Evaluation of Error-State Kalman Filter Method for Estimating Human Lower-Limb Kinematics during Various Walking Gaits.

Inertial measurement units (IMUs) offer an attractive way to study human lower-limb kinematics without traditional laboratory constraints. We present an error-state Kalman filter method to estimate 3D joint angles, joint angle ranges of motion, stride length, and step width using data from an array of seven body-worn IMUs. Importantly, this paper contributes a novel joint axis measurement correction that reduces joint angle drift errors without assumptions of strict hinge-like joint behaviors of the hip and knee. We evaluate the method compared to two optical motion capture methods on twenty human subjects performing six different types of walking gait consisting of forward walking (at three speeds), backward walking, and lateral walking (left and right). For all gaits, RMS differences in joint angle estimates generally remain below 5 degrees for all three ankle joint angles and for flexion/extension and abduction/adduction of the hips and knees when compared to estimates from reflective markers on the IMUs. Additionally, mean RMS differences in estimated stride length and step width remain below 0.13 m for all gait types, except stride length during slow walking. This study confirms the method's potential for non-laboratory based gait analysis, motivating further evaluation with IMU-only measurements and pathological gaits.

A Pilot Study Comparing the Effects of Concurrent and Terminal Visual Feedback on Standing Balance in Older Adults.

While balance training with concurrent feedback has been shown to improve real-time balance in older adults, terminal feedback may simplify implementation outside of clinical settings. Similarly, visual feedback is particularly well-suited for use outside the clinic as it is relatively easily understood and accessible via ubiquitous mobile devices (e.g., smartphones) with little additional peripheral equipment. However, differences in the effects of concurrent and terminal visual feedback are not yet well understood. We therefore performed a pilot study that directly compared the immediate effects of concurrent and terminal visual feedback as a first and necessary step in the future design of visual feedback technologies for balance training outside of clinical settings. Nineteen healthy older adults participated in a single balance training session during which they performed 38 trials of a single balance exercise including trials with concurrent, terminal or no visual feedback. Analysis of trunk angular position and velocity features recorded via an inertial measurement unit indicated that sway angles decreased with training regardless of feedback type, but sway velocity increased with concurrent feedback and decreased with terminal feedback. After removing feedback, training with either feedback type yielded decreased mean velocity, but only terminal feedback yielded decreased sway angles. Consequently, this study suggests that, for older adults, terminal visual feedback may be a viable alternative to concurrent visual feedback for short duration single-task balance training. Terminal feedback provided using ubiquitous devices should be further explored for balance training outside of clinical settings.

Error-state Kalman filter for lower-limb kinematic estimation: Evaluation on a 3-body model.

Human lower-limb kinematic measurements are critical for many applications including gait analysis, enhancing athletic performance, reducing or monitoring injury risk, augmenting warfighter performance, and monitoring elderly fall risk, among others. We present a new method to estimate lower-limb kinematics using an error-state Kalman filter that utilizes an array of body-worn inertial measurement units (IMUs) and four kinematic constraints. We evaluate the method on a simplified 3-body model of the lower limbs (pelvis and two legs) during walking using data from simulation and experiment. Evaluation on this 3-body model permits direct evaluation of the ErKF method without several confounding error sources from human subjects (e.g., soft tissue artefacts and determination of anatomical frames). RMS differences for the three estimated hip joint angles all remain below 0.2 degrees compared to simulation and 1.4 degrees compared to experimental optical motion capture (MOCAP). RMS differences for stride length and step width remain within 1% and 4%, respectively compared to simulation and 7% and 5%, respectively compared to experiment (MOCAP). The results are particularly important because they foretell future success in advancing this approach to more complex models for human movement. In particular, our future work aims to extend this approach to a 7-body model of the human lower limbs composed of the pelvis, thighs, shanks, and feet.

Quantifying warfighter performance during a bounding rush (prone-sprinting-prone) maneuver.

