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IntroductionAdvancements in exercise science have highlighted the importance of accurate muscular strength assessments for optimizing performance and preventing injuries.MethodsWe propose a novel approach to measuring muscular strength in young, healthy individuals using Bot Fit, a hip-joint exoskeleton, during resistance exercises. In this study, we introduced performance metrics to evaluate exercise performance during both short and extended durations of three resistance exercises: squats, knee-ups, and reverse lunges. These metrics, derived from the robot’s motor signals and sEMG data, include initial exercise speed, the number of repetitions, and muscle engagement. We compared these metrics against baseline muscular strength, measured using standard fitness equipment such as one-repetition maximum (1RM) and isometric contraction tests, conducted with 30 participants aged 23 to 30 years.ResultsOur results revealed that initial exercise speed and the number of repetitions were significant predictors of baseline muscular strength. Using statistical multivariable analysis, we developed a highly accurate model (R=0.884, adj. R2=0.753, p-value 0.87) with strong explanatory power.ConclusionThis model, focusing on a single exercise (squat) and a key performance metric (initial speed), accurately represents the muscular strength of Bot Fit users across all three exercises. This study expands the application of hip-joint exoskeleton robots, enabling efficient estimation of lower limb muscle strength through resistance exercises with Bot Fit.

Fairness constitutes a cornerstone of social norms, emphasizing equal treatment and equitable distribution in interpersonal relationships. Unfair treatment often leads to direct responses and can spread to others through a phenomenon known as pay-it-forward (PIF) reciprocity. This study examined how unfairness spreads in interactions with new partners who have higher, equal, or lower status than the participants. In the present study, participants (N = 47, all Korean) were given either fair or unfair treatment in the first round of a dictator game. They then allocated monetary resources among partners positioned at various hierarchical levels in the second round. Our main goal was to determine if the severity of inequity inflicted on new partners was influenced by their hierarchical status. The results revealed an inclination among participants to act more generously towards partners of higher ranking despite prior instances of unfair treatment, whereas a tendency for harsher treatment was directed towards those with lower ranking. The interaction between the fairness in the first round (DG1) and the hierarchical status of the partner in the second round (DG2) was significant, indicating that the effect of previous fairness on decision-making differed depending on the ranking of the new partners. This study, therefore, validates the presence of unfairness PIF reciprocity within hierarchical contexts.

Abstract Background Adipokines are hormones secreted from adipose tissue and are associated with cardiometabolic diseases (CMD). Functional differences between adipokines (leptin, adiponectin, and resistin) are known, but inconsistently reported associations with CMD and lack of studies in Hispanic populations are research gaps. We investigated the relationship between subclinical atherosclerosis and multiple adipokine measures. Methods Cross-sectional data from the Cameron County Hispanic Cohort (N = 624; mean age = 50; Female = 70.8%) were utilized to assess associations between adipokines [continuous measures of adiponectin, leptin, resistin, leptin-to-adiponectin ratio (LAR), and adiponectin-resistin index (ARI)] and early atherosclerosis [carotid-intima media thickness (cIMT)]. We adjusted for sex, age, body mass index (BMI), smoking status, cytokines, fasting blood glucose levels, blood pressure, lipid levels, and medication usage in the fully adjusted linear regression model. We conducted sexes-combined and sex-stratified analyses to account for sex-specificity and additionally tested whether stratification of participants by their metabolic status (metabolically elevated risk for CMD as defined by having two or more of the following conditions: hypertension, dyslipidemia, insulin resistance, and inflammation vs. not) influenced the relationship between adipokines and cIMT. Results In the fully adjusted analyses, adiponectin, leptin, and LAR displayed significant interaction by sex (p

