Movements Of Abdomen Research Articles

Shape-Configurable Mesh for Hernia Repair by Synchronizing Anisotropic Body Motion.

Continuous progress has been made in elucidating the relationship between material property, device design, and body function to develop surgical meshes. However, an unmet need still exists wherein the surgical mesh can handle the body motion and thereby promote the repair process. Here, the hernia mesh design and the advanced polymer properties are tailored to synchronize with the anisotropic abdominal motion through shape configuration. The thermomechanical property of shape configurable polymer enables molding of mesh shape to fit onto the abdominal structure upon temperature shift, followed by shape fixing with the release of the heat energy. The microstructural design of mesh is produced through finite element modeling to handle the abdominal motion efficiently through the anisotropic longitudinal and transverse directions. The design effects are validated through in vitro, ex vivo, and in vivo mechanical analyses using a self-configurable, body motion responsive (BMR) mesh. The regenerative function of BMR mesh leads to effective repair in a rat hernioplasty model by effectively handling the anisotropic abdomen motion. Subsequently, the device-tissue integration is promoted by promoting healthy collagen synthesis with fibroblast-to-myofibroblast differentiation. This study suggests a potential solution to promote hernia repair by fine-tuning the relationship between material property and mesh design.

Detection of Respiratory Events during Sleep Based on Fusion Analysis and Entropy Features of Cardiopulmonary Signals.

Sleep apnea hypopnea syndrome (SAHS) is a common sleep disorder with a high prevalence. The apnea hypopnea index (AHI) is an important indicator used to diagnose the severity of SAHS disorders. The calculation of the AHI is based on the accurate identification of various types of sleep respiratory events. In this paper, we proposed an automatic detection algorithm for respiratory events during sleep. In addition to the accurate recognition of normal breathing, hypopnea and apnea events using heart rate variability (HRV), entropy and other manual features, we also presented a fusion of ribcage and abdomen movement data combined with the long short-term memory (LSTM) framework to achieve the distinction between obstructive and central apnea events. While only using electrocardiogram (ECG) features, the accuracy, precision, sensitivity, and F1 score of the XGBoost model are 0.877, 0.877, 0.876, and 0.876, respectively, demonstrating that it performs better than other models. Moreover, the accuracy, sensitivity, and F1 score of the LSTM model for detecting obstructive and central apnea events were 0.866, 0.867, and 0.866, respectively. The research results of this paper can be used for the automatic recognition of sleep respiratory events as well as AHI calculation of polysomnography (PSG), which provide a theoretical basis and algorithm references for out-of-hospital sleep monitoring.

A Potential Pitfall and Clinical Solutions in Surface-Guided Deep Inspiration Breath Hold Radiation Therapy for Left-Sided Breast Cancer

Deep inspiration breath hold (DIBH) is an effective technique to spare the heart in treating left-sided breast cancer. Surface-guided radiation therapy (SGRT) is increasingly applied in DIBH setup and motion monitoring. Patient-specific breathing behavior, either thoracically driven or abdominally driven (A-DIBH), should be unaltered, online identified, and monitored accordingly to ensure reproducible heart-sparing treatment. Sixty patients with left-sided breast cancer treated with SGRT were analyzed: 20 A-DIBH patients with vertical chest elevation (VCE ≤ 5 mm) were prospectively identified, and 40 control patients were retrospectively and randomly selected for comparison. At simulation, both free-breathing (FB) and DIBH computed tomography (CT) were acquired, guided by a motion surrogate placed around the xiphoid process. For SGRT treatment setups, the region of interest (ROI) was defined on the CT chest surface, and the surrogate-based setup was a backup. For all 60 patients, the VCE was measured as the average of the FB-to-DIBH elevations at the breast and xiphoid process, together with abdominal elevation. In the 40-patient control group, A-DIBH patients (VCE ≤ 5 mm) were identified. Of the 20 A-DIBH patients, 10 were treated with volumetric modulated arc therapy plans, and 10 patients were treated with tangent plans. Clinical DIBH plans were recalculated on FB CT to compare maximum dose (DMax), 5% of the maximum dose (D5%), mean dose (DMean), and V30Gy, V20Gy, and V5Gy of the heart and lungs and their significance. In the 20 A-DIBH patients, VCE=3 ± 2 mm, surrogate motion (9 ± 6 mm), and abdomen motion of 14 ± 5 mm are found. Heart dose reduction from FB to DIBH is significant (P < .01): ∆DMax=-8.4 ± 9.8 Gy, ∆D5%=-2.4 ± 4.4 Gy, and ∆DMean=-0.6 ± 0.9 Gy. Six out of 40 control patients (15%) are found to have VCE ≤ 5 mm. A-DIBH (VCE ≤ 5 mm) patient population is significant (15%), and they should be identified in the SGRT workflow and monitored accordingly. A new abdominal ROI or an abdominal surrogate should be used instead of the conventional chest-only ROI. Patient-specific DIBH should be preserved for higher reproducibility to ensure heart sparing.

