Motion Signatures Research Articles

Intermittent subdiffusion of short nuclear actin rods due to interactions with chromatin.

The interior of cellular nuclei, the nucleoplasm, is a crowded fluid that is pervaded by protein-decorated DNA polymers, the chromatin. Due to the complex architecture of chromatin and a multitude of associated nonequilibrium processes, e.g., DNA repair, the nucleoplasm can be expected to feature nontrivial material properties and hence anomalous transport phenomena. Here, we have used single-particle tracking on nuclear actin rods to probe such transport phenomena. Our analysis reveals that short actin rods in the nucleus show an intermittent, antipersistent subdiffusion with clear signatures of fractional Brownian motion. Moreover, the diffusive motion is heterogeneous with clear signatures of an intermittent switching of trajectories between at least two different mobilities, most likely due to transient associations with chromatin. In line with this interpretation, hyperosmotic stress is seen to stall the motion of nuclear actin rods, whereas hypo-osmotic conditions yield a reptationlike motion. Our data highlights the heterogeneity of transport in the nucleoplasm that needs to be taken into account for an understanding of nucleoplasmic organization and the mechanobiology of nuclei.

Tracer dynamics in the active random average process

We investigate the dynamics of tracer particles in the random average process (RAP), a single-file system in one dimension. In addition to the position, every particle possesses an internal spin variable σ(t) that can alternate between two values, ±1, at a constant rate γ. Physically, the value of σ(t) dictates the direction of motion of the corresponding particle and, for finite γ, every particle performs non-Markovian active dynamics. Herein, we study the effect of this non-Markovian behavior in the fluctuations and correlations of the positions of tracer particles. We analytically show that the variance of the position of a tagged particle grows sub-diffusively as ∼ζqt at large times for the quenched uniform initial conditions. While this sub-diffusive growth is identical to that of the Markovian/non-persistent RAP, the coefficient ζq is rather different and bears the signature of the persistent motion of active particles through higher-point correlations (unlike in the Markovian case). Similarly, for the annealed (steady-state) initial conditions, we find that the variance scales as ∼ζat at large times, with the coefficient ζa once again different from the non-persistent case. Although both ζ q and ζa individually depart from their Markovian counterparts, their ratio ζa/ζq is still equal to 2 , a condition observed for other diffusive single-file systems. This condition turns out to be true even in the strongly active regimes, as corroborated by extensive simulations and calculations. Finally, we study the correlation between the positions of two tagged particles in both quenched uniform and annealed initial conditions. We verify all our analytical results using extensive numerical simulations.

Gait signatures of endurance runners with low back pain: A case controlled cross sectional study

BackgroundLow back pain (LBP) is an understudied condition among runners, and it is unclear what biomechanical features could be targeted for gait retraining to mitigate pain. Research questionHow do running biomechanics differ between healthy individuals and those with running-related LBP? MethodsThis was a case-controlled, comparative study design of community runners: running-related LBP (n=52) and healthy controls (n=52). All runners completed running history forms and performed a 3-dimensional gait analysis. Kinematic data were collected using a motion capture system and normalized to a gait cycle, while participants ran on a level grade at self-selected speed on an instrumented treadmill. Current running volume, temporal-spatial, kinetic and kinematic features were compared between groups. ResultsThe LBP group had 39.5 % lower weekly distance and 15.4 % fewer were currently training for a race (all p<.05). Runners with LBP demonstrated lower cadence (166±10 step/min vs. 171±9 step/min; p=.05), greater center of gravity lateral displacement (1.4±0.5 cm vs. 1.2 ±.3 cm; p=.044) and greater stride width variability (1.3±0.4 cm versus 1.0 ± 0.04 cm; p=.008). Runners with LBP had a greater Vertical Average Loading Rate ([VALR] 67.7±22.2 bodyweights [BW]/s vs. 62.2±21.5 BW/s; p=.022), and higher joint moments (N*m/(kg*m)) at the knee in the sagittal plane (2.13±0.50 vs. 1.87±0.56; p <.001), frontal plane (1.44±0.39 vs. 1.29±0.29; p=.013), and at the hip in the frontal plane (2.04±0.51 vs. 1.84±0.41; p=.024). No differences were found between groups in the pelvis, hip, knee, and ankle joint excursions in any plane of motion during a typical gait cycle. SignificanceThese collective motion signature may reflect challenges with control of motion and VALR in the presence of back pain. Cadence training to increase step rate, coupled with core/hip muscle activation, may be an important strategy to reduce motion variability, impact loading rate and pain symptoms while running.