OBJECTIVES The purpose of this study was to investigate the effects of assist and resistance torque on the spatiotemporal gait characteristics, and the symmetry and asymmetry of gait using a Gait Enhancing and Motivating System (GEMS) in the elderly. METHODS A cross-sectional and repeated measure design was used. A total of 18 participants (9 males, 9 females; age: 63.5 ± 5.02 years; mass: 64.26 ± 6.87 kg; height: 164.06 ± 7.15 cm) were recruited from a local community, and spatiotemporal gait data were collected with OptoGait system and GEMS. Spatiotemporal gait variables and differences between the dominant and non-dominant legs of these variables were assessed (step length, step time, stance phase, swing phase, single support, load response, pre swing phase, stride time, stride length, double support, cadence, and gait speed). The effects of three modes including normal, assist, and resist modes using GEMS were investigated twice for each participant on a 9-meter walkway. A one-way repeated measure analysis of variance followed by Bonferroni post-hoc tests was conducted. RESULTS The assist mode increased step time, swing phase, stride time and reduced stance phase, pre-swing phase, double support, cadence, and gait speed as compared to normal mode. The resist mode increased stance phase, load response, pre-swing phase, double support, cadence, and reduced step time, swing phase, and stride time. In dominant leg, assist mode showed increased step time and reduced pre-swing phase than normal mode, and greater step time than resist mode (p < 0.05). However, there was no effect of external torque on symmetry and asymmetry between both legs (p > 0.05). CONCLUSIONS The resistance and assist torque of GEMS alter spatiotemporal characteristics during the stance and swing phase of gait in the elderly. However, the resistance torque and assist torque of GEMS did not increase or decrease the gait asymmetry between the dominant and non-dominant legs.

Abstract Ingroup favoritism and fairness are two potentially competing motives guiding intergroup behaviors in human. Here, we investigate if and how limited resources can modulate the way these two motives affect individuals’ decisions in intergroup situation. In the present study, participants (N = 58) were asked to accept or reject three types of resource allocation proposals generated by a computer: the ingroup advantageous condition, outgroup advantageous condition, and neutral condition. In general, participants were more willing to accept the proposals in the ingroup advantageous condition than the outgroup advantageous or the neutral conditions, and also in the moderate inequality than the extreme inequality condition. This may indicate that people sought a careful balance between ingroup favoritism and fairness, although we also found marked individual differences in their preferences for ingroup favoritism or fairness. Importantly, as predicted, participants were more likely to show ingroup favoritism only when limited resources affect the well-being of ingroup members. The present study provides novel insights into the situational and personality factors affecting human intergroup behaviors, shedding light on motives underlying intergroup conflicts prevalent in human societies.

Abstract Background Aging societies lead to higher demand for gait rehabilitation as age-related neurological disorders such as stroke and spinal cord injury increase. Since conventional methods for gait rehabilitation are physically and economically burdensome, robotic gait training systems have been studied and commercialized, many of which provided movements confined in the sagittal plane. For better outcomes of gait rehabilitation with more natural gait patterns, however, it is desirable to provide pelvic movements in the transverse plane. In this study, a robotic gait training system capable of pelvic motions in the transverse plane was used to evaluate the effect of the pelvic motions on stroke patients. Method Healbot T, which is a robotic gait training system and capable of providing pelvic movements in the transverse plane as well as flexion/extension of the hip and knee joints and adduction/abduction of the hip joints, is introduced and used to evaluate the effect of the pelvic movement on gait training of stroke patients. Gait trainings in Healbot T with and without pelvic movements are carried out with stroke patients having hemiparesis. Experiment Twenty-four stroke patients with hemiparesis were randomly assigned into two groups and 23 of them successfully completed the experiment except one subject who had dropped out due to personal reasons. Pelvis-on group was provided with pelvic motions whereas no pelvic movement was allowed for pelvis-off group during 10 sessions of gait trainings in Healbot T. Electromyography (EMG) signals and interaction forces as well as the joint angles of the robot were measured. Gait parameters such as stride length, cadence, and walking speed were measured while walking on the ground without assistance of Healbot T after gait training on 1st, 5th, and 10th day. Result Stride length significantly increased in both groups. Furthermore, cadence and walking speed of the pelvis-on group were increased by 10.6% and 11.8%. Although interaction forces of both groups except the thighs showed no differences, EMG signals from gluteus medius of the pelvis-on group increased by 88.6% during stance phase. In addition, EMG signals of biceps femoris, gastrocnemius medial, and gastrocnemius lateral of the pelvis-on group increased whereas EMG signals of the pelvis-off group except gastrocnemius lateral showed no difference after gait trainings. Conclusion Gait training using a robotic gait training system with pelvic movements was conducted to investigate the effects of lateral and rotational pelvic movements in gait training of stroke patients. The pelvic movements affected to increase voluntary muscle activation during the stance phase as well as cadence and walking speed. Clinical trial registration KCT0003762, 2018-1254, Registered 28 October 2018, https://cris.nih.go.kr/cris/search/search_result_st01_kren.jsp?seq=14310&ltype=&rtype=

