Static, Dynamic, and Cognitive Fit of Exosystems for the Human Operator.

OBJECTIVE: To define static, dynamic, and cognitive fit and their interactions as they pertain to exosystems and to document open research needs in using these fit characteristics to inform exosystem design. BACKGROUND: Initial exosystem sizing and fit evaluations are currently based on scalar anthropometric dimensions and subjective assessments. As fit depends on ongoing interactions related to task setting and user, attempts to tailor equipment have limitations when optimizing for this limited fit definition. METHOD: A targeted literature review was conducted to inform a conceptual framework defining three characteristics of exosystem fit: static, dynamic, and cognitive. Details are provided on the importance of differentiating fit characteristics for developing exosystems. RESULTS: Static fit considers alignment between human and equipment and requires understanding anthropometric characteristics of target users and geometric equipment features. Dynamic fit assesses how the human and equipment move and interact with each other, with a focus on the relative alignment between the two systems. Cognitive fit considers the stages of human-information processing, including somatosensation, executive function, and motor selection. Human cognitive capabilities should remain available to process task- and stimulus-related information in the presence of an exosystem. Dynamic and cognitive fit are operationalized in a task-specific manner, while static fit can be considered for predefined postures. CONCLUSION: A deeper understanding of how an exosystem fits an individual is needed to ensure good human-system performance. Development of methods for evaluating different fit characteristics is necessary. APPLICATION: Methods are presented to inform exosystem evaluation across physical and cognitive characteristics.

Correction: McGrath, T., et al. An Auto-Calibrating Knee Flexion-Extension Axis Estimator using Principal Component Analysis with Inertial Sensors. Sensors 2018, 18(6), 1882.

The authors wish to make the following revisions to this paper [...].

An Auto-Calibrating Knee Flexion-Extension Axis Estimator Using Principal Component Analysis with Inertial Sensors.

Inertial measurement units (IMUs) have been demonstrated to reliably measure human joint angles—an essential quantity in the study of biomechanics. However, most previous literature proposed IMU-based joint angle measurement systems that required manual alignment or prescribed calibration motions. This paper presents a simple, physically-intuitive method for IMU-based measurement of the knee flexion/extension angle in gait without requiring alignment or discrete calibration, based on computationally-efficient and easy-to-implement Principle Component Analysis (PCA). The method is compared against an optical motion capture knee flexion/extension angle modeled through OpenSim. The method is evaluated using both measured and simulated IMU data in an observational study (n = 15) with an absolute root-mean-square-error (RMSE) of 9.24∘ and a zero-mean RMSE of 3.49∘. Variation in error across subjects was found, made emergent by the larger subject population than previous literature considers. Finally, the paper presents an explanatory model of RMSE on IMU mounting location. The observational data suggest that RMSE of the method is a function of thigh IMU perturbation and axis estimation quality. However, the effect size for these parameters is small in comparison to potential gains from improved IMU orientation estimations. Results also highlight the need to set relevant datums from which to interpret joint angles for both truth references and estimated data.

Analysis of Flexible Ureteroscopic Motion and Kinematic Efficiency: A Simulation-Based Pilot Study.

