Concept: Center of mass
The objective of this study was to determine whether kinematic data collected by the Microsoft Kinect 2 (MK2) could be used to quantify postural stability in healthy subjects. Twelve subjects were recruited for the project, and were instructed to perform a sequence of simple postural stability tasks. The movement sequence was performed as subjects were seated on top of a force platform, and the MK2 was positioned in front of them. This sequence of tasks was performed by each subject under three different postural conditions: “both feet on the ground” (1), “One foot off the ground” (2), and “both feet off the ground” (3). We compared force platform and MK2 data to quantify the degree to which the MK2 was returning reliable data across subjects. We then applied a novel machine-learning paradigm to the MK2 data in order to determine the extent to which data from the MK2 could be used to reliably classify different postural conditions. Our initial comparison of force plate and MK2 data showed a strong agreement between the two devices, with strong Pearson correlations between the trunk centroids “Spine_Mid” (0.85 ± 0.06), “Neck” (0.86 ± 0.07) and “Head” (0.87 ± 0.07), and the center of pressure centroid inferred by the force platform. Mean accuracy for the machine learning classifier from MK2 was 97.0%, with a specific classification accuracy breakdown of 90.9%, 100%, and 100% for conditions 1 through 3, respectively. Mean accuracy for the machine learning classifier derived from the force platform data was lower at 84.4%. We conclude that data from the MK2 has sufficient information content to allow us to classify sequences of tasks being performed under different levels of postural stability. Future studies will focus on validating this protocol on large populations of individuals with actual balance impairments in order to create a toolkit that is clinically validated and available to the medical community.
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.
In order to stimulate appropriate antimicrobial use and thereby lower the chances of resistance development, an Antibiotic Stewardship Team (A-Team) has been implemented at the University Medical Center Groningen, the Netherlands. Focus of the A-Team was a pro-active day 2 case-audit, which was financially evaluated here to calculate the return on investment from a hospital perspective.
Patients with apraxia perform poorly when demonstrating how an object is used, particularly when pantomiming the action. However, these patients are able to accurately identify, and to pick up and move objects, demonstrating intact ventral and dorsal stream visuomotor processing. Appropriate object manipulation for skilled use is thought to rely on integration of known and visible object properties associated with “ventro-dorsal” stream neural processes. In apraxia, it has been suggested that stored object knowledge from the ventral stream may be less readily available to incorporate into the action plan, leading to an over-reliance on the objects' visual affordances in object-directed motor behavior. The current study examined grasping performance in left hemisphere stroke patients with (N = 3) and without (N = 9) apraxia, and in age-matched healthy control participants (N = 14), where participants repeatedly grasped novel cylindrical objects of varying weight distribution. Across two conditions, object weight distribution was indicated by either a memory-associated cue (object color) or visual-spatial cue (visible dot over the weighted end). Participants were required to incorporate object-weight associations to effectively grasp and balance each object. Control groups appropriately adjusted their grasp according to each object’s weight distribution across each condition, whereas throughout the task two of the three apraxic patients performed poorly on both the memory-associated and visual-spatial cue conditions. A third apraxic patient seemed to compensate for these difficulties but still performed differently to control groups. Patients with apraxia performed normally on the neutral control condition when grasping the evenly weighted version. The pattern of behavior in apraxic patients suggests impaired integration of visible and known object properties attributed to the ventro-dorsal stream: in learning to grasp the weighted object accurately, apraxic patients applied neither pure knowledge-based information (the memory-associated condition) nor higher-level information given in the visual-spatial cue condition. Disruption to ventro-dorsal stream predicts that apraxic patients will have difficulty learning to manipulate new objects on the basis of information other than low-level visual cues such as shape and size.
The spatial distribution of nine Northwest Atlantic groundfish stocks was documented using spatial indicators based on Northeast Fisheries Science Center spring and fall bottom trawl survey data, 1963-2016. We then evaluated the relative importance of population size, fishing pressure and bottom temperature on spatial distribution with an information theoretic approach. Northward movement in the spring was generally consistent with prior analyses, whereas changes in depth distribution and area occupancy were not. Only two stocks exhibited the same changes in spatiotemporal distribution in the fall as compared with the spring. Fishing pressure was the most important predictor of the center of gravity (i.e., bivariate mean location of the population) for the majority of stocks in the spring, whereas in the fall this was restricted to the east-west component. Fishing pressure was also the most important predictor of the dispersion around the center of gravity in both spring and fall. In contrast, biomass was the most important predictor of area occupancy for the majority of stocks in both seasons. The relative importance of bottom temperature was ranked highest in the fewest number of cases. This study shows that fishing pressure, in addition to the previously established role of climate, influences the spatial distribution of groundfish in the Northwest Atlantic. More broadly, this study is one of a small but growing body of literature to demonstrate that fishing pressure has an effect on the spatial distribution of marine resources. Future work must consider both fishing pressure and climate when examining mechanisms underlying fish distribution shifts.