Hispanic/Latinos have been underrepresented in genome-wide association studies (GWAS) for anthropometric traits despite their notable anthropometric variability, ancestry proportions, and high burden of growth stunting and overweight/obesity. To address this knowledge gap, we analyzed densely imputed genetic data in a sample of Hispanic/Latino adults to identify and fine-map genetic variants associated with body mass index (BMI), height, and BMI-adjusted waist-to-hip ratio (WHRadjBMI). We conducted a GWAS of 18 studies/consortia as part of the Hispanic/Latino Anthropometry (HISLA) Consortium (stage 1, n = 59,771) and generalized our findings in 9 additional studies (stage 2, n = 10,538). We conducted a trans-ancestral GWAS with summary statistics from HISLA stage 1 and existing consortia of European and African ancestries. In our HISLA stage 1 + 2 analyses, we discovered one BMI locus, as well as two BMI signals and another height signal each within established anthropometric loci. In our trans-ancestral meta-analysis, we discovered three BMI loci, one height locus, and one WHRadjBMI locus. We also identified 3 secondary signals for BMI, 28 for height, and 2 for WHRadjBMI in established loci. We show that 336 known BMI, 1,177 known height, and 143 known WHRadjBMI (combined) SNPs demonstrated suggestive transferability (nominal significance and effect estimate directional consistency) in Hispanic/Latino adults. Of these, 36 BMI, 124 height, and 11 WHRadjBMI SNPs were significant after trait-specific Bonferroni correction. Trans-ancestral meta-analysis of the three ancestries showed a small-to-moderate impact of uncorrected population stratification on the resulting effect size estimates. Our findings demonstrate that future studies may also benefit from leveraging diverse ancestries and differences in linkage disequilibrium patterns to discover novel loci and additional signals with less residual population stratification.

In swarm robotic systems, task allocation is a challenging problem aiming to decompose complex tasks into a series of subtasks. We propose a self-organizing method to allocate a swarm of robots to perform a foraging task consisting of sequentially dependent subtasks. The method regulates the proportion of robots to meet the task demands for given tasks. Our proposed method is based on the response threshold model, mapping the intensity of task demands to the probability of responding to candidate tasks depending on the response threshold. Each robot is suitable for all tasks but some robots have higher probability of taking certain tasks and lower probability of taking others. In our task allocation method, each robot updates its response threshold depending on the associated task demand as well as the number of neighbouring robots performing the task. It relies neither on a centralized mechanism nor on information exchange amongst robots. Repetitive and continuous task allocations lead to the desired task distribution at a swarm level. We also analyzed the mathematical convergence of the task distribution among a swarm of robots. We demonstrate that the method is effective and robust for a foraging task under various conditions on the number of robots, the number of tasks and the size of the arena. Our simulation results may support the hypothesis that social insects use a task allocation method to handle the foraging task required for a colony's survival.