Introduction: Flexible ureteroscopy (fURS) is the most common surgical procedure for treatment of urolithiasis. Various surgical disciplines and subspecialties have examined surgeon kinematics to improve assessment and generate measures of skill. Despite frequency of utilization, there is no undisputed method for evaluating fURS skills. Our pilot study utilized kinematic evaluations of fURS simulation to determine whether specific surgeon movements, techniques, and strategies correlate with measures of ureteroscopic (URS) efficiency. Methods: A motion capture system and standard video camera were employed to characterize surgeon movement variables. A URS simulation box was used by practicing urologists at various skill levels to perform a series of simple and complex URS movement tasks. Two tasks were chosen for this initial pilot analysis. Body kinematics, time to task completion, and URS movements were analyzed. Task efficiency was defined as quicker time to task completion and smaller ureteroscope end effector travel distance. A combined performance efficiency score (PES) was calculated using the root sum square of these two measures. Results: Twelve practicing urologists were enlisted. Average urologist age was 37 years with an average of 10.1 years of training; 50% were women, 50% were residents; and 33% had completed an Endourology fellowship. For the simple task, no kinematic data correlated with PES; for the complex task, participant head and torso movement correlated with PES (r = 0.60, p = 0.04 for head; r = 0.65, p = 0.02 for torso), with decreased body movement associated with higher efficiency. Conclusion: Our findings suggest that movement economy measures are associated with efficient URS manipulation for complex tasks. Decreased head and torso movement were associated with higher efficiency, suggesting that excess body movement may signal extraneous or improper URS movements. Additional assessment of these variables, including analysis in a clinical setting, is warranted as this may serve as a basis for improvement in endoscopic training and evaluation.

Objective Metrics Quantifying Fit and Performance in Spacesuit Assemblies.

INTRODUCTION: Human-spacesuit fit is not well understood, especially in relation to operational performance and injury risk. Current fit decisions use subjective feedback. This work developed and evaluated new metrics for quantifying fit and assessed metric sensitivity to changes in padding between the human and hip brief assembly (HBA).METHODS: Three subjects donned the Mark III (MKIII) spacesuit with three padding thicknesses between the lower body and HBA. Subjects performed a walking task with inertial measurement units on the thigh and shin of both the human and suit. For each step, cadence, human knee task range of motion (tRoM), difference in human and suit tROM (ΔtRoM), and the relative coordination metric (ρ) between the human-suit femur and tibia were computed.RESULTS: The MKIII significantly reduced user cadence by 20.4% and reduced tRoM by 16.5% during walking with subject-dependent changes due to added padding. In general, the addition of padding significantly altered ΔtRoM; however, variability did exist between subjects. Mixed-effect regressions of dynamic fit (ρ) reflect distinct positive spikes in ρ around heel strike (human-dominated motion) and negative dips following toe off (suit-dominated motion).DISCUSSION: There were mixed effects of padding on gait performance and dynamic fit measures. Differences in dynamic fit between subjects may be more reliant on alternate aspects of fit, such as suit component sizes and designs, than padding level. Subjective feedback supported quantitative observations, highlighting metric utility. Future work will explore the effects of suit sizing components on measures of fit and performance.Fineman RA, McGrath TM, Kelty-Stephen DG, Abercromby AFJ, Stirling LA. Objective metrics quantifying fit and performance in spacesuit assemblies. Aerosp Med Hum Perform. 2018; 89(11):985-995.

Quantification and visualization of coordination during non-cyclic upper extremity motion.

There are many design challenges in creating at-home tele-monitoring systems that enable quantification and visualization of complex biomechanical behavior. One such challenge is robustly quantifying joint coordination in a way that is intuitive and supports clinical decision-making. This work defines a new measure of coordination called the relative coordination metric (RCM) and its accompanying normalization schemes. RCM enables quantification of coordination during non-constrained discrete motions. Here RCM is applied to a grasping task. Fifteen healthy participants performed a reach, grasp, transport, and release task with a cup and a pen. The measured joint angles were then time-normalized and the RCM time-series were calculated between the shoulder-elbow, shoulder-wrist, and elbow-wrist. RCM was normalized using four differing criteria: the selected joint degree of freedom, angular velocity, angular magnitude, and range of motion. Percent time spent in specified RCM ranges was used asa composite metric and was evaluated for each trial. RCM was found to vary based on: (1) chosen normalization scheme, (2) the stage within the task, (3) the object grasped, and (4) the trajectory of the motion. The RCM addresses some of the limitations of current measures of coordination because it is applicable to discrete motions, does not rely on cyclic repetition, and uses velocity-based measures. Future work will explore clinically relevant differences in the RCM as it is expanded to evaluate different tasks and patient populations.