Detection of differences of cardiorespiratory metrics between non-invasive respiratory support modes using machine learning methods

Many preterm infants require invasive mechanical ventilation in the first days of life. Once ventilation is removed, non-invasive respiratory support assists the transition to spontaneous breathing. Three common support modes are Nasal Continuous Positive Airway Pressure (CPAP), Non-Invasive Neurally Adjusted Ventilatory Assist (NIV-NAVA), and Nasal Intermittent Positive Pressure Ventilation (NIPPV). Cardiorespiratory behavior under these supports is not well understood. We hypothesized that if behavior changed with the support, then machine learning should be able to distinguish them, and the most discriminatory features would indicate how the behaviors differ. To test this, we recorded cardiorespiratory signals from infants during CPAP, NIV-NAVA, and NIPPV immediately following extubation. Forty-five metrics related to the amplitude and frequency of these signals were computed at each time and six summary statistics computed for each metric. The feature set was reduced by principal component analysis and used to train a Random Forest classifier. We found that (1) Classification of the three modes performed poorly (accuracy = 58.6%); (2) Classification of CPAP from NIV-NAVA or NIPPV performed well (accuracy = 81.5%). Thus, cardiorespiratory behavior during CPAP is significantly different from NIV-NAVA or NIPPV. The features with the greatest discriminatory power were related to the amplitude of respiratory movements and the correlation between the ribcage and abdomen movements. These results serve to direct further investigation with clinical relevance. Thus, infants with shallow breathing may benefit from the support with largest amplitude respiratory movements, while infants with asynchronous chest and abdominal movements may benefit from the modality with the most correlated movements.

Hardware in the loop simulation and implementation of a dragonfly-like MAV using clap and fling mechanism

The main aim of this paper is to model and simulate flight dynamics and to design a controller for a dragonfly-like micro aerial vehicle (MAV). This MAV has flapping wings using a clap and fling mechanism with a rigid abdomen. Kane’s method is applied to derive the longitudinal motion equations of the MAV as a multi-body system. Then, the aerodynamic lift and drag forces of the MAV are obtained. These equations are substituted in the derived motion equations. Furthermore, a new structure for a dragonfly-like flapping wing MAV is presented in which abdomen motion is considered in the longitudinal mode. In this work, the use of the abdomen is also formulated. A change in the motor’s speed generates differential thrust that creates a pitch moment as a control input. State space linearized equations of motion are presented by using appropriate assumptions in the aerodynamics, and dynamic nonlinear equations. To validate the linearized model, the response of the open-loop linear system is compared with the nonlinear one. In addition, the positive role of the abdomen in the open loop is discussed and analyzed. Finally, an LQR controller is designed for the pitch mode which is robust against disturbances. The validity, effectiveness, and performance of the derived equations and designed autopilot are shown by implemented hardware in the loop testbed using a fixed abdomen. Results demonstrate a good agreement between theoretical and experimental responses with accurate hovering at the desired angle.

