Actual Human Subjects Research Articles

Characterization of droplet clusters in a turbulent multiphase gas cloud using a model cough simulator

This study aims to investigate the transport of droplets ejected from an artificial cough simulator, which releases a turbulent puff of droplets into the surrounding air, closely resembling the human coughing process. The focus is on understanding droplet clustering within the multiphase gas cloud across various operating conditions that emulate the wide variation in the spray characteristics in actual human subjects owing to infection severity, age, and gender. Time-resolved particle image velocimetry (PIV) technique was employed to measure the velocity of both droplet and gas phases. It also facilitates the identification and characterization of droplet clusters through Voronoi analysis of the PIV images. The area and length scale of individual droplet clusters were measured, and the degree of droplet clustering was quantified using the clustering index and relative droplet number density within the clusters. Additionally, the interferometric laser imaging for droplet sizing technique was utilized for planar measurement of individual droplet sizes. The range of Stokes number indicated partial to poor response of the droplets to the turbulent eddies. The results reported, for the first time, the presence of droplet clusters in the simulated coughing process. The wide spectrum of cluster size and self-similar evolution of droplet clusters unveil a multi-scale clustering phenomenon, shedding light on the intricate dynamics of the respiratory droplet dispersion process. The study comprehensively investigates the role of injection pressure on droplet clustering and the spatial development of the clusters, revealing some interesting findings, which are discussed.

Bioequivalence Studies of Highly Variable Drugs: An Old Problem Addressed by Artificial Neural Networks

The bioequivalence (BE) of highly variable drugs is a complex issue in the pharmaceutical industry. The impact of this variability can significantly affect the required sample size and statistical power. In order to address this issue, the EMA and FDA propose the utilization of scaled limits. This study suggests the use of generative artificial intelligence (AI) algorithms, particularly variational autoencoders (VAEs), to virtually increase sample size and therefore reduce the need for actual human subjects in the BE studies of highly variable drugs. The primary aim of this study was to show the capability of using VAEs with constant acceptance limits (80–125%) and small sample sizes to achieve high statistical power. Monte Carlo simulations, incorporating two levels of stochasticity (between-subject and within-subject), were used to synthesize the virtual population. Various scenarios focusing on high variabilities were simulated. The performance of the VAE-generated datasets was compared to the official approaches imposed by the FDA and EMA, using either the constant 80–125% limits or scaled BE limits. To demonstrate the ability of AI generative algorithms to create virtual populations, no scaling was applied to the VAE-generated datasets, only to the actual data of the comparators. Across all scenarios, the VAE-generated datasets demonstrated superior performance compared to scaled or unscaled BE approaches, even with less than half of the typically required sample size. Overall, this study proposes the use of VAEs as a method to reduce the necessity of recruiting large numbers of subjects in BE studies.

Organs in orbit: how tissue chip technology benefits from microgravity, a perspective.

Tissue chips have become one of the most potent research tools in the biomedical field. In contrast to conventional research methods, such as 2D cell culture and animal models, tissue chips more directly represent human physiological systems. This allows researchers to study therapeutic outcomes to a high degree of similarity to actual human subjects. Additionally, as rocket technology has advanced and become more accessible, researchers are using the unique properties offered by microgravity to meet specific challenges of modeling tissues on Earth; these include large organoids with sophisticated structures and models to better study aging and disease. This perspective explores the manufacturing and research applications of microgravity tissue chip technology, specifically investigating the musculoskeletal, cardiovascular, and nervous systems.

In-Situ Measurement of Multi-Axis Torques Applied by Wearable Soft Robots for Shoulder Assistance

While a number of wearable soft robotic devices have been proposed to assist the shoulder, limited efforts have been made to quantify the amount of torque they apply to the body. Most work to-date has assessed soft actuator performance with simple benchtop experiments that may not be representative of the boundary conditions on the human body. We propose a new methodology to measure torques directly in-situ on the body and then use this technique to make a detailed comparison of two versions of a soft wearable shoulder assistance robot. The impact of a number of factors are considered, such as actuator design, garment anchoring, material hysteresis, arm pose, and inflation pressure. Many of these factors are not present on the benchtop and are found to significantly affect torque production. We compare results obtained on a simple benchtop test fixture with two on-body settings: an idealized mannequin and actual human subjects. The mannequin and human results were similar, but differed significantly from the benchtop, further motivating the need for on-body testing. Moving forward, we believe that the ability to directly quantify device performance in-situ will be critical to develop new design, modeling, and control strategies for wearable robots.