A single sacrum mounted inertial measurement unit (IMU) was employed to analyze warfighter performance on a bounding rush (prone-sprinting-prone) task. Thirty-nine participants (23M/16F) performed a bounding rush task consisting of four bounding rush cycles. The sacrum mounted IMU recorded angular velocity and acceleration data were used to provide estimates of sacral velocity and position. Individual rush cycles were parsed into three principal movement phases; namely, the get up, sprint, and get down phases. The timing of each phase was analyzed, averaged for each participant, and compared to the overall rush cycle time using regression analysis. A cluster analysis further reveals differences between high and low performers. Get down time was most predictive of bounding rush performance (R2 = 0.75) followed by get up time (R2 = 0.58) and sprint time (R2 = 0.40). Comparing high and low performers, the get down time exhibited nearly twice the effect on mean rush cycle time compared to get up time (effect size of -2.61 to -1.46, respectively). Overall, this IMU-based method reveals key features of the bounding rush that govern performance. Consequently, this objective method may support future training regimens and performance standards for military recruits, and parallel applications for athletes.

Determining anatomical frames via inertial motion capture: A survey of methods.

Despite the exponential growth in using inertial measurement units (IMUs) for biomechanical studies, future growth in "inertial motion capture" is stymied by a fundamental challenge - how to estimate the orientation of underlying bony anatomy using skin-mounted IMUs. This challenge is of paramount importance given the need to deduce the orientation of the bony anatomy to estimate joint angles. This paper systematically surveys a large number (N = 112) of studies from 2000 to 2018 that employ four broad categories of methods to address this challenge across a range of body segments and joints. We categorize these methods as: (1) Assumed Alignment methods, (2) Functional Alignment methods, (3) Model Based methods, and (4) Augmented Data methods. Assumed Alignment methods, which are simple and commonly used, require the researcher to visually align the IMU sense axes with the underlying anatomical axes. Functional Alignment methods, also commonly used, relax the need for visual alignment but require the subject to complete prescribed movements. Model Based methods further relax the need for prescribed movements but instead assume a model for the joint. Finally, Augmented Data methods shed all of the above assumptions, but require data from additional sensors. Significantly different estimates of the underlying anatomical axes arise both across and within these categories, and to a degree that renders it difficult, if not impossible, to compare results across studies. Consequently, a significant future need remains for creating and adopting a standard for defining anatomical axes via inertial motion capture to fully realize this technology's potential for biomechanical studies.

How the phage T4 injection machinery works including energetics, forces, and dynamic pathway.

The virus bacteriophage T4, from the family Myoviridae, employs an intriguing contractile injection machine to inject its genome into the bacterium Escherichia coli Although the atomic structure of phage T4 is largely understood, the dynamics of its injection machinery remains unknown. This study contributes a system-level model describing the nonlinear dynamics of the phage T4 injection machinery interacting with a host cell. The model employs a continuum representation of the contractile sheath using elastic constants inferred from atomistic molecular-dynamics (MD) simulations. Importantly, the sheath model is coupled to component models representing the remaining structures of the virus and the host cell. The resulting system-level model captures virus-cell interactions as well as competing energetic mechanisms that release and dissipate energy during the injection process. Simulations reveal the dynamical pathway of the injection process as a "contraction wave" that propagates along the sheath, the energy that powers the injection machinery, the forces responsible for piercing the host cell membrane, and the energy dissipation that controls the timescale of the injection process. These results from the model compare favorably with the available (but limited) experimental measurements.

Effect of IMU Design on IMU-Derived Stride Metrics for Running.