Abdominal Movements in Insect Flight Reshape the Role of Non-Aerodynamic Structures for Flight Maneuverability I: Model Predictive Control for Flower Tracking.

SynopsisResearch on insect flight control has focused primarily on the role of wings. Yet abdominal deflections during flight can potentially influence the dynamics of flight. This paper assesses the role of airframe deformations in flight, and asks to what extent the abdomen contributes to flight maneuverability. To address this, we use a combination of both a Model Predictive Control (MPC)-inspired computational inertial dynamics model, and free flight experiments in the hawkmoth, Manduca sexta. We explored both underactuated (i.e., number of outputs are greater than the number of inputs) and fully actuated (equal number of outputs and inputs) systems. Using metrics such as the non-dimensionalized tracking error and cost of transport to evaluate flight performance of the inertial dynamics model, we show that fully actuated simulations minimized the tracking error and cost of transport. Additionally, we tested the effect of restricted abdomen movement on free flight in live hawkmoths by fixing a carbon fiber rod over the thoracic-abdomen joint. Moths with a restricted abdomen performed worse than sham treatment moths. This study finds that abdominal motions contribute to flight control and maneuverability. Such motions of non-aerodynamic structures, found in all flying taxa, can inform the development of multi-actuated micro air vehicles.

The influence of receiving real-time visual feedback on breathing during treadmill running to exhaustion.

Breathing plays a vital role in everyday life, and specifically during exercise it provides working muscles with the oxygen necessary for optimal performance. Respiratory inductance plethysmography (RIP) monitors breathing through elastic belts around the chest and abdomen, with efficient breathing defined by synchronous chest and abdomen movement. This study examined if providing runners with visual feedback through RIP could increase breathing efficiency and thereby time to exhaustion. Thirteen recreational runners (8F, 5M) ran to exhaustion on an inclined treadmill on two days, with visual feedback provided on one randomly chosen day. Phase angle was calculated as a measure of thoraco-abdominal coordination. Time to exhaustion was not significantly increased when visual feedback was provided (p = 1). Phase angle was not significantly predicted by visual feedback (p = 0.667). Six participants improved phase angle when visual feedback was provided, four of whom increased time to exhaustion. Four participants improved phase angle by 9° or more, three of whom increased time to exhaustion. Participants who improved phase angle with visual feedback highlight that improving phase angle could increase time to exhaustion. Greater familiarization with breathing techniques and visual feedback and a different paradigm to induce running fatigue are needed to support future studies of breathing in runners.

Contactless Simultaneous Breathing and Heart Rate Detections in Physical Activity Using IR-UWB Radars.

Vital signs monitoring in physical activity (PA) is of great significance in daily healthcare. Impulse Radio Ultra-WideBand (IR-UWB) radar provides a contactless vital signs detection approach with advantages in range resolution and penetration. Several researches have verified the feasibility of IR-UWB radar monitoring when the target keeps still. However, various body movements are induced by PA, which lead to severe signal distortion and interfere vital signs extraction. To address this challenge, a novel joint chest–abdomen cardiopulmonary signal estimation approach is proposed to detect breath and heartbeat simultaneously using IR-UWB radars. The movements of target chest and abdomen are detected by two IR-UWB radars, respectively. Considering the signal overlapping of vital signs and body motion artifacts, Empirical Wavelet Transform (EWT) is applied on received radar signals to remove clutter and mitigate movement interference. Moreover, improved EWT with frequency segmentation refinement is applied on each radar to decompose vital signals of target chest and abdomen to vital sign-related sub-signals, respectively. After that, based on the thoracoabdominal movement correlation, cross-correlation functions are calculated among chest and abdomen sub-signals to estimate breath and heartbeat. The experiments are conducted under three kinds of PA situations and two general body movements, the results of which indicate the effectiveness and superiority of the proposed approach.

