CMMSE: Study of a new symmetric anomaly in the elliptic, hyperbolic and parabolic Keplerian motion

In the present work, we define a new anomaly, $\Psi$, termed semifocal anomaly. It is determined by the mean between the true anomaly, $f$, and the antifocal anomaly, $f^{\prime}$; Fukushima defined $f^{\prime}$ as the angle between the periapsis and the secondary around the empty focus. In this first part of the paper, we take an approach to the study of the semifocal anomaly in the hyperbolic motion and in the limit case correspoding to the parabolic movement. From here we find a relation beetween the semifocal anomaly and the true anomaly that holds independently of the movement type. We focus on the study of the two-body problem when this new anomaly is used as the temporal variable.\\ In the second part, we show the use of this anomaly —combined with numerical integration methods— to improve integration errors in one revolution. Finally, we analyze the errors committed in the integration process —depending on several values of the eccentricity— for the elliptic, parabolic and hyperbolic cases in the apsidal region.

How often should dead-reckoned animal movement paths be corrected for drift?

Background Understanding what animals do in time and space is important for a range of ecological questions, however accurate estimates of how animals use space is challenging. Within the use of animal-attached tags, radio telemetry (including the Global Positioning System, ‘GPS’) is typically used to verify an animal’s location periodically. Straight lines are typically drawn between these ‘Verified Positions’ (‘VPs’) so the interpolation of space-use is limited by the temporal and spatial resolution of the system’s measurement. As such, parameters such as route-taken and distance travelled can be poorly represented when using VP systems alone. Dead-reckoning has been suggested as a technique to improve the accuracy and resolution of reconstructed movement paths, whilst maximising battery life of VP systems. This typically involves deriving travel vectors from motion sensor systems and periodically correcting path dimensions for drift with simultaneously deployed VP systems. How often paths should be corrected for drift, however, has remained unclear. Methods and results Here, we review the utility of dead-reckoning across four contrasting model species using different forms of locomotion (the African lion Panthera leo, the red-tailed tropicbird Phaethon rubricauda, the Magellanic penguin Spheniscus magellanicus, and the imperial cormorant Leucocarbo atriceps). Simulations were performed to examine the extent of dead-reckoning error, relative to VPs, as a function of Verified Position correction (VP correction) rate and the effect of this on estimates of distance moved. Dead-reckoning error was greatest for animals travelling within air and water. We demonstrate how sources of measurement error can arise within VP-corrected dead-reckoned tracks and propose advancements to this procedure to maximise dead-reckoning accuracy. Conclusions We review the utility of VP-corrected dead-reckoning according to movement type and consider a range of ecological questions that would benefit from dead-reckoning, primarily concerning animal–barrier interactions and foraging strategies.

A different point of view: the evaluation of motor imagery perspectives in patients with sensorimotor impairments in a longitudinal study

Background Motor imagery (MI) has been successfully applied in neurological rehabilitation. Little is known about the spontaneous selection of the MI perspectives in patients with sensorimotor impairments. What perspective is selected: internal (first-person view), or external (third-person view)? The aim was to evaluate the MI perspective preference in patients with sensorimotor impairments. Methods In a longitudinal study including four measurement sessions, 55 patients (25 stroke, 25 multiple sclerosis, 5 Parkinson’s disease; 25 females; mean age 58 ± 14 years) were included. MI ability and perspective preference in both visual and kinaesthetic imagery modalities were assessed using the Kinaesthetic and Visual Imagery Questionnaire-20 (KVIQ-20), the body rotation task (BRT), and mental chronometry (MC). Additionally, patients’ activity level was assessed. Descriptive analyses were performed regarding different age- (< 45, 45–64, > 64), activity levels (inactive, partially active, active), and KVIQ-20 movement classifications (axial, proximal, distal, upper and lower limb). A mixed-effects model was used to investiage the relationship between the primary outcome (MI perspective: internal, external) with the explanatory variables age, MI modality (visual, kinaesthetic), movement type (axial, proximal, distal), activity levels and the different assessments (KVIQ-20, BRT, MC). Results Imagery modality was not a significant predictor of perspective preference. Over the four measurement sessions, patients tended to become more consistent in their perspective selection, however, time point was not a significant predictor. Movement type was a significant predictor: imagination of distal vs. axial and proximal vs. axial movements were both associated with preference for external perspective. Patients with increased physical activity level tend to use internal imagery, however, this effect was borderline not statistically significant. Age was neither a significant precictor. Regarding the MI assessments, the KVIQ- 20 score was a significant predictor. The patients with higher test scores tend to use the external perspective. Conclusion It is recommended to evaluate the spontaneous MI perspective selection to design patient-specific MI training interventions. Distal movements (foot, finger) may be an indicator when evaluating the consistency of the MI perspective in patients with sensorimotor impairments.