Researchers employ foot-mounted inertial measurement units (IMUs) to estimate the three-dimensional trajectory of the feet as well as a rich array of gait parameters. However, the accuracy of those estimates depends critically on the limitations of the accelerometers and angular velocity gyros embedded in the IMU design. In this study, we reveal the effects of accelerometer range, gyro range, and sampling frequency on gait parameters (e.g., distance traveled, stride length, and stride angle) estimated using the zero-velocity update (ZUPT) method. The novelty and contribution of this work are that it: (1) quantifies these effects at mean speeds commensurate with competitive distance running (up to 6.4 m/s); (2) identifies the root causes of inaccurate foot trajectory estimates obtained from the ZUPT method; and (3) offers important engineering recommendations for selecting accurate IMUs for studying human running. The results demonstrate that the accuracy of the estimated gait parameters generally degrades with increased mean running speed and with decreased accelerometer range, gyro range, and sampling frequency. In particular, the saturation of the accelerometer and/or gyro induced during running for some IMU designs may render those designs highly inaccurate for estimating gait parameters.

Body-worn IMU array reveals effects of load on performance in an outdoor obstacle course.

This study introduces a new method to understand how added load affects human performance across a broad range of athletic tasks (ten obstacles) embedded in an outdoor obstacle course. The method employs an array of wearable inertial measurement units (IMUs) to wirelessly record the movements of major body segments to derive obstacle-specific metrics of performance. The effects of load are demonstrated on (N = 22) participants who each complete the obstacle course under four conditions including unloaded (twice) and with loads of 15% and 30% of their body weight (a total of 88 trials across the group of participants). The IMU-derived performance metrics reveal marked degradations in performance with increasing load across eight of the ten obstacles. Overall, this study demonstrates the significant potential in using this wearable technology to evaluate human performance across multiple tasks and, simultaneously, the adverse effects of body-borne loads on performance. The study addresses a major need of military organizations worldwide that frequently employ standardized obstacle courses to understand how added loads influence warfighter performance. Importantly, the findings and conclusions drawn from IMU data would not be possible using traditional timing metrics used to evaluate task performance.

Human crawling performance and technique revealed by inertial measurement units.

Human crawling performance and technique are of broad interest to roboticists, biomechanists, and military personnel. This study explores the variables that define crawling performance in the context of an outdoor obstacle course used by military organizations worldwide to evaluate the effects of load and personal equipment on warfighter performance. Crawling kinematics, measured from four body-worn inertial measurement units (IMUs) attached to the upper arms and thighs, are recorded for thirty-three participants. The IMU data is distilled to four metrics of crawling performance; namely, crawl speed, crawl stride time, ipsilateral limb coordination, and contralateral limb coordination. We hypothesize that higher performance (as identified by higher crawl speeds) is associated with more coordinated limbs and lower stride times. A cluster analysis groups participants into high and low performers exhibiting statistically significant differences across the four performance metrics. In particular, high performers exhibit superior limb coordination associated with a "diagonal gait" in which contralateral limbs move largely in-phase to produce faster crawl speeds and shorter crawl stride times. In contrast, low performers crawl at slower speeds with longer crawl stride times and less limb coordination. Beyond these conclusions, a major contribution of this study is a method for deploying wearable IMUs to study crawling in contextually relevant (i.e. non-laboratory) environments.

Load-embedded inertial measurement unit reveals lifting performance.

Manual lifting of loads arises in many occupations as well as in activities of daily living. Prior studies explore lifting biomechanics and conditions implicated in lifting-induced injuries through laboratory-based experimental methods. This study introduces a new measurement method using load-embedded inertial measurement units (IMUs) to evaluate lifting tasks in varied environments outside of the laboratory. An example vertical load lifting task is considered that is included in an outdoor obstacle course. The IMU data, in the form of the load acceleration and angular velocity, is used to estimate load vertical velocity and three lifting performance metrics: the lifting time (speed), power, and motion smoothness. Large qualitative differences in these parameters distinguish exemplar high and low performance trials. These differences are further supported by subsequent statistical analyses of twenty three trials (including a total of 115 total lift/lower cycles) from fourteen healthy participants. Results reveal that lifting time is strongly correlated with lifting power (as expected) but also correlated with motion smoothness. Thus, participants who lift rapidly do so with significantly greater power using motions that minimize motion jerk.

Quantifying performance on an outdoor agility drill using foot-mounted inertial measurement units.