Geometrical multiscale tortuosity of desert ant walking trajectories.

Desert ants stand out as some of the most intriguing insect navigators, having captured the attention of scientists for decades. This includes the structure of walking trajectories during goal approach and search behaviour for the nest and familiar feeding sites. In the present study, we analysed such trajectories with regard to changes in walking direction. The directional change of the ants was quantified, i.e. an angle θ between trajectory increments of a given arclength λ was computed. This was done for different length scales λ, according to our goal of analysing desert ant path characteristics with respect to length scale. First, varying λ through more than two orders of magnitude demonstrated Brownian motion characteristics typical of the random walk component of search behaviour. Unexpectedly, this random walk component was also present in - supposedly rather linear - approach trajectories. Second, there were small but notable deviations from a uniform angle distribution that is characteristic of random walks. This was true for specific search situations, mostly close to the (virtual) goal position. And third, experience with a feeder position resulted in straighter approaches and more focused searches, which was also true for nest searches, albeit to a lesser extent. Taken together, these results both verify and extend previous studies on desert ant path characteristics. Of particular interest are the ubiquitous Brownian motion signatures and specific deviations thereof close to the goal position, indicative of unexpectedly structured search behaviour.

Floating wind turbine motion signature in the far-wake spectral content – a wind tunnel experiment

Abstract. The growing interest in floating offshore wind turbines (FOWTs) is rooted in the potential source of increased offshore energy production. As the technology is still in a pre-industrial state, several questions remain to be addressed where little field data are available. This study uses physical modelling at a reduced scale to investigate the signature of the floating motions into the wake spectral content of a simplified FOWT model. A wind turbine model based on the actuator disc concept is placed in an atmospheric boundary layer wind tunnel and subjected to a range of surge, heave and pitch motions. The signatures of idealised sinusoidal motion and realistic broadband motion on the model’s wake at distances of 4.6 D (D being the disc diameter) and 8 D are measured through the use of a rake of single hot wires. The spectral analysis shows that harmonic motion leaves clear signatures in the far wake's energy spectra, mainly in the top tip region, while broadband motion does not leave easily detectable signatures.

Reversal of drift direction during the Laschamp geomagnetic excursion

Earth's magnetic field changes in both space and time: the temporal changes are called geomagnetic and paleomagnetic secular variations. Westward drift has been noted as a feature of secular variation for several centuries, but eastward drift has received less attention. We use three global geomagnetic field models covering the past 100 kyr to extend temporal coverage for tracking the zonal (azimuthal) motion of the radial magnetic field. The models we use are GGF100k (100–0 ka), GGFSS70 (70–15 ka), LSMOD.2 (50–30 ka); the extent of the models enables the inclusion of the extreme secular variations found during excursions, particularly the Laschamp excursion (42–40 ka). GGFSS70 and LSMOD.2 have higher temporal resolution than GGF100k, but their underlying data have poorer spatial coverage. Spatial structure is greatly diminished in all models for spherical harmonic degrees l>4.We use two types of time-longitude plots, one of the full radial field to expose reverse and intense flux patches at the core-mantle boundary. The second time-longitude plot is processed to enhance zonal motion signatures and allows us to use Radon drift analyses to uncover characteristic time scales of both westward and eastward drift at mid to high latitudes in both the northern and southern hemispheres. Our results differ across the three models, which we attribute to varying degrees of resolution, accuracy, and data distribution. Nevertheless, recurrent episodes of both eastward and westward drift ranging from ±0.05o/yr to ±0.18o/yr occur in both the northern and southern hemispheres. Westward drift dominates. We also observe 8–20 kyr intervals between occurrences of high-latitude reverse flux patches correlated with strong drift signals. Focusing on the period 50–30 ka, we observe dominant eastward drift preceding the Laschamp excursion and westward drift subsequently. In a period not associated with an excursion, 90–80 ka, we see strong mid to high latitude drift signatures in the northern hemisphere.

A New Multi-resolution Analysis Method for Electrooculography Signals.