How Often Should Dead-Reckoned Animal Movement Paths be Corrected for Drift?

BackgroundUnderstanding what animals do in time and space is important for a range of ecological questions, however accurate estimates of how animals use space is challenging. Within the use of animal-attached tags, radio telemetry (including the Global Positioning System (GPS)) is typically used to verify an animal’s location periodically. Straight lines are typically drawn between these ‘Verified Positions’ (VPs) so the interpolation of space-use is limited by the temporal- and spatial resolution of the system’s measurement. As such, parameters such as route-taken and distance travelled can be poorly represented when using VP systems alone. Dead-reckoning has been suggested as a technique to improve the accuracy and resolution of reconstructed movement paths, whilst maximising battery life of VP systems. This typically involves deriving travel vectors from motion sensor systems and periodically correcting path dimensions for drift with simultaneously deployed VP systems. How often paths should be corrected for drift, however, has remained unclear.Methods & ResultsHere, we review the utility of dead-reckoning across four contrasting model species using different forms of locomotion (the African lion Panthera leo, the Red-tailed tropicbird Phaethon rubricauda, the Magellanic penguin Spheniscus magellanicus, and the Imperial cormorant Leucocarbo atriceps). Simulations were performed to examine the extent of dead-reckoning error, relative to VPs, as a function of Verified Position correction (VP correction) rate and the effect of this on estimates of distance moved. Dead-reckoning error was greatest for animals travelling within air and water. We demonstrate how sources of measurement error can arise within VP-corrected dead-reckoned tracks and propose advancements to this procedure to maximise dead-reckoning accuracy.ConclusionsWe review the utility of VP-corrected dead-reckoning according to movement type and consider a range of ecological questions that would benefit from dead-reckoning, primarily concerning animal-barrier interactions and foraging strategies.

The Characteristics of Northeast China Cold Vortex With Different Active Paths in June and Their Relationship With Precipitation and Pre-SST

In this study, a K-means clustering (KMC) method was used to identify the paths of the Northeast China (NEC) Cold Vortex (NCCV). The NCCV was divided into four types according to the identified active paths: (1) Eastward movement type (EM); (2) Southeastward long-distance movement type (SLM); (3) Eastward short-distance movement type (ESM); and (4) Southward short-distance movement type (SSM). The characteristics of the four types of the NCCV, along with their impacts on the precipitation during early summer in NEC, were studied. The results showed that the KMC method can effectively divide the NCCV events into four different types. The maintaining days of these four types of the NCCV were found to have obvious interannual and interdecadal variation features. For example, the maintaining days of the EM and ESM types were mainly characterized by interannual variability, while the SLM and SSM types have the obvious 10–13a interdecadal variation along with interannual variability. In terms of the spatial distributions and impacts on precipitation, the EM type was found to appear in the majority of the areas located in NEC, the SLM type mainly occurred in the northwestern region of NEC and the highest rain center was located in the south-central portion, while the ESM type and SSM type were observed precipitation only appear in a small portion of the northeastern region. In addition, it is also observed the distribution of the sea-surface temperature (SST) anomalies had close relationship with the formation of these four types of the NCCV. The tripole distributions of the SST anomalies in the Atlantic Ocean corresponded to the EM type of the NCCV, the positive anomalies of SST in the eastern equatorial Pacific Ocean and negative anomalies in the western equatorial Pacific corresponded to the SLM type, the positive SSTs in the Northwest Pacific correspond to the ESM type, while negative anomalies SST in the western equatorial Pacific Ocean corresponded to the SSM type of the NCCV.

Predicting lying, sitting, walking and running using Apple Watch and Fitbit data

ObjectivesThis study’s objective was to examine whether commercial wearable devices could accurately predict lying, sitting and varying intensities of walking and running.MethodsWe recruited a convenience sample of 49 participants (23 men and 26 women) to wear three devices, an Apple Watch Series 2, a Fitbit Charge HR2 and iPhone 6S. Participants completed a 65 min protocol consisting of 40 min of total treadmill time and 25 min of sitting or lying time. The study’s outcome variables were six movement types: lying, sitting, walking self-paced and walking/running at 3 metabolic equivalents of task (METs), 5 METs and 7 METs. All analyses were conducted at the minute level with heart rate, steps, distance and calories from Apple Watch and Fitbit. These included three different machine learning models: support vector machines, Random Forest and Rotation forest.ResultsOur dataset included 3656 and 2608 min of Apple Watch and Fitbit data, respectively. Rotation Forest models had the highest classification accuracies for Apple Watch at 82.6%, and Random Forest models had the highest accuracy for Fitbit at 90.8%. Classification accuracies for Apple Watch data ranged from 72.6% for sitting to 89.0% for 7 METs. For Fitbit, accuracies varied between 86.2% for sitting to 92.6% for 7 METs.ConclusionThis preliminary study demonstrated that data from commercial wearable devices could predict movement types with reasonable accuracy. More research is needed, but these methods are a proof of concept for movement type classification at the population level using commercial wearable device data.