Organ-on-a-chip: A new tool for in vitro research

Organ-on-a-chip (OOC, organ chip) technology can closely simulate the human microenvironment, synthesize organ-like functional units on a fluidic chip substrate, and simulate the physiology of tissues and organs. It will become an increasingly important platform for in vitro drug development and screening. Most importantly, organ-on-a-chip technology, incorporating 3D cell cultures, overcomes the traditional drawbacks of 2D (flat) cell-culture technology in vitro and in vivo animal trials, neither of which generate completely reliable results when it comes to the actual human subject. It is expected that organ chips will allow huge reductions in the incidence of failure in late-stage human trials, thus slashing the cost of drug development and speeding up the introduction of drugs that are effective. There have been three key enabling technologies that have made organ chip technology possible: 3D bioprinting, fluidic chips, and 3D cell culture, of which the last has allowed cells to be cultivated under more physiologically realistic growth conditions than 2D culture. The fusion of these advanced technologies and the addition of new research methods and algorithms has enabled the construction of chip types with different structures and different uses, providing a wide range of controllable microenvironments, both for research at the cellular level and for more reliable analysis of the action of drugs on the human body. This paper summarizes some research progress of organ-on-a-chip in recent years, outlines the key technologies used and the achievements in drug screening, and makes some suggestions concerning the current challenges and future development of organ-on-a-chip technology.

Characterization, Design, and Experimentation of a Fabric-Based Wearable Joint Sensing Device on Human Elbow

Abstract The use of conductive fabrics (CFs) in the design of wearables for joint sensing has recently received much interest in a wide range of applications such as robotics, rehabilitation, personal wellness, and sports. However, one key limitation in the existing measurement approach is that the user’s anthropometric information is required to relate the joint parameters to the CF sensor strain reading. This paper seeks to address this limitation by evaluating a new wearable device concept that comprises a CF strain–voltage sensor embedded as part of an inverted slider-crank (ISC) mechanism for joint extension sensing. This benefits from not requiring anthropometric information from the user to relate the joint parameters to the fabric strain readings, as opposed to an existing design. We first characterize the electromechanical property of a commercially available CF. Second, we formulate the joint sensing device’s geometric synthesis procedure as a constrained revolute joint system, where the CF is designed and introduced as an RPR chain to obtain an ISC linkage. Lastly, we designed our wearable sensing device and validated against an ISC linkage fixture representing an elbow joint and an actual healthy human subject’s left elbow. The ISC linkage fixture experimental setup shows that our designed joint sensing device can track the elbow extension motion of 140 deg with a maximum error of 7.66%. The results from our human subject’s left elbow show that it can track the elbow flexion–extension at various angular motion, with error ranges between 8.24 deg and 12.86 deg, and have provided us with an acceptable average Spearman’s coefficient values rs at 0.95.

Security and privacy issues related to the workplace-based security robot system.

An isolated robot must take account of uncertainty in its world model and adapt its activities to take into account such as uncertainty. In the same way, a robot interaction with security and privacy issues (RISAPI) with people has to account for its confusion about the human internal state, as well as how this state will shift as humans respond to the robot. This paper discusses RISAPI of our original work in the field, which shows how probabilistic planning and system theory algorithms in workplace robotic systems that work with people can allow for that reasoning using a security robot system. The problem is a general way as an incomplete knowledge 2-player game. In this general framework, the various hypotheses and these contribute to thrilling and complex robot behavior through real-time interaction, which transforms actual human subjects into a spectrum of production systems, robots, and care facilities. The models of the internal human situation, in which robots can be designed efficiently, are limited, and achieve optimal computational intractability in large, high-dimensional spaces. To achieve this, versatile, lightweight portrayals of the human inner state and modern algorithms offer great hope for reasoning.

