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Surface stiffness of bulk soft tissue in musculoskeletal extremities is important to consider in the design of prosthetics, exoskeletons, and protective gear. This knowledge is also foundational for surgical simulation and clinical interventions leveraging manipulation of the musculoskeletal surfaces. Injuries to musculoskeletal extremities are common and surgical and preventive interventions require interactions between various objects such as surgical tools and support surfaces with tissue boundaries. While a handful of investigations examined the variations in indentation mechanics due to pathology or injury specific sites, a comprehensive analysis across the surfaces of musculoskeletal extremities has not been completed. In this study we examine variations of surface stiffness across 8 sites of the upper and lower arms and legs for 95 subjects using an instrumented ultrasound device. Differences in surface stiffness were observed between gender, activity level, and indentation location groups. The lower arm posterior location had the highest average stiffness (3.89 × 10 -3  MPa/mm), while the lowest stiffness was observed at the upper leg posterior location (0.98 × 10 -3  MPa/mm). The differences between indentation sites were larger in magnitude when compared to differences due to demographics (gender and activity level). However the large ranges of the 95% confidence intervals suggest that an aggregated metric based on population or sub-group may not capture individual variations. This study implicates the motivation to explore tissue composition variations within the indentation sites as well as the potential importance to include variations in surface stiffness during surgical simulations., (Copyright © 2019 Elsevier Ltd. All rights reserved.)

Ultrasound is a popular and affordable imaging modality, but the nature of freehand ultrasound operation leads to unknown applied loads at non-quantifiable angles. The purpose of this paper was to demonstrate an instrumentation strategy for an ultrasound system to measure probe forces and orientation during freehand imaging to characterize the interaction between the probe and soft-tissue as well as enhance repeatability. The instrumentation included a 6-axis load cell, an inertial measurement unit, and an optional sensor for camera-based motion capture. A known method for compensation of the ultrasound probe weight was implemented, and a novel method for temporal synchronization was developed. While load and optical sensing was previously achieved, this paper presents a strategy for potential instrumentation on a variety of ultrasound machines. A key feature was the temporal synchronization, utilizing the electrocardiogram (EKG) feature built-in to the ultrasound. The system was used to perform anatomical imaging of tissue layers of musculoskeletal extremities and imaging during indentation on an in vivo subject and an in vitro specimen. The outcomes of the instrumentation strategy were demonstrated during minimal force and indentation imaging. In short, the system presented robust instrumentation of an existing ultrasound system to fully characterize the probe force, orientation, and optionally its movement during imaging while efficiently synchronizing all data. Researchers may use the instrumentation strategy on any EKG capable ultrasound systems if mechanical characterization of soft tissue or minimization of forces and deformations of tissue during anatomical imaging are desired., (Copyright © 2018 The Authors. Published by Elsevier Ltd.. All rights reserved.)

High plantar pressures have been associated with foot ulceration in people with diabetes, who can experience loss of protective sensation due to peripheral neuropathy. Therefore, characterization of elevated plantar pressure distributions can provide a means of identifying diabetic patients at potential risk of foot ulceration. Plantar pressure distribution classification can also be used to determine suitable preventive interventions, such as the provision of an appropriately designed insole. In the past, emphasis has primarily been placed on the identification of individual focal areas of elevated pressure. The goal of this study was to utilize k-means clustering analysis to identify typical regional peak plantar pressure distributions in a group of 819 diabetic feet. The number of clusters was varied from 2 to 10 to examine the effect on the differentiation and classification of regional peak plantar pressure distributions. As the number of groups increased, so too did the specificity of their pressure distributions: starting with overall low or overall high peak pressure groups and extending to clusters exhibiting several focal peak pressures in different regions of the foot. However, as the number of clusters increased, the ability to accurately classify a given regional peak plantar pressure distribution decreased. The balance between these opposing constraints can be adjusted when assessing patients with feet that are potentially "at risk" or while prescribing footwear to reduce high regional pressures. This analysis provides an understanding of the variability of the regional peak plantar pressure distributions seen within the diabetic population and serves as a guide for the preemptive assessment and prevention of diabetic foot ulcers., (Copyright © 2012 Elsevier Ltd. All rights reserved.)