A head-mounted display (HMD) with inappropriate mass and center of mass (COM) increases the physical workload of HMD users. The aim of this study was to investigate the effects of mass and COM of HMD on physical workload. Twelve subjects participated in this study. The mass and posteroanterior COM position were 0.8, 1.2, or 1.6 kg and -7.0, 0.0, or 7.0 cm, respectively. The subjects gazed at the target objects in four test postures: the neutral, look-up, body-bending, and look-down postures. The normalized joint torques for the neck and the lumbar region were calculated based on the measured segment angles. The results showed that the neck joint torque was significantly affected by mass and COM and it increased as the HMD mass increased for all test postures. The COM position that minimized the neck joint torque varied depending on the test postures, and the recommended ranges of COM were identified.
A human’s center of mass (COM) is a widely used parameter in both clinical and practical applications. The segmental analysis method for determining the COM is considered the gold standard but is difficult to apply in a real environment.
Center of mass (CoM) velocity variation in swimming direction is related to swimming performance and efficiency. However, it is difficult to calculate the CoM velocity during swimming. Therefore, we aimed to establish a practical estimation method for the CoM velocity in swimming direction during front-crawl swimming with underwater cameras. Ten swimmers were recorded during front-crawl swimming (25 m, maximal effort) using a motion capture system with 18 underwater and 9 land cameras. Three CoM velocity estimation methods were constructed (single-hip velocity, both-hips velocity, and both-hips velocity with simulated arm velocity correction). Each model was validated against the actual CoM velocity. The difference between the single-hip velocity and the actual CoM velocity in swimming direction was significantly larger compared to that for the other 2 models. Furthermore, the accuracy of CoM velocity estimation was increased when both-hips velocity was corrected using the simulated arm velocity. The method allowed estimation of the CoM velocity with only 2 underwater cameras with a maximal difference of 0.06 m・s-1. This study established a novel and practical method for the estimation of the CoM velocity in swimming direction during front-crawl swimming.
In this paper, we are interested in computing ZIP code proximity from two perspectives, proximity between two ZIP codes (Ad-Hoc) and neighborhood proximity (Top-K). Such a computation can be used for ZIP code-based target marketing as one of the smart city applications. A naïve approach to this computation is the usage of the distance between ZIP codes. We redefine a distance metric combining the centroid distance with the intersecting road network between ZIP codes by using a weighted sum method. Furthermore, we prove that the results of our combined approach conform to the characteristics of distance measurement. We have proposed a general and heuristic approach for computingAd-Hocproximity, while for computingTop-Kproximity, we have proposed a general approach only. Our experimental results indicate that our approaches are verifiable and effective in reducing the execution time and search space.
Balance changes during pregnancy likely occur because of mass gains and mass distribution changes. However, to date there is no way of tracking balance through center of mass motion because no method is available to identify of the body center of mass throughout pregnancy. We compared methods for determining segment masses and torso center of mass location. The availability of a method for tracking these changes during pregnancy will make determining balance changes through center of mass motion an option for future pregnancy balance research. Thirty pregnant women from eight weeks gestation until birth were recruited for monthly anthropometric measurements, motion capture analysis of body segment locations, and force plate analysis of center of pressure during quiet standing and supine laying. From these measurements, we were able to compare regression, volume measurement, and weighted sum methods to calculate body center of mass throughout pregnancy. We found that mass changes around the trunk were most prevalent as expected, but mass changes throughout the body (especially the thighs) were also seen. Our findings also suggest that a series of anthropometric measurements first suggested by Pavol et al. (2002), in combination with quiet standing on a force plate, can be used to identify the needed components (segment masses and torso center of mass location in three dimensions) to calculate body center of mass changes during pregnancy. The results of this study will make tracking of center of mass motion a possibility for future pregnancy balance research.