and crouched postures and compared them with data from bipedal chimpanzee walking. Human crouched-posture gait mechanics were more similar to that of bipedal chimpanzee gait than to normal human walking, especially in sagittal plane hip and knee angles. However, there were persistent differences between species, as humans walked with less transverse plane pelvis rotation, less hip abduction, and greater peak anterior-posterior ground reaction force in late stance than chimpanzees. Our results suggest that human crouched-posture walking reproduces only a small subset of the characteristics of 3D kinematics and ground reaction forces of chimpanzee walking, with the remaining differences likely due to the distinct musculoskeletal morphologies of humans and chimpanzees.
Abstract
Background
The Study of Muscle, Mobility and Aging (SOMMA) aims to understand the biological basis of many facets of human aging, with a focus on mobility decline, by creating a unique ...platform of data, tissues, and images.
Methods
The multidisciplinary SOMMA team includes 2 clinical centers (University of Pittsburgh and Wake Forest University), a biorepository (Translational Research Institute at Advent Health), and the San Francisco Coordinating Center (California Pacific Medical Center Research Institute). Enrollees were age ≥70 years, able to walk ≥0.6 m/s (4 m); able to complete 400 m walk, free of life-threatening disease, and had no contraindications to magnetic resonance or tissue collection. Participants are followed with 6-month phone contacts and annual in-person exams. At baseline, SOMMA collected biospecimens (muscle and adipose tissue, blood, urine, fecal samples); a variety of questionnaires; physical and cognitive assessments; whole-body imaging (magnetic resonance and computed tomography); accelerometry; and cardiopulmonary exercise testing. Primary outcomes include change in walking speed, change in fitness, and objective mobility disability (able to walk 400 m in 15 minutes and change in 400 m speed). Incident events, including hospitalizations, cancer diagnoses, fractures, and mortality are collected and centrally adjudicated by study physicians.
Results
SOMMA exceeded its goals by enrolling 879 participants, despite being slowed by the COVID-19 pandemic: 59.2% women; mean age 76.3 ± 5.0 years (range 70–94); mean walking speed 1.04 ± 0.20 m/s; 15.8% identify as other than Non-Hispanic White. Over 97% had data for key measurements.
Conclusions
SOMMA will provide the foundation for discoveries in the biology of human aging and mobility.
The field of point-of-care ultrasound (POCUS) has advanced in recent decades due to the benefits it holds for medical providers. However, aspiring POCUS practitioners require adequate training. ...Unfortunately, there remains a paucity of resources to deliver this training, particularly in rural and underserved areas. Despite these barriers, calls for POCUS training in undergraduate medical education are growing, and many medical schools now deliver some form of POCUS education. Our program lacked POCUS training; therefore, we developed and implemented a POCUS curriculum for our first-year medical students.
We developed a POCUS curriculum for first year medical students in a rural medically underserved region of the United States. To evaluate our course, we measured learning outcomes, self-reported confidence in a variety of POCUS domains, and gathered feedback on the course with a multi-modal approach: an original written pre- and post-test, survey tool, and semi-structured interview protocol, respectively.
Student (n=24) knowledge of POCUS significantly increased (pre-test average score = 55%, post-test average score = 79%, P<0.0001), and the course was well received based on student survey and interview feedback. In addition, students reported increased confidence toward a variety of knowledge and proficiency domains in POCUS use and their future clinical education and practice.
Despite a lack of consensus in POCUS education, existing literature describes many curricular designs across institutions. We leveraged a combination of student initiatives, online resources, remote collaborations, local volunteers, and faculty development to bring POCUS to our institution in a rural and medically underserved region. Moreover, we demonstrate positive learning and experiential outcomes that may translate to improved outcomes in students' clinical education and practice. Further research is needed to evaluate the psychomotor skills, broader learning outcomes, and clinical performance of students who take part in our POCUS course.
•We recommend measuring walking speed over 6 m plus acceleration and deceleration zones.•For replication, studies should report methods for estimating preferred walking speed.•Preferred walking speed ...is more affected by measurement protocol than by testing site.•Acceleration and deceleration zones allowed for similar speeds across conditions.•Participants walked slower for 400 m than for shorter, straightaway distances.
Walking speed influences a variety of typical outcome measures in gait analysis. Many researchers use a participant’s preferred walking speed (PWS) during gait analysis with a goal of trying to capture how a participant would typically walk. However, the best practices for estimating PWS and the impact of laboratory size and walk distance are still unclear.
Is measured PWS consistent across different distances and between two laboratory sites?
Participants walked overground at a “comfortable speed” for six different conditions with either dynamic (4, 6, 10, and 400 m) or static (4 and 10 m) starts and stops at two different data collection sites. Repeated measures ANOVA with Bonferroni corrections were used to test for differences between conditions and sites.
Participants walked significantly faster in the 4, 6, and 10 m dynamic conditions than in the 400 m condition. On average, participants walked slower in the static trials than the dynamic trials of the same distance. There was a significant interaction of lab and condition and so results were examined within each lab. Across both labs, we found that the 4 and 10 m dynamic conditions were not different than the 6 m dynamic condition at both sites, while other tests did not provide consistent results at both sites.
We recommend researchers use a 6 m distance with acceleration and deceleration zones to reliably test for PWS across different laboratories. Given some of the differences found between conditions that varied by site, we also emphasize the need to report the test environment and methods used to estimate PWS in all future studies so that the methods can be replicated between studies.
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