Electrooculography (EOG) signals indicate the degree and direction of eye movements. Hence, EOG signals have been useful in eye movement controlled rehabilitation systems. Denoising and accurate identification of the type of eye movement in EOG signals are the major challenges in their analysis. The state-of-the-art techniques for EOG signal analysis concerning denoising and eye movement extraction are based on multi-resolution analysis using wavelet bases, such as Haar or Daubechies. However, these wavelets are designed for general purpose signal processing applications and hence are not optimized for the EOG signal structures. In this paper, we propose a new multi-resolution basis specific to the analysis of EOG signals. The scaling and wavelet functions for the basis are derived from the signatures of blinks and saccades respectively, and hence we name them as blinklets and saclets accordingly, thereby forming a new multi-resolution basis. These descriptors are found to be more effective than standard wavelets for EOG signals, signal denoising, and for identifying the different eye movement signatures such as saccades, blinks, smooth pursuits, and fixations, as tested on the Physiosig and Centre for Biomedical Cybernetics Eye Movement (CBC-EM) EOG Databases.

EarSet: A Multi-Modal Dataset for Studying the Impact of Head and Facial Movements on In-Ear PPG Signals

Photoplethysmography (PPG) is a simple, yet powerful technique to study blood volume changes by measuring light intensity variations. However, PPG is severely affected by motion artifacts, which hinder its trustworthiness. This problem is pressing in earables since head movements and facial expressions cause skin and tissue displacements around and inside the ear. Understanding such artifacts is fundamental to the success of earables for accurate cardiovascular health monitoring. However, the lack of in-ear PPG datasets prevents the research community from tackling this challenge. In this work, we report on the design of an ear tip featuring a 3-channels PPG and a co-located 6-axis motion sensor. This, enables sensing PPG data at multiple wavelengths and the corresponding motion signature from both ears. Leveraging our device, we collected a multi-modal dataset from 30 participants while performing 16 natural motions, including both head/face and full body movements. This unique dataset will greatly support research towards making in-ear vital signs sensing more accurate and robust, thus unlocking the full potential of the next-generation PPG-equipped earables.

Comparative Analysis of Audio Processing Techniques on Doppler Radar Signature of Human Walking Motion Using CNN Models.

Artificial intelligence (AI) radar technology offers several advantages over other technologies, including low cost, privacy assurance, high accuracy, and environmental resilience. One challenge faced by AI radar technology is the high cost of equipment and the lack of radar datasets for deep-learning model training. Moreover, conventional radar signal processing methods have the obstacles of poor resolution or complex computation. Therefore, this paper discusses an innovative approach in the integration of radar technology and machine learning for effective surveillance systems that can surpass the aforementioned limitations. This approach is detailed into three steps: signal acquisition, signal processing, and feature-based classification. A hardware prototype of the signal acquisition circuitry was designed for a Continuous Wave (CW) K-24 GHz frequency band radar sensor. The collected radar motion data was categorized into non-human motion, human walking, and human walking without arm swing. Three signal processing techniques, namely short-time Fourier transform (STFT), mel spectrogram, and mel frequency cepstral coefficients (MFCCs), were employed. The latter two are typically used for audio processing, but in this study, they were proposed to obtain micro-Doppler spectrograms for all motion data. The obtained micro-Doppler spectrograms were then fed to a simplified 2D convolutional neural networks (CNNs) architecture for feature extraction and classification. Additionally, artificial neural networks (ANNs) and 1D CNN models were implemented for comparative analysis on various aspects. The experimental results demonstrated that the 2D CNN model trained on the MFCC feature outperformed the other two methods. The accuracy rate of the object classification models trained on micro-Doppler features was 97.93%, indicating the effectiveness of the proposed approach.

A Novel Probabilistic Network Model for Estimating Cognitive-Gait Connection Using Multimodal Interface

Research in human gait analysis has captivated several computer vision researchers to solve human identification problems. The proposed work provides a novel approach for cognitive state estimation via multi-modal analysis. The advantage of multi-modal system is to provide adequate motion signatures with ensemble of multimodal gait data to ensure data reliability for classification. The relationship between human cognitive states and gait is predicted using both temporal and non-temporal probabilistic models. We estimate prior probability tables for non-temporal probabilistic model known as Simple Bayesian Model after analysing the data acquired from Inertial Measurement Unit (IMU), Electroencephalography (EEG) and multiple Kinect V2.0 sensors. A novel Dynamic Bayesian Network (DBN) is used as probabilistic temporal model for estimating most probable sequence of transitions among human cognitive states. We apply Gaussian Mixture Modelling with Expectation maximisation (GMM-EM) to tune transition and emission probabilities for maximizing the probability of the observed sequence. A promising estimation accuracy of 88.6% is obtained. Also, Principal Component Analysis (PCA) and k-nearest neighbour (kNN) algorithms are applied separately to calculate the input probabilities for DBN model. It is observed that both GMM-EM and k-NN based approaches outperform all the state-of-the-art techniques. Moreover, standard statistical tests are performed on acquired dataset to validate the experimental results.