Computer vision-based objective evaluation of increase in breathing resistances of respirators on human subjects

The purpose of this study was to evaluate objectively the impact of wearing respirators on breathing resistances of actual human subjects. We designed a monitor of the nasal airflow, which was composed of a full facepiece mask, a pipe for gathering nasal airflow, a monitoring line and a camera. A total of 5 normal adult volunteers were recruited in this study. Wearing the monitor, the subjects were required to sit for 1 min and walk for 1 min during wearing eight different models of respirators and without a respirator. Subsequently, the swing video of the monitoring line was collected by the camera during each breath of the subjects. The mean value of maximum swing angles of the monitoring line and the swing angle ratio were calculated through the image processing of the experimental videos. The experimental results show that the swing angle ratio during exhalation and inhalation are effective for representing exhalation resistances and inhalation resistances respectively. This is the first reported study that combines computer vision and the self-developed nasal airflow monitor to demonstrate quantitatively and objectively the exhalation resistances and inhalation resistances with the use of different respirators on actual human subjects.

Population of 224 realistic human subject-based computational breast phantoms.

To create a database of highly realistic and anatomically variable 3D virtual breast phantoms based on dedicated breast computed tomography (bCT) data. A tissue classification and segmentation algorithm was used to create realistic and detailed 3D computational breast phantoms based on 230 + dedicated bCT datasets from normal human subjects. The breast volume was identified using a coarse three-class fuzzy C-means segmentation algorithm which accounted for and removed motion blur at the breast periphery. Noise in the bCT data was reduced through application of a postreconstruction 3D bilateral filter. A 3D adipose nonuniformity (bias field) correction was then applied followed by glandular segmentation using a 3D bias-corrected fuzzy C-means algorithm. Multiple tissue classes were defined including skin, adipose, and several fractional glandular densities. Following segmentation, a skin mask was produced which preserved the interdigitated skin, adipose, and glandular boundaries of the skin interior. Finally, surface modeling was used to produce digital phantoms with methods complementary to the XCAT suite of digital human phantoms. After rejecting some datasets due to artifacts, 224 virtual breast phantoms were created which emulate the complex breast parenchyma of actual human subjects. The volume breast density (with skin) ranged from 5.5% to 66.3% with a mean value of 25.3% ± 13.2%. Breast volumes ranged from 25.0 to 2099.6 ml with a mean value of 716.3 ± 386.5 ml. Three breast phantoms were selected for imaging with digital compression (using finite element modeling) and simple ray-tracing, and the results show promise in their potential to produce realistic simulated mammograms. This work provides a new population of 224 breast phantoms based on in vivo bCT data for imaging research. Compared to previous studies based on only a few prototype cases, this dataset provides a rich source of new cases spanning a wide range of breast types, volumes, densities, and parenchymal patterns.

An Agent-Based Model of Public Participation in Sustainability Management

This article reports on an agent-based simulation of public participation in decision making about sustainability management. Agents were modeled as socially intelligent actors who communicate using a system of symbols. The goal of the simulation was for agents to reach consensus about which situations in their regional environment to change and which ones not to change as part of a geodesign process for improving water quality in the greater Puget Sound region. As opposed to studying self-organizing behavior at the scale of a local 'commons', our interest was in how online technology supports the self-organizing behavior of agents distributed over a wide regional area, like a watershed or river basin. Geographically-distributed agents interacted through an online platform similar to that used in online field experiments with actual human subjects. We used a factorial research design to vary three interdependent factors each with three different levels. The three factors included 1) the social and geographic distribution of agents (local, regional, international levels), 2) abundance of agents (low, medium, high levels), and 3) diversity of preconceptions (blank slate, clone, social actor levels). We expected that increasing the social and geographic distribution of agents and the diversity of their preconceptions would have a significant impact on agent consensus about which situations to change and which ones not to change. However, our expectations were not met by our findings, which we trace all the way back to our conceptual model and a theoretical gap in sustainability science. The theory of self-organizing resource users does not specify how a group of social actors' preconceptions about a situation is interdependent with their social and geographic orientation to that situation. We discuss the results of the experiment and conclude with prospects for research on the social and geographic dimensions of self-organizing behavior in social-ecological systems spanning wide regional areas.