An efficient two-step multi-organ registration on abdominal CT via deep-learning based segmentation

Registration of three dimensional (3D) abdominal computed tomography (CT) scans is essential for computer-aided disease diagnosis and treatment, but the non-rigid respiratory movements of abdomen increase its difficulty. An automatic two-step multi-organ registration method is presented in this paper for abdominal CT scans. First, the lightweight squeeze-and-excitation (SE) attention blocks and the fully connected conditional random field (CRF)-based post-processing are integrated into a fully convolutional networks (FCN) based model, which can achieve more accurate segmentation results for abdominal multiple organs such as liver, kidneys, and spleen. Then, a non-rigid local correlation coefficient (LCC) similarity metric and an isotropic total variation regularization are combined to register the multi-organ regions, which can reduce computation time and avoid the over-smooth problem of deformation field. The proposed method is validated on three public abdominal CT databases, and the experimental results show that the segmentation and registration performances of our method outperform those of some competing methods. Moreover, compared with global registration strategy, the average registration time of the proposed method is shortened by 20.45%, and the average MSE, PSNR, SSIM, and DICE values are also improved by 7.21%, 22.37%, 15.80%, and 14.43%, respectively.

Possible self-assembly in linyphiid sheet webs

Most lines in the sheets of four linyphiid species bore numerous small droplets. Droplet-bearing lines of Linyphia simplicata (F. O. Pickard-Cambridge, 1902) and Neriene coosa (Gertsch, 1951) adhered weakly to smooth, dry surfaces, contradicting previous statements that such lines in linyphiid webs are not sticky. Droplets at the intersections of lines tended to be larger than nearby droplets on the same lines, and were more widely separated from adjacent droplets than were other, nearby droplets on the same lines. A self-assembly hypothesis to explain these findings, that larger droplets accumulated at intersections as a result of lines in the sheet scraping against each other, was supported by confirming that larger intersection droplets were more widely separated from adjacent droplets than were smaller intersection droplets. These observations suggest a new, dynamic view of linyphiid sheet webs, in which the distribution of sticky material is adjusted advantageously immediately after lines are produced, due to the upward dabbing movements of the spider's abdomen that press the sheet lines against each other during sheet construction, and perhaps also to other movements of newly laid lines against each other. Larger droplets maybe advantageous in binding lines together, and in adhering to prey.

Effects of abdomen undulation in energy consumption and stability for monarch butterfly

The flight of monarch butterflies is characterized by a relatively large wing, flapping at a relatively low frequency coupled with abdomen undulation. This paper presents the dynamics of a flapping wing flyer that can be applied to the coupled motion of the wing, body, and abdomen at the monarch butterfly scale, which is formulated directly on the configuration manifold. The resulting thorax and abdomen motion as well as the resultant forces are consistent with the flight of a live monarch butterfly. Based on these, beneficial effects of the abdomen undulation in the flight of monarch butterflies are illustrated. For both hover and forward-climbing trajectories, the abdomen undulation results in a reduction of the energy and power consumption. Furthermore, the Floquet stability analysis shows that the periodic orbits associated with both flight modes are stable. In particular, the abdomen undulation improves the stability. Compared to the dynamics of hawkmoth, bumblebee, and fruitfly models, the monarch possesses superior stability properties.

The Toxicity of Essential Oils From Three Origanum Species Against Head Louse, Pediculus humanus capitis.

Pediculosis caused by human head louse, Pediculus humanus capitis De Geer (Anoplura: Pediculidae) is a public health problem with a high prevalence, especially among children in school age. Different chemical pediculicides (insecticides) are used against lice but the repeated application of these pediculicides for the treatment of P. humanus capitis infestation in the past decades has resulted in the development of resistance. The plant essential oils have been used as alternative sources of lice treatment agents. Pediculicidal activity of the essential oils of three Origanum species (O. onites, O. majorana and O. minutiflorum) against P. humanus capitis adults was examined in this study. Essential oils from aerial parts of three Origanum species were obtained by hydrodistillation using a Clevenger-type apparatus. P. humanus capitis specimens used were obtained from infested children by combing method at primary schools. Adult lice were exposed to three dilutions (1%, 0.5% and 0.1% w/v) of tested oils for 5min using the adult immersion test. According to the results, all Origanum essential oils at 1% concentration have been shown to significantly decrease the rate of limb, bowel and abdomen movements, producing more than 90% mortality after 12h. Our results indicated that Origanum essential oils can be used for the development of new pediculicides against head louse.