Skipper: A Federated Siamese Network-Based Group Activity Segregator for IoMT Systems

The social IoMT-based activity-monitoring system comprises several devices with different datasets. It faces challenges like a collection of a global activity dataset which comprises a myriad of activities. In this article, we propose a federated Siamese network-based data-independent group activity segregator—Skipper—which aims to identify anomalies in an activity-monitoring social IoMT system. The novelty of this work is that Skipper does not require any dataset before its deployment, which removes the need for any prior training of the model for activity monitoring. As a proof of concept, we select activities pertaining to school environments to identify low-performing students in a classroom, who would require teachers’ close attention to ensure balanced growth and proper health. Skipper monitors the students independently for their motion signatures through a wearable device that consists of an accelerometer. A federated Siamese network calculates indices that signify the degree of similarity among the students’ activities. Skipper identifies the students who do not perform the same activity. With real-world implementations, we observe that Skipper requires network rates of 10 Kb/s, making it suitable for low bandwidth networks while we achieve just 20% CPU and 10 MB memory utilization on constrained edge devices. Further, with an increasing number of students up to 100, the time delay for final results is limited to 80 s. Hence, Skipper is a fast, easy, and accurate solution for recognizing outliers in IoMT social systems.

Direct Observational Evidence of the Multi-scale, Dynamical Mass Accretion Toward a High-mass Star-forming Hub-filament System

There is growing evidence that high-mass star formation and hub-filament systems (HFS) are intricately linked. The gas kinematics along the filaments and the forming high-mass star(s) in the central hub are in excellent agreement with the new generation of global hierarchical high-mass star formation models. In this paper, we present an observational investigation of a typical HFS cloud, G310.142+0.758 (G310 hereafter), which reveals unambiguous evidence of mass inflow from the cloud scale via the filaments onto the forming protostar(s) at the hub conforming with the model predictions. Continuum and molecular line data from the ATOMS and MALT90 surveys that cover different spatial scales are used. Three filaments (with a total mass of 5.7 ± 1.1 × 103 M ⊙) are identified converging toward the central hub region where several signposts of high-mass star formation have been observed. The hub region contains a massive clump (1280 ± 260 M ⊙) harboring a central massive core. Additionally, five outflow lobes are associated with the central massive core implying a forming cluster. The observed large-scale, smooth, and coherent velocity gradients from the cloud down to the core scale, and the signatures of infall motion seen in the central massive clump and core, clearly unveil a nearly continuous, multi-scale mass accretion/transfer process at a similar mass infall rate of ∼10−3 M ⊙ yr−1 over all scales, feeding the central forming high-mass protostar(s) in the G310 HFS cloud.

Attosecond delays between dissociative and non-dissociative ionization of polyatomic molecules

The interplay between electronic and nuclear motions in molecules is a central concept in molecular science. To what extent it influences attosecond photoionization delays is an important, still unresolved question. Here, we apply attosecond electron-ion coincidence spectroscopy and advanced calculations that include both electronic and nuclear motions to study the photoionization dynamics of CH4 and CD4 molecules. These molecules are known to feature some of the fastest nuclear dynamics following photoionization. Remarkably, we find no measurable delay between the photoionization of CH4 and CD4, neither experimentally nor theoretically. However, we measure and calculate delays of up to 20 as between the dissociative and non-dissociative photoionization of the highest-occupied molecular orbitals of both molecules. Experiment and theory are in quantitative agreement. These results show that, in the absence of resonances, even the fastest nuclear motion does not substantially influence photoionization delays, but identify a previously unknown signature of nuclear motion in dissociative-ionization channels. These findings have important consequences for the design and interpretation of attosecond chronoscopy in molecules, clusters, and liquids.

Pontine Waves Accompanied by Short Hippocampal Sharp Wave-Ripples During Non-rapid Eye Movement Sleep.