Running agility is required for many sports and other physical tasks that demand rapid changes in body direction. Quantifying agility skill remains a challenge because measuring rapid changes of direction and quantifying agility skill from those measurements are difficult to do in ways that replicate real task/game play situations. The objectives of this study were to define and to measure agility performance for a (five-cone) agility drill used within a military obstacle course using data harvested from two foot-mounted inertial measurement units (IMUs). Thirty-two recreational athletes ran an agility drill while wearing two IMUs secured to the tops of their athletic shoes. The recorded acceleration and angular rates yield estimates of the trajectories, velocities and accelerations of both feet as well as an estimate of the horizontal velocity of the body mass center. Four agility performance metrics were proposed and studied including: 1) agility drill time, 2) horizontal body speed, 3) foot trajectory turning radius, and 4) tangential body acceleration. Additionally, the average horizontal ground reaction during each footfall was estimated. We hypothesized that shorter agility drill performance time would be observed with small turning radii and large tangential acceleration ranges and body speeds. Kruskal-Wallis and mean rank post-hoc statistical analyses revealed that shorter agility drill performance times were observed with smaller turning radii and larger tangential acceleration ranges and body speeds, as hypothesized. Moreover, measurements revealed the strategies that distinguish high versus low performers. Relative to low performers, high performers used sharper turns, larger changes in body speed (larger tangential acceleration ranges), and shorter duration footfalls that generated larger horizontal ground reactions during the turn phases. Overall, this study advances the use of foot-mounted IMUs to quantify agility performance in contextually-relevant settings (e.g., field of play, training facilities, obstacle courses, etc.).

Estimating Stair Running Performance Using Inertial Sensors.

Stair running, both ascending and descending, is a challenging aerobic exercise that many athletes, recreational runners, and soldiers perform during training. Studying biomechanics of stair running over multiple steps has been limited by the practical challenges presented while using optical-based motion tracking systems. We propose using foot-mounted inertial measurement units (IMUs) as a solution as they enable unrestricted motion capture in any environment and without need for external references. In particular, this paper presents methods for estimating foot velocity and trajectory during stair running using foot-mounted IMUs. Computational methods leverage the stationary periods occurring during the stance phase and known stair geometry to estimate foot orientation and trajectory, ultimately used to calculate stride metrics. These calculations, applied to human participant stair running data, reveal performance trends through timing, trajectory, energy, and force stride metrics. We present the results of our analysis of experimental data collected on eleven subjects. Overall, we determine that for either ascending or descending, the stance time is the strongest predictor of speed as shown by its high correlation with stride time.

Method for Estimating Three-Dimensional Knee Rotations Using Two Inertial Measurement Units: Validation with a Coordinate Measurement Machine.

Three-dimensional rotations across the human knee serve as important markers of knee health and performance in multiple contexts including human mobility, worker safety and health, athletic performance, and warfighter performance. While knee rotations can be estimated using optical motion capture, that method is largely limited to the laboratory and small capture volumes. These limitations may be overcome by deploying wearable inertial measurement units (IMUs). The objective of this study is to present a new IMU-based method for estimating 3D knee rotations and to benchmark the accuracy of the results using an instrumented mechanical linkage. The method employs data from shank- and thigh-mounted IMUs and a vector constraint for the medial-lateral axis of the knee during periods when the knee joint functions predominantly as a hinge. The method is carefully validated using data from high precision optical encoders in a mechanism that replicates 3D knee rotations spanning (1) pure flexion/extension, (2) pure internal/external rotation, (3) pure abduction/adduction, and (4) combinations of all three rotations. Regardless of the movement type, the IMU-derived estimates of 3D knee rotations replicate the truth data with high confidence (RMS error < 4 ° and correlation coefficient r ≥ 0.94 ).

Dynamic Model Exposes the Energetics and Dynamics of the Injection Machinery for Bacteriophage T4.