A novel noninvasive approach for evaluating work of breathing indices in a developmental rat model using respiratory inductance plethysmography

Pulmonary function testing (PFT) is an important component for evaluating the outcome of experimental rodent models of respiratory diseases. Respiratory inductance plethysmography (RIP) provides a noninvasive method of PFT requiring minimal cooperation. RIP measures work of breathing (WOB) indices including phase angle (Ф), percent rib cage (RC %), breaths per minute (BPM), and labored breathing index (LBI) on an iPad. The aim of this study was to evaluate the utility of a recently developed research instrument, pneuRIP, for evaluation of WOB indices in a developmental rat model. Sprague Dawley rats (2 months old) were commercially acquired and anaesthetised with isoflurane. The pneuRIP system uses two elastic bands: one band (RC) placed around the rib cage under the upper armpit and another band (AB) around the abdomen. The typical thoracoabdominal motion (TAM) plot showed the abdomen and rib cage motion in synchrony. The plots of phase angle and LBI as a function of data point number showed that values were within the range. The distribution for phase angle and LBI was within a narrow range. pneuRIP testing provided instantaneous PFT results. This study demonstrated the utility of RIP as a rapid, noninvasive approach for evaluating treatment interventions in the rodent model.

Classification and Detection of Breathing Patterns with Wearable Sensors and Deep Learning.

Rapid assessment of breathing patterns is important for several emergency medical situations. In this research, we developed a non-invasive breathing analysis system that automatically detects different types of breathing patterns of clinical significance. Accelerometer and gyroscopic data were collected from light-weight wireless sensors placed on the chest and abdomen of 100 normal volunteers who simulated various breathing events (central sleep apnea, coughing, obstructive sleep apnea, sighing, and yawning). We then constructed synthetic datasets by injecting annotated examples of the various patterns into segments of normal breathing. A one-dimensional convolutional neural network was implemented to detect the location of each event in each synthetic dataset and to classify it as belonging to one of the above event types. We achieved a mean F1 score of 92% for normal breathing, 87% for central sleep apnea, 72% for coughing, 51% for obstructive sleep apnea, 57% for sighing, and 63% for yawning. These results demonstrate that using deep learning to analyze chest and abdomen movement data from wearable sensors provides an unobtrusive means of monitoring the breathing pattern. This could have application in a number of critical medical situations such as detecting apneas during sleep at home and monitoring breathing events in mechanically ventilated patients in the intensive care unit.

Fiber-Optic Based Smart Textiles for Real-Time Monitoring of Breathing Rate.

Wearable light textiles are gaining widespread interest in application for measurement and monitoring of biophysical parameters. Fiber optic sensors, in particular Bragg Grating (FBG) sensors, can be a competitive method for monitoring of respiratory behavior for chest and abdomen regions since the sensors are able to convert physical movement into wavelength shift. This study aims to show the performance of elastic belts with integrated optical fibers during the breathing activities done by two volunteers. Additionally, the work aims to determine how the positions of the volunteers affect the breathing pattern detected by optical fibers. As a reference, commercial mobile application for sensing vibration is used. The obtained results show that the FBGs are able to detect chest and abdomen movements during breathing and consequently reconstruct the breathing pattern. The accuracy of the results varies for two volunteers but remains consistent.