Ponto-geniculo-occipital or pontine (P) waves have long been recognized as an electrophysiological signature of rapid eye movement (REM) sleep. However, P-waves can be observed not just during REM sleep, but also during non-REM (NREM) sleep. Recent studies have uncovered that P-waves are functionally coupled with hippocampal sharp wave ripples (SWRs) during NREM sleep. However, it remains unclear to what extent P-waves during NREM sleep share their characteristics with P-waves during REM sleep and how the functional coupling to P-waves modulates SWRs. Here, we address these issues by performing multiple types of electrophysiological recordings and fiber photometry in both sexes of mice. P-waves during NREM sleep share their waveform shapes and local neural ensemble dynamics at a short (~100 milliseconds) timescale with their REM sleep counterparts. However, the dynamics of mesopontine cholinergic neurons are distinct at a longer (~10 seconds) timescale: although P-waves are accompanied by cholinergic transients, the cholinergic tone gradually reduces before P-wave genesis during NREM sleep. While P-waves are coupled to hippocampal theta rhythms during REM sleep, P-waves during NREM sleep are accompanied by a rapid reduction in hippocampal ripple power. SWRs coupled with P-waves are short-lived and hippocampal neural firing is also reduced after P-waves. These results demonstrate that P-waves are part of coordinated sleep-related activity by functionally coupling with hippocampal ensembles in a state-dependent manner.

Discurso feminista e identidad americana en la danza moderna: Martha Graham y el significado social del cuerpo femenino

. Este artículo reflexiona acerca de los conceptos del discurso feminista y de la identidad americana en el contexto de la significación social del cuerpo danzante tal y como está representado en las coreografías de la bailarina americana Martha Graham. Aquí abordamos el impacto de las obras revolucionarias Heretic (1929) Lamentation (1930), Primitive Mysteries (1931), Frontier (1935), Letter to the World (1940) y Appalachian Spring (1944), explorando su significado social con referencia a la demarcación de la masculinidad y de la feminidad en la visión de danza de Graham. La iconografía visual, las partituras extraordinarias y la atmósfera sensorial creada por y para estas coreografías seminales son experiencias únicas de una danza artística específica que construye el discurso feminista. La contribución de Martha Graham a la formación de la danza moderna y sus característicos movimientos de ‘contract and release’ que forman la Graham Technique, en la que la energía se localiza en el centro del cuerpo, está saturada de emoción humana. El discurso feminista incorporado en estas coreografías habla del amor y de la muerte, de la opresión y de la libertad, de las limitaciones del género y de la lucha por identidad. Su contribución iluminadora a la danza contemporánea se basó en sus frases de movimiento corporal únicas y en su cuestionamiento sin concesiones de los cuerpos construidos socialmente. Martha Graham creó un nuevo vocabulario de movimiento que revolucionó la danza y se configuró debido al ‘cultural embodiment, cultural communication and the whole shift in the Western lifeworld at the beginning of the twentieth century’ . Palabras clave. Martha Graham, Graham Technique, danza moderna, significado social, discurso feminista, cuerpo femenino, grupos sociales, identidad americana, paisaje musical, cuerpo danzante femenino.

Fine-scale cultural variation reinforces genetic structure in England.

Genes and languages both contain signatures of human evolution, population movement, and demographic history. Cultural traits like language are transmitted by interactions between people, and these traits influence how people interact. In particular, if groups of people differentiate each other based on some qualities of their cultures, and if these qualities are passed to the next generation, then this differentiation can result in barriers to gene flow. Previous work finds such barriers to gene flow between groups that speak different languages, and we explore this phenomenon further: can more subtle cultural differences also produce genetic structure in a population? We focus on whether subtle, dialect-level linguistic differences in England have influenced genetic population structure, likely by affecting mating preferences. We analyze spatially dense linguistic and genetic data-both of which independently contain spatially structured variation in England-to examine whether the cultural differences represented by variation in English phonology colocalize with higher genetic rates of change. We find that genetic variation and dialect markers have similar spatial distributions on a country-wide scale, and that throughout England, linguistic boundaries colocalize with the boundaries of genetic clusters found using fineSTRUCTURE. This gene-language covariation, in the absence of geographic barriers that could coordinate cultural and genetic differentiation, suggests that similar social forces influenced both dialect boundaries and the genetic population structure of England.