Global Temporal Movement Control

Complex movements require the fine-tuned temporal interplay of several effectors. If the temporal properties of one of these effectors were distorted, all other movement plans would need to be updated in order to produce successful behavior. This requirement of a global motor time stands in direct contrast to the multiple duration-channels in visual time. We explored whether time-critical and goal-oriented movements are indeed globally affected by temporal recalibration. In a ready-set-go paradigm, participants reproduced the interval between ready- and set-signals by performing different movements in Virtual Reality (VR). Halfway through the experiments, movements in VR were artificially slowed down, so that participants had to adapt their behavior. In three experiments, we found that these adaptation effects were not affected by movement type, interval range, location, or environmental context. We conclude that the temporal planning of motor actions is recalibrated globally, suggesting the presence of a global temporal movement controller.

Investigating the Intervention Parameters of Endogenous Paired Associative Stimulation (ePAS)

Advances in our understanding of neural plasticity have prompted the emergence of neuromodulatory interventions, which modulate corticomotor excitability (CME) and hold potential for accelerating stroke recovery. Endogenous paired associative stimulation (ePAS) involves the repeated pairing of a single pulse of peripheral electrical stimulation (PES) with endogenous movement-related cortical potentials (MRCPs), which are derived from electroencephalography. However, little is known about the optimal parameters for its delivery. A factorial design with repeated measures delivered four different versions of ePAS, in which PES intensities and movement type were manipulated. Linear mixed models were employed to assess interaction effects between PES intensity (suprathreshold (Hi) and motor threshold (Lo)) and movement type (Voluntary and Imagined) on CME. ePAS interventions significantly increased CME compared to control interventions, except in the case of Lo-Voluntary ePAS. There was an overall main effect for the Hi-Voluntary ePAS intervention immediately post-intervention (p = 0.002), with a sub-additive interaction effect at 30 min’ post-intervention (p = 0.042). Hi-Imagined and Lo-Imagined ePAS significantly increased CME for 30 min post-intervention (p = 0.038 and p = 0.043 respectively). The effects of the two PES intensities were not significantly different. CME was significantly greater after performing imagined movements, compared to voluntary movements, with motor threshold PES (Lo) 15 min post-intervention (p = 0.012). This study supports previous research investigating Lo-Imagined ePAS and extends those findings by illustrating that ePAS interventions that deliver suprathreshold intensities during voluntary or imagined movements (Hi-Voluntary and Hi-Imagined) also increase CME. Importantly, our findings indicate that stimulation intensity and movement type interact in ePAS interventions. Factorial designs are an efficient way to explore the effects of manipulating the parameters of neuromodulatory interventions. Further research is required to ensure that these parameters are appropriately refined to maximise intervention efficacy for people with stroke and to support translation into clinical practice.

Estimating Center of Mass Kinematics During Perturbed Human Standing Using Accelerometers

Estimating center of mass (COM) through sensor measurements is done to maintain walking and standing stability with exoskeletons. The authors present a method for estimating COM kinematics through an artificial neural network, which was trained by minimizing the mean squared error between COM displacements measured by a gold-standard motion capture system and recorded acceleration signals from body-mounted accelerometers. A total of 5 able-bodied participants were destabilized during standing through: (1) unexpected perturbations caused by 4 linear actuators pulling on the waist and (2) volitionally moving weighted jars on a shelf. Each movement type was averaged across all participants. The algorithm’s performance was quantified by the root mean square error and coefficient of determination (R2) calculated from both the entire trial and during each perturbation type. Throughout the trials and movement types, the average coefficient of determination was 0.83, with 89% of the movements with R2 > .70, while the average root mean square error ranged between 7.3% and 22.0%, corresponding to 0.5- and 0.94-cm error in both the coronal and sagittal planes. COM can be estimated in real time for balance control of exoskeletons for individuals with a spinal cord injury, and the procedure can be generalized for other gait studies.