Bacteriophage T4 infects the bacterial host (Escherichia coli) using an efficient genomic delivery machine that is driven by elastic energy stored in a contractile tail sheath. Although the atomic structure of T4 is largely known, the dynamics of its fascinating injection machinery is not understood. This article contributes, to our knowledge, the first predictions of the energetics and dynamics of the T4 injection machinery using a novel dynamic model. The model employs an atomistic (molecular dynamics) representation of a fraction of the sheath structure to generate a continuum model of the entire sheath that also couples to a model of the viral capsid and tail tube. The resulting model of the entire injection machine reveals estimates for the energetics, timescale, and pathway of the T4 injection process as well as the force available for cell rupture. It also reveals the large and highly nonlinear conformational changes of the sheath whose elastic energy drives the injection process.

Movements Indicate Threat Response Phases in Children at Risk for Anxiety.

Temporal phases of threat response, including potential threat (anxiety), acute threat (startle, fear), and post-threat response modulation, have been identified as the underlying markers of anxiety disorders. Objective measures of response during these phases may help identify children at risk for anxiety; however, the complexity of current assessment techniques prevent their adoption in many research and clinical contexts. We propose an alternative technology, an inertial measurement unit (IMU), that enables noninvasive measurement of the movements associated with threat response, and test its ability to detect threat response phases in young children at a heightened risk for developing anxiety. We quantified the motion of 18 children (3-7 years old) during an anxiety-/fear-provoking behavioral task using an IMU. Specifically, measurements from a single IMU secured to the child's waist were used to extract root-mean-square acceleration and angular velocity in the horizontal and vertical directions, and tilt and yaw range of motion during each threat response phase. IMU measurements detected expected differences in child motion by threat phase. Additionally, potential threat motion was positively correlated to familial anxiety risk, startle range of motion was positively correlated with child internalizing symptoms, and response modulation motion was negatively correlated to familial anxiety risk. Results suggest differential theory-driven threat response phases and support previous literature connecting maternal child risk to anxiety with behavioral measures using more feasible objective methods. This is the first study demonstrating the utility of an IMU for characterizing the motion of young children to mark the phases of threat response modulation. The technique provides a novel and objective measure of threat response for mental health researchers.

Quantifying warfighter performance in a target acquisition and aiming task using wireless inertial sensors.

An array of inertial measurement units (IMUS) was experimentally employed to analyze warfighter performance on a target acquisition task pre/post fatigue. Eleven participants (5M/6F) repeated an exercise circuit carrying 20 kg of equipment until fatigued. IMUs secured to the sacrum, sternum, and a rifle quantified peak angular velocity magnitude (PAVM) and turn time (TT) on a target acquisition task (three aiming events with two 180° turns) within the exercise circuit. Turning performance of two turns was evaluated pre/post fatigue. Turning performance decreased with fatigue. PAVMs decreased during both turns for the sternum (p < 0.001), sacrum (p = 0.007) and rifle (p = 0.002). TT increased for the sternum (p = 0.001), sacrum (p = 0.003), and rifle (p = 0.02) during turn 1, and for the rifle (p = 0.04) during turn 2. IMUs detected and quantified changes in warfighter aiming performance after fatigue. Similar methodologies can be applied to many movement tasks, including quantifying movement performance for load, fatigue, and equipment conditions.

On the Skill of Balancing While Riding a Bicycle.