In vivo performance of intraperitoneal onlay mesh after ventral hernia repair

BackgroundVentral hernia repair needs to be improved since recurrence, postoperative pain and other complications are still reported in many patients. The behavior of implants in vivo is not sufficiently understood to design a surgical mesh mechanically compatible with the human abdominal wall. MethodsThis analysis was based on radiological pictures of patients who underwent laparoscopic ventral hernia repair. The pictures show the trunk of the patient at rest in a standing position and under side bending. The change in the distance between different tacks due to trunk movement was analyzed, which allowed us to determine the in vivo elongation of the mesh incorporated into the abdominal wall. FindingsThe relative elongations of the surgical mesh varied from a few percent to greater than 100% in two cases. The median of the median relative elongations obtained for all patients is 9.5%, and the median of the maximum relative elongations for all patients is 32.6%. The maximum elongation occurs between tacks that are next to each other. Trunk movement causes implant deformation, and this study provides quantitative information regarding changes in the distance between fasteners. InterpretationThe physiological movement of the human abdomen must be regarded as a very important factor in mesh deformation and should be considered in surgical practice to reduce the hernia recurrence rate and postoperative pain.

A Wearable RF Sensor for Monitoring Respiratory Patterns.

We present a non-invasive approach for continuous monitoring of respiration dynamics using a wearable radio-frequency (RF) sensor based on near-field coherent sensing. A continuous-wave RF signal at 1.8 GHz is generated by a software-defined radio, with both transmitter (Tx) and receiver (Rx) antennas placed close to the xiphoid process. The experimental prototype of the mobile sensor can modulate the internal organ motion in the near-field region of the Tx antenna and is then received by the nearby Rx antenna to be demodulated and sampled. Through peak detection, we have identified inhalation and exhalation peaks of each breath cycle to estimate the breath rate and the lung volume. The extracted respiratory parameters are compared with the conventional chest belts data for various simulated respiratory conditions including voluntary deep, fast-shallow and slow-shallow breathing. We also characterized simulated central sleep apneas, Cheyne-Stokes, Biot's, ataxic and coughing conditions. To accurately identify obstructive apnea, we presented a two-sensor approach that can capture paradoxical movement of thorax and abdomen. The on-line recognition of these respiratory patterns can be employed not only to continuously monitor patients with chronic respiratory disorders but also to provide real-time feedback for future therapeutic purposes.

Dynamic 3D Reconstruction of Thoracic Cage and Abdomen in Children and Adolescents With Scoliosis: Preliminary Results of Optical Reflective Motion Analysis Assessment.

In patients with untreated scoliosis or in those with posterior spinal instrumented fusion (PSF), the movements of neither the thoracic cage (ThC) nor the abdomen (ABD) during quiet and deep breathing have been well defined in the literature. The purpose of this study was to evaluate kinematic variations in the ThC and ABD during quiet and deep breathing by optical reflective motion analysis (ORMA) in children with scoliosis. The study included 6 healthy children (group A), 7 subjects with untreated scoliosis over 50 degrees (group B), and 8 patients with scoliosis treated by PSF (group C). After anthropometric measurements (standing height, sitting height, arm span, chest perimeter, body weight, body mass index, T1-T12, and L1-L5 length) were obtained, the movements of subjects during quiet and deep breathing were measured with a 10-camera 3-dimensional ORMA system (82 markers) with the subjects in a standard standing position. No significant differences were observed in sex, age, weight, height, or arm span (P>0.05). Significant differences were observed in the chest perimeter, Cobb angle, and body mass index (P<0.05). ThC and ABD movements during quiet and deep breathing decreased significantly in group B and C when compared with group A (P<0.05). Group B showed decreased expansion of the ThC (-52.4% to -58.3%) and relatively increased motion of the ABD compared with groups A and C (P<0.001). However, ABD expansion remained lower in group B than in groups A and C (-32.8% and -5.7%). PSF does not completely eliminate transverse plane kinematics, although a greater reduction was observed at instrumented than noninstrumented levels (-60.8% vs. -35.1%; P<0.05). ORMA is a useful tool for assessing alterations in the kinematics of the ThC and ABD caused by severe scoliosis and/or PSF. Compared with normal subjects, patients with severe scoliosis had poorer and less effective kinematics of the ThC and ABD. In contrast, operated subjects had better and more effective kinematics of the ThC and ABD, breathing curves, thoracic expansion, and abdominal movements closer to normal compared with patients with severe, untreated deformity. Level III.