Passive and dynamic gait measures for biped mechanism: formulation and simulation analysis

SUMMARYUnderstanding and mimicking human gait is essential for design and control of biped walking robots. The unique characteristics of normal human gait are described as passive dynamic walking, whereas general human gait is neither completely passive nor always dynamic. To study various walking motions, it is important to quantify the different levels of passivity and dynamicity, which have not been addressed in the current literature. In this paper, we introduce the initial formulations of Passive Gait Measure (PGM) and Dynamic Gait Measure (DGM) that quantify passivity and dynamicity, respectively, of a given biped walking motion, and the proposed formulations will be demonstrated for proof-of-concepts using gait simulation and analysis. The PGM is associated with the optimality of natural human walking, where the passivity weight functions are proposed and incorporated in the minimization of physiologically inspired weighted actuator torques. The PGM then measures the relative contribution of the stance ankle actuation. The DGM is associated with the gait stability, and quantifies the effects of inertia in terms of the Zero-Moment Point and the ground projection of center of mass. In addition, the DGM takes into account the stance foot dimension and the relative threshold between static and dynamic walking. As examples, both human-like and robotic walking motions during single support phase are generated for a planar biped system using the passivity weights and proper gait parameters. The calculated PGM values show more passive nature of human-like walking as compared with the robotic walking. The DGM results verify the dynamic nature of normal human walking with anthropomorphic foot dimension. In general, the DGMs for human-like walking are greater than those for robotic walking. The resulting DGMs also demonstrate their dependence on the stance foot dimension as well as the walking motion; for a given walking motion, smaller foot dimension results in increased dynamicity. Future work on experimental validation and demonstration will involve actual walking robots and human subjects. The proposed results will benefit the human gait studies and the development of walking robots.

Development of an advanced hearing protection evaluation system

Acoustic Test Fixtures (ATFs) are practical and often necessary tools for testing Hearing Protection Devices (HPDs) especially with extremely loud impulsive and/or continuous noise, for which the use of live subjects might not be advisable. Although there have been various standardized and laboratory ATFs from past research, there still exists large uncertainty in the correlation between the attenuation results obtained from ATFs and those obtained from actual human subject tests, particularly for intraaural HPDs. It is suspected that one of the main factors contributing to the discrepancy may be insufficient fidelity in the circumaural/intraaural flesh and bone. Human subject testing was performed to obtain median parameters of ear canal geometry and eardrum reflectance, which are considered to be critical parameters for circumaural/intraaural HPD attenuation performance. This presentation discusses the research methodologies and design implementation of these important subsystems in this advanced Hearing Protection Evaluation System (HPES).

Objective Assessment of Increase in Breathing Resistance of N95 Respirators on Human Subjects

Face masks or respirators are commonly worn by medical professionals and patients for protection against respiratory tract infection and the spread of illnesses, such as severe acute respiratory syndrome and pandemic influenza (H1N1). Breathing discomfort due to increased breathing resistance is known to be a problem with the use of N95 respirators but there is a lack of scientific data to quantify this effect. The purpose of this study was to assess objectively the impact of wearing N95 face masks on breathing resistance. A total of 14 normal adult volunteers (seven males and seven females) were recruited in this study. Nasal airflow resistance during inspiration and expiration was measured using a standard rhinomanometry and nasal spirometry. A modified full face mask was produced in-house in order to measure nasal resistance with the use of N95 (3M 8210) respirators. The results showed a mean increment of 126 and 122% in inspiratory and expiratory flow resistances, respectively, with the use of N95 respirators. There was also an average reduction of 37% in air exchange volume with the use of N95 respirators. This is the first reported study that demonstrates quantitatively and objectively the substantial impairment of nasal airflow in terms of increased breathing resistance with the use of N95 respirators on actual human subjects.

Development of an advanced hearing protection evaluation system.

Acoustic test fixtures (ATFs) are practical and often necessary tools for testing hearing protection devices (HPDs) especially with extremely loud impulsive and/or continuous noise, for which the use of live subjects might not be advisable. Although there have been various standardized and laboratory ATFs from past research, there still exists large uncertainty in the correlation between the attenuation results obtained from ATFs and those obtained from actual human subject tests, particularly for intraaural HPDs. It is suspected that one of the main factors contributing to the discrepancy may be insufficient fidelity in the circumaural/intraaural flesh system, whose underlying dynamics is not yet clear. Therefore the first goal of this research is to better understand this biomechanical system and implement it into a new ATF prototype which emulates circumaural/intraaural HPD attenuation performance. This prototype ATF will be validated against human subjects. This presentation discusses the research methodologies and design strategies for developing this advanced hearing protection evaluation system.