The variability of spatial and temporal step kinematics have separately been shown to prospectively predict falls by older adults. However, the published literature has not addressed the relative importance of the information related to locomotion control contributed by variability of spatial variables, temporal variables, or both. We conducted a post hoc analysis to determine the extent to which the variability of spatial and temporal step kinematics are independent descriptors of locomotion control in healthy young and older adults. A second purpose of the analysis was to establish the extent to which treadmill walking mimics overground walking using a benchmark for step kinematics. Eighteen young adults and 12 older adults walked at a self-selected velocity on an instrumented treadmill from which step length variability, step width variability and step time variability were computed. Stepwise discriminant analysis correctly classified group membership of 70 percent of the 30 subjects (i.e., young or older adult) using only step width variability (p=0.037, Wilk's lamda=0.854). Step width variability was 70+/-57 percent larger than step length variability (p<0.001). This relationship was similar to that of the benchmark established for overground locomotion. The results suggest that for healthy younger and older adults step width variability is a more meaningful descriptor of locomotion control than step length variability and step time variability. Given the potential clinical impact, further systematic study and improvement of the methods and technology for acquiring step kinematic data are warranted.

Variability of step kinematics has been associated with falls by older adults. However, between-study differences with regard to the number of steps used to compute variability have varied by an order of magnitude. If the number of steps used to compute variability is too low there is the potential for a statistically spurious outcome. On the other hand, for subjects with mobility impairments a protocol requiring too many steps to estimate variability imposes an unnecessary burden on the subjects. We have determined the minimum number of steps needed to estimate the variability of spatial and temporal step kinematics. More than 700 steps were collected during level walking on an instrumented treadmill. Accurate estimation of step kinematic variability required at least 400 steps. The increased error in estimating the mean and standard deviations of the step kinematic variables with too few steps can impose an experimental cost with regard to statistical design considerations. The extent to which translation of these results can be made to the variability of spatial and temporal step kinematics collected during over-ground walking awaits further research.

The practical determination of accurate body segment inertial parameters for the general older adult population remains a problem, especially in estimating these parameters for women and accounting for variations in body type. A method is presented for determining the mass and center of mass location of the body segments of individuals within the general population of older adults. Effects of sex and body type on older adult mass distribution are accounted for using 32 easily obtainable body measurements. The method is based on existing results from different data sources and employs a combination of validated estimation approaches, including: body mass and segment length proportions, linear and nonlinear regression equations, and a mathematical model of the trunk. The method was applied to a validation sample of healthy, community-dwelling older adults (29 men, 50 women). Predicted body mass was 96.7+/-4.8% and 95.7+/-3.7% of measured body mass in the men and women, respectively. The estimates of body segment mass and trunk center of mass location for the sample population approximate those reported in the literature, supporting the validity of the described method. By producing practical, subject-specific estimates of body segment inertial parameters, the method should allow more accurate biomechanical analyses of the older adult population.

The purpose of the present study was to induce slips in healthy subjects as a means to determine if recovery from an induced slip is possible under conditions in which the displacements and velocities of the slipping foot exceed the generally accepted limits of 10cm and 50cm/s, respectively, and to determine if there are gait-related variables that predispose an individual to falling after a slip. Thirty-three young and barefoot adults, protected by an instrumented safety harness, were subjected to a single slipping trial following a series of unperturbed walking trials. The slip was induced when the bare foot contacted a vinyl sheet coated with mineral oil. Lower extremity kinematics were acquired using a video-based motion capture system. Fourteen and 12 subjects could be unambiguously categorized as having fallen or recovered, respectively. Four variables demonstrated significant between-group differences and two were used to compute the probability of the slip outcome using logistic regression. The variables were the displacement of the foot during the slip and the angle of the shank relative to the ground at the instant of ground contact just prior to the slip. Separate univariate logistic regressions using each variable were significant and correctly classified about 70% of the slip outcomes. The results demonstrated that previously published values for the displacement and velocity of the slipping foot, 10cm and 50cm/s, respectively, may not accurately represent the upper limits beyond which recovery is not possible. The results also demonstrated that heel-strike angle, reflective of stride length, exerts a significant influence on the outcome of a slip.