Many studies have been conducted to assess the health effects of climate change in Korea. However, there has been a lack of consideration regarding how the results of these studies can be applied to relevant policies. The current study aims to examine research trends at the agenda-setting stage and to review future ways in which health-related adaptation to climate change can be addressed within national public health policy. A systematic review of previous studies of the health effects of climate change in Korea was conducted. Many studies have evaluated the effect of ambient temperature on health. A large number of studies have examined the effects on deaths and cardio-cerebrovascular diseases, but a limitation of these studies is that it is difficult to apply their findings to climate change adaptation policy in the health sector. Many infectious disease studies were also identified, but these mainly focused on malaria. Regarding climate change-related factors other than ambient temperature, studies of the health effects of these factors (with the exception of air pollution) are limited. In Korea, it can be concluded that studies conducted as part of the agenda-setting stage are insufficient, both because studies on the health effects of climate change have not ventured beyond defining the problem and because health adaptation to climate change has not been set as an important agenda item. In the future, the sharing and development of relevant databases is necessary. In addition, the priority of agenda items should be determined as part of a government initiative.

Why would people conform more to others with higher social positions? People may place higher confidence in the opinions of those who rank higher in the social hierarchy, or they may wish to make better impressions on people of higher social status. We investigated how individual preferences for novel stimuli are influenced by the preferences of others in the social hierarchy and whether anonymity affects such preference changes. After manipulation of their social rank, participants were asked to indicate how much they liked or disliked a series of images. Then, they were shown the rating given to each image by a partner (either inferior or superior in social rank) and were given a chance to adjust their ratings. The participants were more likely to change their preferences to match those of a superior partner in the public vs. private condition. The tendency to conform to the views of the superior partner was stronger among those with higher social dominance orientation (SDO) and those with greater fear of negative evaluation (FNE) by others. Altogether, the findings suggest that the motivation to make better impressions on people of higher social status can be the major driver of conformity to others with higher social positions.

Moving object detection and tracking are technologies applied to wide research fields including traffic monitoring and recognition of workers in surrounding heavy equipment environments. However, the conventional moving object detection methods have faced many problems such as much computing time, image noises, and disappearance of targets due to obstacles. In this paper, we introduce a new moving object detection and tracking algorithm based on the sparse optical flow for reducing computing time, removing noises and estimating the target efficiently. The developed algorithm maintains a variety of corner features with refreshed corner features, and the moving window detector is proposed to determine the feature points for tracking, based on the location history of the points. The performance of detecting moving objects is greatly improved through the moving window detector and the continuous target estimation. The memory-based estimator provides the capability to recall the location of corner features for a period of time, and it has an effect of tracking targets obscured by obstacles. The suggested approach was applied to real environments including various illumination (indoor and outdoor) conditions, a number of moving objects and obstacles, and the performance was evaluated on an embedded board (Raspberry pi4). The experimental results show that the proposed method maintains a high FPS (frame per seconds) and improves the accuracy performance, compared with the conventional optical flow methods and vision approaches such as Haar-like and Hog methods.

Visual homing navigation has been a challenging issue in indoor localization and navigation. Inspired by insect navigation, the snapshot model was introduced for homing navigation, where a pair of snapshots at the current location and at the nest are compared to guide the homing direction. We investigate Haar-like features in vision to extract visual cues, based on the snapshot model. The Haar-like features consist of masks randomly generated over the snapshot image at the home location, and later, their matching scores at the snapshot available at the current location are calculated for the correspondence measure. We draw landmark vectors using the correspondence measure of Haar-like features at their angular positions. Interestingly, a collection of Haar-like features provide visual characteristics to reflect a pair of snapshot images, which can determine the homing direction. In this paper, we propose two types of homing methods based on the image difference using Haar-like features, the Haar-like landmark vector model and the Haar-like image distance model. We demonstrate the effectiveness of the methods in several environments.

For local homing navigation, a mobile robot is supposed to return home using snapshots of the surrounding environment. It basically follows the snapshot model, comparing the home snapshot and the current view to determine the homing direction. In this paper, we suggest a high-order moment potential to describe the landmark feature distribution for local homing navigation. The moment potential function calculates the sum of products of the feature and the distance of landmark particles as a holistic view, allowing a high order of the distance. It effectively combines the range sensor values of landmarks in the current view and the visual features. By analogy with the moment in physics, the center of the moment is estimated as the reference point, which is the unique convergence point in the convex moment potential from any view, and using the property, the gradient of moment potential at the current position and home location can derive the homing vector. We provide a proof of convergence for any moment potential with order greater than or equal to one. Also, we demonstrate homing performances with various moment models in real environments to validate our models. The suggested moment models combining both landmark distance and visual feature have better performances than the visual information alone, and high-order moment potentials can be searched to obtain a better description of landmark distribution for a given environment.