P28: Analysis of Surface Electromyography (sEMG) Signals for Motion Signatures in Strength Training Exercises via Stretchable Wearable Electronic Sensors

Background: The characterization of commonly used strength training exercises has a range of implications for analysis of techniques displaying proper form and injury prevention in both sports and clinical rehabilitation settings. This study examines the ability of wearable sensors to effectively determine the degree of activation of different muscle groups using surface electromyography (sEMG) signals. The interpretation of these signals across muscle groups within an exercise allow for the characterization of their motion signatures. Wearable sensors with embedded electrodes (BioStamps RC, MC10 Inc.) were applied to two defined muscle groups for three exercises: a triceps push-up (PU), a biceps curl (BC) and an unweighted squat (US). Methods: Seven healthy volunteers performed three consecutive exercises in the following order; PU, BC, and US. Each exercise was performed for five repetitions with BioStamps applied to the distal and proximal ends of the subjects’ dominant side using adhesive bandages. For each of the defined exercises the investigator played a timed voice recording in which the subjects were instructed to perform the series of repetitions with consistent timing. Sensors automatically upload de-identified data to a tablet device during use. The following parameters are reported from the stamp: electromyographic data (of the muscle causing abduction and adduction) and acceleration (of the distal and proximal ends of the limb which is being abducted/adducted). The data was uploaded to Python and analyzed using a rolling average. P-values were then determined using a one-tailed t-test. Results: Each of the three strength exercises had two identifiable motion signatures, one from each muscle group, derived from the sEMG data which shows the peak muscle activation during the 5 repetitions of an exercise (Figure 1, E). Placement on the BioStamps on the TB and BB recorded activation in the PU and BC (Figure 1, A & B). There is a difference between the TB and BB activation in the PU (p=0.358) but no difference was found between their activation in the BC (p=0.06). This finding was limited by the small sample size (n=7), which would be improved in a future study. Placement of the BioStamps on the BF and RF was used in the unweighted squat (Figure 1, C & D). There is a difference in the RF and BF activation in the US (p=0.179). Discussion: By nature of the antagonistic motion of the triceps brachii (TB) and biceps brachii (BB) in a push-up, activation levels measured by sEMG recordings are expected to be similar. The TB acts as one of the primary movers, while the BB acts as an antagonist and stabilizes the movement to allow for a controlled push-up. Similarly, in a squat similar levels of activation were expected in the rectus femoris (RF) and the biceps femoris (BF) as the RF functions as a primary mover and the BF as a stabilizer. Activation of both the primary mover and stabilizing muscles is important for proper form and function.Figure 1. A & B. Placement of BioStamps on the triceps brachii and biceps brachii, muscles used in the biceps curl (p=0.06) and triceps push-up (p=0.358). C & D. Placement of BioStamps on the rectus femoris and the biceps femoris, muscles used in the unweighted squat (p=0.179). E. Unweighted squat sEMG graph showing muscle activation (mV) of rectus femoris over time (s).

P30: Remote and In-Clinic Teletracking and Analysis for Enhanced Rheumatologic Examination

Purpose: Rheumatoid arthritis and related arthritides associated with chronic joint inflammation of the hands significantly affects range of motion and daily living functionality due to stiffness, pain, and swelling. It is vital to closely monitor changes in joint flexibility across the progression of this disease state to assess treatment efficacy and provide informed quantitative analysis. Our group previously developed and reported on a video-based motion analysis system with a wide range of utility. Using this system, we evaluated the range of motion of radiocarpal and phalangeal joints in arthritic versus normal subjects. We hypothesized that use of this system in clinic and at home would provide accurate and quantitative data on joint flexibility and also allow assessment of progression of flexibility of affected joints in patients experiencing joint inflammation across their treatment timelines. Methods: Healthy volunteers and those experiencing self-reported, clinically-diagnosed arthritis were instructed via a telehealth remote platform to place small brightly-colored visual markers (1cm2) on their hands. Using our video motion analysis system, video recordings were captured as subjects performed: 1) wrist flexion and extension, 2) finger flexion and extension, and 3) finger adduction and abduction. The digital recordings were imaged as a motion signature and the data was analyzed to obtain the angle (degrees) of rotation about the joints by correcting full extension/adduction to a “zero degrees” baseline and calculating the degrees of flexion/abduction at the peak point. This protocol allowed for versatility of analysis based on the treatment course providing novel access to patient monitoring outside of the clinic setting. Results: Range of motion of the radiocarpal and phalangeal joints measured in degrees was successfully recorded on both healthy (n=14, 9F 5M) and arthritic subjects (n=8, 4M 4F) in a virtual setting via the video motion analysis system. In all cases the system offered the resolution required to determine overall joint flexibility. A clear quantitative distinction was detected between arthritic patients versus health subjects. Conclusion: A video motion analysis system utilizing small markers can characterize, track, and compare joint flexibility in at-home settings for rheumatoid arthritis and related joint diseases. With face-to-face clinic time being an increasingly limited commodity, this system offers a valuable, digital tool to not only assess patients remotely but it adds a quantitative dimension previously absent in the Rheumatologic exam. As this project continues, arthritis subjects will be monitored over time to assess functionality of disease-state tracking across a treatment time course. Digital assessment of joint flexibility is a useful addition to the diagnostic armamentarium of the Rheumatologist, Orthopedist and related Health Care providers enhancing the precision of diagnosis and therapy.