Humans have ridden bicycles for over 200 years, yet there are no continuous measures of how skill differs between novice and expert. To address this knowledge gap, we measured the dynamics of human bicycle riding in 14 subjects, half of whom were skilled and half were novice. Each subject rode an instrumented bicycle on training rollers at speeds ranging from 1 to 7 m/s. Steer angle and rate, steer torque, bicycle speed, and bicycle roll angle and rate were measured and steering power calculated. A force platform beneath the roller assembly measured the net force and moment that the bicycle, rider and rollers exerted on the floor, enabling calculations of the lateral positions of the system centers of mass and pressure. Balance performance was quantified by cross-correlating the lateral positions of the centers of mass and pressure. The results show that all riders exhibited similar balance performance at the slowest speed. However at higher speeds, the skilled riders achieved superior balance performance by employing more rider lean control (quantified by cross-correlating rider lean angle and bicycle roll angle) and less steer control (quantified by cross-correlating steer rate and bicycle roll rate) than did novice riders. Skilled riders also used smaller steering control input with less variation (measured by average positive steering power and standard deviations of steer angle and rate) and less rider lean angle variation (measured by the standard deviation of the rider lean angle) independent of speed. We conclude that the reduction in balance control input by skilled riders is not due to reduced balance demands but rather to more effective use of lean control to guide the center of mass via center of pressure movements.

Quantifying performance and effects of load carriage during a challenging balancing task using an array of wireless inertial sensors.

We utilize an array of wireless inertial measurement units (IMUs) to measure the movements of subjects (n=30) traversing an outdoor balance beam (zigzag and sloping) as quickly as possible both with and without load (20.5kg). Our objectives are: (1) to use IMU array data to calculate metrics that quantify performance (speed and stability) and (2) to investigate the effects of load on performance. We hypothesize that added load significantly decreases subject speed yet results in increased stability of subject movements. We propose and evaluate five performance metrics: (1) time to cross beam (less time=more speed), (2) percentage of total time spent in double support (more double support time=more stable), (3) stride duration (longer stride duration=more stable), (4) ratio of sacrum M-L to A-P acceleration (lower ratio=less lateral balance corrections=more stable), and (5) M-L torso range of motion (smaller range of motion=less balance corrections=more stable). We find that the total time to cross the beam increases with load (t=4.85, p<0.001). Stability metrics also change significantly with load, all indicating increased stability. In particular, double support time increases (t=6.04, p<0.001), stride duration increases (t=3.436, p=0.002), the ratio of sacrum acceleration RMS decreases (t=-5.56, p<0.001), and the M-L torso lean range of motion decreases (t=-2.82, p=0.009). Overall, the IMU array successfully measures subject movement and gait parameters that reveal the trade-off between speed and stability in this highly dynamic balance task.

Accuracy of Femur Angles Estimated by IMUs During Clinical Procedures Used to Diagnose Femoroacetabular Impingement.

We present a novel method for quantifying femoral orientation angles using a thigh-mounted inertial measurement unit (IMU). The IMU-derived femoral orientation angles reproduce gold-standard motion capture angles to within mean (standard deviation) differences of 0.1 (1.1) degrees on cadaveric specimens during clinical procedures used for the diagnosis of Femoroacetabular Impingement (FAI). The method, which assumes a stationary pelvis, is easy to use, inexpensive, and provides femur motion trajectory data in addition to range of motion measures. These advantages may accelerate the adoption of this technology to inform FAI diagnoses and assess treatment efficacy. To this end, we further investigate the accuracy of hip joint angles calculated using this methodology and assess the sensitivity of our estimates to skin motion artifact during these tasks.

Role of microscopic flexibility in tightly curved DNA.

The genetic material in living cells is organized into complex structures in which DNA is subjected to substantial contortions. Here we investigate the difference in structure, dynamics, and flexibility between two topological states of a short (107 base pair) DNA sequence in a linear form and a covalently closed, tightly curved circular DNA form. By employing a combination of all-atom molecular dynamics (MD) simulations and elastic rod modeling of DNA, which allows capturing microscopic details while monitoring the global dynamics, we demonstrate that in the highly curved regime the microscopic flexibility of the DNA drastically increases due to the local mobility of the duplex. By analyzing vibrational entropy and Lipari-Szabo NMR order parameters from the simulation data, we propose a novel model for the thermodynamic stability of high-curvature DNA states based on vibrational untightening of the duplex. This novel view of DNA bending provides a fundamental explanation that bridges the gap between classical models of DNA and experimental studies on DNA cyclization, which so far have been in substantial disagreement.