Evaluation of selected sorbent materials for the collection of volatile organic compounds related to human scent using non-contact sampling mode

Human scent can be collected by either contact or non-contact sampling mode. The most frequently used human scent evidence collection device known as the Scent Transfer Unit (STU-100) is a dynamic sampling device and is often used in a non-contact mode. A customized human scent collection chamber was utilized in combination with controlled odor mimic permeation systems containing five standard human scent volatiles to optimize the flow rate, collection material and geometry of the absorbent material. The scent collection method which yielded the greatest amount of volatile organic compounds (VOCs) detected included the use of a single layer of Johnson and Johnson gauze/multiple layers of Dukal gauze with the STU-100 on the lowest flow rate setting. The correlation of the resulting VOC profiles demonstrate that collection of standard VOCs in controlled conditions yielded reproducible VOC profiles on all materials studied with the exception of polyester. Finally, the method was tested using actual human subjects under optimized set of conditions.

MCAT to XCAT: The Evolution of 4-D Computerized Phantoms for Imaging Research: Computer models that take account of body movements promise to provide evaluation and improvement of medical imaging devices and technology.

Recent work in the development of computerized phantoms has focused on the creation of ideal "hybrid" models that seek to combine the realism of a patient-based voxelized phantom with the flexibility of a mathematical or stylized phantom. We have been leading the development of such computerized phantoms for use in medical imaging research. This paper will summarize our developments dating from the original four-dimensional (4-D) Mathematical Cardiac-Torso (MCAT) phantom, a stylized model based on geometric primitives, to the current 4-D extended Cardiac-Torso (XCAT) and Mouse Whole-Body (MOBY) phantoms, hybrid models of the human and laboratory mouse based on state-of-the-art computer graphics techniques. This paper illustrates the evolution of computerized phantoms toward more accurate models of anatomy and physiology. This evolution was catalyzed through the introduction of nonuniform rational b-spline (NURBS) and subdivision (SD) surfaces, tools widely used in computer graphics, as modeling primitives to define a more ideal hybrid phantom. With NURBS and SD surfaces as a basis, we progressed from a simple geometrically based model of the male torso (MCAT) containing only a handful of structures to detailed, whole-body models of the male and female (XCAT) anatomies (at different ages from newborn to adult), each containing more than 9000 structures. The techniques we applied for modeling the human body were similarly used in the creation of the 4-D MOBY phantom, a whole-body model for the mouse designed for small animal imaging research. From our work, we have found the NURBS and SD surface modeling techniques to be an efficient and flexible way to describe the anatomy and physiology for realistic phantoms. Based on imaging data, the surfaces can accurately model the complex organs and structures in the body, providing a level of realism comparable to that of a voxelized phantom. In addition, they are very flexible. Like stylized models, they can easily be manipulated to model anatomical variations and patient motion. With the vast improvement in realism, the phantoms developed in our lab can be combined with accurate models of the imaging process (SPECT, PET, CT, magnetic resonance imaging, and ultrasound) to generate simulated imaging data close to that from actual human or animal subjects. As such, they can provide vital tools to generate predictive imaging data from many different subjects under various scanning parameters from which to quantitatively evaluate and improve imaging devices and techniques. From the MCAT to XCAT, we will demonstrate how NURBS and SD surface modeling have resulted in a major evolutionary advance in the development of computerized phantoms for imaging research.