P33: “Digital Dance”: Analyzing and Quantifying Signatures of a Demi Plié via Stretchable Electronic Wearable Sensors for Dance Movement Therapy

Background: Dance, an artistic movement, has utility in dance/movement therapy (DMT) when performed accurately and safely. Dance movements consist of exercises promoting muscle building, flexibility, and enhancing longevity as well as providing psychological benefits. Here we evaluated the foundational ballet exercise, the demi plié, and the associated movements of the knees and pelvis. We hypothesized that deviations in motion signatures are identifiable between dancers performing correct vs. incorrect demi pliés, as well as between collegiate level dancers and non-dancers. Methods: Motion sensors (BioStamps) were placed on the left tibialis anterior and sacrum of seven classically trained, injury-free, collegiate-level dancers, who then performed: 1) correct demi pliés, 2) incorrect demi pliés with anterior pelvic tilt, and 3) incorrect demi pliés with posterior pelvic tilt. Then, six non-dancers of similar age, performed correct demi pliés to the best of their ability after brief instruction. For all conditions, acceleration and gyroscope data was collected (X, Y, and Z axes). Results: The dancers movement of the sacrum differed between Conditions 1 and 2 (p=0.00018) and Conditions 1 and 3 (p=0.00178). No significant difference in movement of the sacrum was found between Condition 1 in the dancer group and the non-dancer group (p=0.30952). In addition, no statistically significant difference was found between the depth of plié in the dancers between Conditions 1 and 2 (p=0.50162) and Conditions 1 and 3 (p=0.84254) and in the non-dancer group compared to Condition 1 in the dancers (p=0.26011). No consistent patterns were found regarding medial and lateral motion of the tibialis anterior in both the dancer and non-dancer groups. Conclusions: The BioStamps technology accurately tracked the movements of the tibialis anterior and sacrum during correct and incorrect classical demi pliés in both the “Dancer” and “Non-dancer” groups. This knowledge when applied could promote correct ballet technique and be used in injury prevention, as well as for dance/movement therapy (DMT).

The persistence of the critically endangered Asiatic cheetah relies upon urgent connectivity protection: a landscape genetics perspective

Decreasing genetic diversity, gene flow rates and population connectivity can increase inbreeding rates and extinction risks. Asiatic cheetah is a critically endangered mammal with large home range that suffered from extreme range reduction and population decline. Their population is now fragmented into two subpopulations. We used genetic markers to estimate genetic diversity, relatedness, minimum effective population size and gene flow, and to assess population structure. Putative corridors connecting subpopulations were inferred using connectivity models based on topography, land cover and human footprints resistance variables. Individual pairwise genetic relatedness was compared with resistance values obtained from these models and with Euclidean distances between samples to assess the most important factors shaping the current genetic structure. The estimated effective population size was extremely low (Ne = 11 to 17). Both Northern and Southern Subpopulations exhibited low genetic diversity and high relatedness. Several signatures of gene flow and movement of individuals between subpopulations were observed suggesting that inferred corridors potentially connecting subpopulations are functional. However, no traces of gene flow were observed for the latest generations, maybe due to a decrease of functional connectivity in recent years. The resistance model including all variables was best related to genetic relatedness, whereas population differentiation is mostly driven by isolation by distance. The very low estimated effective population size, decreased genetic diversity, and high relatedness of Asiatic cheetah suggests that population reinforcement, removing obstacles to connectivity and boosting prey population conservation in stepping stones are urgently needed to prevent the imminent extinction of iconic biodiversity.