Mobile robots and their applications are involved with many research fields including electrical engineering, mechanical engineering, computer science, artificial intelligence and cognitive science [...]

Intelligent imaging and analysis have been studied in various research fields, including medical imaging, biomedical applications, computer vision, visual inspection and robot systems [...]

The electrocardiogram (ECG) waveform conveys information regarding the electrical property of the heart. The patterns vary depending on the individual heart characteristics. ECG features can be potentially used for biometric recognition. This study presents a new method using the entire ECG waveform pattern for matching and demonstrates that the approach can potentially be employed for individual biometric identification. Multi-cycle ECG signals were assessed using an ECG measuring circuit, and three electrodes can be patched on the wrists or fingers for considering various measurements. For biometric identification, our-fold cross validation was used in the experiments for assessing how the results of a statistical analysis will generalize to an independent data set. Four different pattern matching algorithms, i.e., cosine similarity, cross correlation, city block distance, and Euclidean distances, were tested to compare the individual identification performances with a single channel of ECG signal (3-wire ECG). To evaluate the pattern matching for biometric identification, the ECG recordings for each subject were partitioned into training and test set. The suggested method obtained a maximum performance of 89.9% accuracy with two heartbeats of ECG signals measured on the wrist and 93.3% accuracy with three heartbeats for 55 subjects. The performance rate with ECG signals measured on the fingers improved up to 99.3% with two heartbeats and 100% with three heartbeats of signals for 20 subjects.

This paper presents a distributed coordination methodology for multi-robot systems, based on nearest-neighbor interactions. Among many interesting tasks that may be performed using swarm robots, we propose a biologically-inspired control law for a shepherding task, whereby a group of external agents drives another group of agents to a desired location. First, we generated sheep-like robots that act like a flock. We assume that each agent is capable of measuring the relative location and velocity to each of its neighbors within a limited sensing area. Then, we designed a control strategy for shepherd-like robots that have information regarding where to go and a steering ability to control the flock, according to the robots’ position relative to the flock. We define several independent behavior rules; each agent calculates to what extent it will move by summarizing each rule. The flocking sheep agents detect the steering agents and try to avoid them; this tendency leads to movement of the flock. Each steering agent only needs to focus on guiding the nearest flocking agent to the desired location. Without centralized coordination, multiple steering agents produce an arc formation to control the flock effectively. In addition, we propose a new rule for collecting behavior, whereby a scattered flock or multiple flocks are consolidated. From simulation results with multiple robots, we show that each robot performs actions for the shepherding behavior, and only a few steering agents are needed to control the whole flock. The results are displayed in maps that trace the paths of the flock and steering robots. Performance is evaluated via time cost and path accuracy to demonstrate the effectiveness of this approach.

[-10]For local homing navigation, an agent is supposed to return home based on the surrounding environmental information. According to the snapshot model, the home snapshot and the current view are compared to determine the homing direction. In this paper, we propose a novel homing navigation method using the moment model. The suggested moment model also follows the snapshot theory to compare the home snapshot and the current view, but the moment model defines a moment of landmark inertia as the sum of the product of the feature of the landmark particle with the square of its distance. The method thus uses range values of landmarks in the surrounding view and the visual features. The center of the moment can be estimated as the reference point, which is the unique convergence point in the moment potential from any view. The homing vector can easily be extracted from the centers of the moment measured at the current position and the home location. The method effectively guides homing direction in real environments, as well as in the simulation environment. In this paper, we take a holistic approach to use all pixels in the panoramic image as landmarks and use the RGB color intensity for the visual features in the moment model in which a set of three moment functions is encoded to determine the homing vector. We also tested visual homing or the moment model with only visual features, but the suggested moment model with both the visual feature and the landmark distance shows superior performance. We demonstrate homing performance with various methods classified by the status of the feature, the distance and the coordinate alignment.