Evaluation Experiment of Ultrasound Computed Tomography for the Abdominal Sound Speed Imaging

Abdominal sound speed tomographic imaging using through-transmission travel time data on the body surface was investigated. To this end, a hundred kHz range low-frequency wave was used to reduce the wave attenuation within an inner body medium. A method was investigated for the reconstruction of the image with the smallest possible number of path data around the abdominal surface. Specifically, the data from a strong scattering spinal cord should be avoided. To fulfill the requirement, the smoothed path algebraic reconstruction technique was introduced. The validity of this method was examined both on the numerically synthesized data and the experimentally measured data for the phantom specimen and actual human subject. It was shown that an abdominal tomographic sound speed image could be successfully obtained by preparing only 32 transducer locations at the circumference around the abdominal surface and their combination of less than 100 number of observation path data as well as by avoiding the data intersecting the spinal cord. In addition, fat regions were extracted having a sound speed lower than the threshold value to demonstrate the possibility of this method for metabolic syndrome diagnosis.

Genre and Ideology in Vladimír Holan's Red Army Soldiers

Among Vladimír Holan's postwar poetic output, the cycle Rudoarmĕjci (Red army soldiers, 1947) enjoys high critical acclaim while the trio of his other works, Dík Sovĕtskému svazu (Thanks to the Soviet Union), Panychida (A memorial service), and the cycle Tobé (To you), is regarded as a crude exercise in propaganda. Peter Steiner argues that the main reason for this evaluative difference is that the genre of the cycle enables Holan to disseminate an ideological message similar to that of the unappreciated trio in a more subtle, less ostentatious manner. The first part of the article analyzes the various techniques of portraiture Holan employed to represent ordinary Russian soldiers (prosopopeia and ethopoeia). In the second part, Steiner discusses the genre's ideological potential. Since portrait by definition must depict an actual human subject, the very selection of the model and his or her features embroils such a work in a specific social reality and reflects the author's attitude toward it. This worldview, however, is not added to the text mechanically, from without, but comprises an integral part of the very mimetic apparatus that generates its overall meaning.

Adaptive physics based tetrahedral mesh generation using level sets

We present a tetrahedral mesh generation algorithm designed for the Lagrangian simulation of deformable bodies. The algorithm’s input is a level set (i.e., a signed distance function on a Cartesian grid or octree). First a bounding box of the object is covered with a uniform lattice of subdivision-invariant tetrahedra. The level set is then used to guide a red green adaptive subdivision procedure that is based on both the local curvature and the proximity to the object boundary. The final topology is carefully chosen so that the connectivity is suitable for large deformation and the mesh approximates the desired shape. Finally, this candidate mesh is compressed to match the object boundary. To maintain element quality during this compression phase we relax the positions of the nodes using finite elements, masses and springs, or an optimization procedure. The resulting mesh is well suited for simulation since it is highly structured, has topology chosen specifically for large deformations, and is readily refined if required during subsequent simulation. We then use this algorithm to generate meshes for the simulation of skeletal muscle from level set representations of the anatomy. The geometric complexity of biological materials makes it very difficult to generate these models procedurally and as a result we obtain most if not all data from an actual human subject. Our current method involves using voxelized data from the Visible Male [1] to create level set representations of muscle and bone geometries. Given this representation, we use simple level set operations to rebuild and repair errors in the segmented data as well as to smooth aliasing inherent in the voxelized data.

Forensic Engineering Design Construction And Use Of Economical Human Surrogates

Anthropometric Dummies Have Been Used In Accident And Emergency Response Research For Over Five Decades. Such Mechanical Surrogates Have Been Valuable Tools To Help Scientists, Engineers And Others Understand Spatial Relationships And Dynamic Events Involving The Human Body In Situations Where It Is Too Dangerous Or Too Costly To Use Actual Human Subjects. Mechanical Human Surrogates Can Also Be Valuable Tools For The Forensic Engineer In Certain Situations, Whether The Task At Hand Is To Understand The Space Occupied By, The Inertial Response Of, The Deformation Compliance Of Or The Forces Or Positions Experienced By The Human Body During Dynamic Events. Rarely, However, Can The Forensic Engineers Assignment Financially Justify The Purchase Or Use Of Commercially Available Biofidelic Manikins, Assuming Such Manikins Of The Size And Weight Needed Even Exist In The First Place. The Purpose Of This Paper Is To Offer An Economical Design And Method Of Construction Using Common And Readily Available Materials For Mechanical Lumped-Mass Human Surrogates (Dummies) That Will Provide Space, Mass And Joint Movement That Approximately Represent That Of The Human Body.