Breath Rate Variability: A Novel Measure to Study the Meditation Effects.

Context:Reliable quantitative measure of meditation is still elusive. Although electroencephalogram (EEG) and heart rate variability (HRV) are known as quantitative measures of meditation, effects of meditation on EEG and HRV may well take long time as these measures are involuntarily controlled. Effect of mediation on respiration is well known; however, quantitative measures of respiration during meditation have not been studied.Aims:Breath rate variability (BRV) as an alternate measure of meditation even over a short duration is proposed. The main objective of this study is to test the hypothesis that BRV is a simple measure that differentiates between meditators and nonmeditators.Settings and Design:This was a nonrandomized, controlled trial. Volunteers meditate in their natural habitat during signal acquisition.Subjects and Methods:We used Photo-Plythysmo-Gram (PPG) signal acquisition system from BIO-PAC and recorded video of chest and abdomen movement due to respiration during a short meditation (15 min) session for 12 individuals (all males) meditating in a relaxed sitting posture. Seven of the 12 individuals had substantial experience in meditation, while others are controls without any experience in meditation. Respiratory signal from PPG signal was derived and matched with that of the video respiratory signal. This derived respiratory signal is used for calculating BRV parameters in time, frequency, nonlinear, and time-frequency domain.Statistical Analysis Used:First, breath-to-breath interval (BBI) was calculated from the respiration signal, then time domain parameters such as standard deviation of BBI (SDBB), root mean square value of SDBB (RMSSD), and standard deviation of SDBB (SDSD) were calculated. We performed spectral analysis to calculate frequency domain parameters (power spectral density [PSD], power of each band, peak frequency of each band, and normalized frequency) using Burg, Welch, and Lomb–Scargle (LS) method. We calculated nonlinear parameters (sample entropy, approximate entropy, Poincare plot, and Renyi entropy). We calculated time frequency parameters (global PSD, low frequency-high frequency [LF-HF] ratio, and LF-HF power) by Burg LS and wavelet method.Results:The results show that the mediated individuals have high value of SDSD (+24%), SDBB (+29%), and RMSSD (+26%). Frequency domain analysis shows substantial increment in LFHF power (+73%) and LFHF ratio (+33%). Nonlinear parameters such as SD1 and SD2 were also more (>20%) for meditated persons.Conclusions:As compared to HRV, BRV can provide short-term effect on anatomic nervous system meditation, while HRV shows long-term effects. Improved autonomic function is one of the long-term effects of meditation in which an increase in parasympathetic activity and decrease in sympathetic dominance are observed. In future works, BRV could also be used for measuring stress.

Use of high-speed video recording to detect wing beating produced by honey bees

Honey bees use many signals to communicate and coordinate different activities in a colony. In this study, wing and abdomen movements occurring during social interactions between bees were recorded using a high-speed camera. Wing beating was observed in queens, workers and drones. Some of the observed behaviors were reported earlier, but many of them were described here for the first time including drones moving their wings while leaving the nest for mating flights, workers trying to evict them from the nest or in a colony with drone-laying queen, and workers vibrating their wings in contact with a queen outside of the process of swarming, in turns with a shaking signal or while evicting drones from the nest. Queens moved their wings with significantly higher frequency, performing longer pulses of wing beats than drones and workers. Drones vibrated their wings with the frequency similar to workers, but they performed significantly shorter pulses of wing beating. In workers, the frequency of wing beats and the duration of wing-beating pulses were significantly different among various behaviors. Wing beating was performed by bees relatively often in many social contexts and it differed in frequency and pulse duration, which indicates that wing beating may be used for transferring information. High-speed video recording revealed a wide range of new behaviors which may play an important role in honey bee communication. Therefore, it may be used as an alternative or addition to recordings made with microphones and laser vibrometers.