A number of landmark-based navigation algorithms have been studied using feature extraction over the visual information. In this paper, we apply the distance information of the surrounding environment in a landmark navigation model. We mount a depth sensor on a mobile robot, in order to obtain omnidirectional distance information. The surrounding environment is represented as a circular form of landmark vectors, which forms a snapshot. The depth snapshots at the current position and the target position are compared to determine the homing direction, inspired by the snapshot model. Here, we suggest a holistic view of panoramic depth information for homing navigation where each sample point is taken as a landmark. The results are shown in a vector map of homing vectors. The performance of the suggested method is evaluated based on the angular errors and the homing success rate. Omnidirectional depth information about the surrounding environment can be a promising source of landmark homing navigation. We demonstrate the results that a holistic approach with omnidirectional depth information shows effective homing navigation.

Rats use their whiskers as tactile sensors to sense their environment. Active whisking, moving whiskers back and forth continuously, is one of prominent features observed in rodents. They can discriminate different textures or extract features of a nearby object such as size, shape and distance through active whisking. There have been studies to localize objects with artificial whiskers inspired by rat whiskers. The linear whisker model based on beam theory has been used to estimate the radial distance, that is, the distance between the base of the whisker and a target object. In this paper, we investigate deflection angle measurements instead of forces or moments, based on a linear tapered whisker model to see the role of tapered whiskers found in real animals. We analyze how accurately this model estimates the radial distance, and quantify the estimation errors and noise sensitivity. We also compare the linear model simulation and nonlinear numerical solutions. It is shown that the radial distance can be estimated using deflection angles at two different positions on the tapered whisker. We argue that the tapered whisker has an advantage of estimating the radial distance better, as compared to an untapered whisker, and active sensing allows that estimation without the whisker’s material property and thickness or the moment at base. In addition, we investigate the potential of passive sensing for tactile localization.

Dynamic task allocation is a necessity in a group of robots. Each member should decide its own task such that it is most commensurate with its current state in the overall system. In this work, the response threshold model is applied to a dynamic foraging task. Each robot employs a task switching function based on the local task demand obtained from the surrounding environment, and no communication occurs between the robots. Each individual member has a constant-sized task demand history that reflects the global demand. In addition, it has response threshold values for all of the tasks and manages the task switching process depending on the stimuli of the task demands. The robot then determines the task to be executed to regulate the overall division of labor. This task selection induces a specialized tendency for performing a specific task and regulates the division of labor. In particular, maintaining a history of the task demands is very effective for the dynamic foraging task. Various experiments are performed using a simulation with multiple robots, and the results show that the proposed algorithm is more effective as compared to the conventional model.

People often align their behaviors and decisions with others' expectations, especially those of higher social positions, when they are being observed. However, little attention has been paid to the neural mechanisms underlying increased conformity to the social hierarchy under social observation. Using a preference rating task, we investigated whether and how individual preferences for novel stimuli were influenced by others' preferences by manipulating others' social hierarchy and observational context. The behavioral results showed that human participants of both sexes were more likely to change their preferences to match those of a superior partner in a public than in a private context. fMRI data revealed distinct contributions of the subregions of the medial prefrontal cortex (mPFC) to increased conformity to social hierarchy under observation. Specifically, the ventral mPFC showed increased activity when participants' preferences aligned with those of superior partners, regardless of behavioral manifestation. The rostral mPFC showed increased activity when conforming to a superior partner and nonconforming to an inferior one, indicating goal-dependent valuation. The dorsal mPFC showed increased activity in private conditions with a superior partner but only in those with a higher tendency to conform. These findings support the hierarchical allostatic regulation model of the mPFC function for social valuation and suggest strategic conformity as a way to minimize metabolic costs. [ABSTRACT FROM AUTHOR]