Search

Blood pressure (BP) monitoring is vital in daily healthcare, especially for cardiovascular diseases. However, BP values are mainly acquired through a contact-sensing method, which is inconvenient and unfriendly for BP monitoring. This paper proposes an efficient end-to-end network for estimating BP values from a facial video to achieve remote BP estimation in daily life. The network first derives a spatiotemporal map of a facial video. Then, it regresses the BP ranges with a designed blood pressure classifier and simultaneously calculates the specific value with a blood pressure calculator in each BP range based on the spatiotemporal map. In addition, an innovative oversampling training strategy was developed to handle the problem of unbalanced data distribution. Finally, we trained the proposed blood pressure estimation network on a private dataset, MPM-BP, and tested it on a popular public dataset, MMSE-HR. As a result, the proposed network achieved a mean absolute error (MAE) and root mean square error (RMSE) of 12.35 mmHg and 16.55 mmHg on systolic BP estimations, and those for diastolic BP were 9.54 mmHg and 12.22 mmHg, which were better than the values obtained in recent works. It can be concluded that the proposed method has excellent potential for camera-based BP monitoring in the indoor scenarios in the real world. [ABSTRACT FROM AUTHOR]

Behaviour recognition technology is an interdisciplinary technology, integrating many research achievements in computer vision, deep learning, pattern recognition and other fields. The key information of bone data on human behavior can not only accurately describe the motion posture of the human body in three-dimensional space, but also its rigid connection structure is robust to various external interference factors. However, the behavioral recognition algorithm is influenced by different factors such as background, light and environment, which is easy to lead to unstable recognition accuracy and limited application scenarios. To address this problem, in this paper, we propose a noise filtering algorithm based on data correlation and skeleton energy model filtering, construct a set of football player data sets, using the ST-GCN algorithm to train the skeleton characteristics of football players, and construct a behavior recognition system applied to football players. Finally, by comparing the accuracy of Deep LSTM, 2s-AGCN and the algorithm in this paper, the accuracy of TOP1 and TOP5 is 39.97% and 66.34%, respectively, which are significantly higher than the other two algorithms. It can realize the statistics of athletes and analyze the technical and tactical movements of players on the football field. [ABSTRACT FROM AUTHOR]

Geographical information is gaining new momentum as an analysis and visualization tool for collections of cultural objects. It provides all kinds of users with new opportunities to contextualize and understand these objects in ways that resemble our ordinary spatially-located experience and to do so better than textual narratives. The SeMap project has built an online resource that shows more than 200,000 cultural objects through spatiotemporal maps, thus enabling new experiences and perspectives around these objects. Data come from the CER.ES repository and were created by a network of more than 100 Spanish museums. This article explains the refinement of the data provided by the repository, mostly by adding a semantic structure thanks to the CIDOC-CRM ontology, and by simplifying the exceedingly complex terminologies employed in the original records. Particular attention is paid to the methods for geolocating the information, as well as adding temporal filters (among others) to user queries. The functionalities, interface, and technical requirements are also explored at length. [ABSTRACT FROM AUTHOR]

Traffic incidents endanger the smooth running of vehicles. Congestion caused by traffic incidents has caused a waste of time and fuel and seriously affected transportation efficiency. At present, most methods use manual judgment or image features to detect traffic incidents, but these methods lack timeliness, leading to secondary incidents. For dangerous road sections such as ramp-free and long downhills, this paper proposes an algorithm to quickly detect traffic incidents based on a spatiotemporal map of vehicle trajectories. First, a vehicle dataset from the monitoring perspective is constructed, and an improved YOLOv4 detection algorithm is used to detect images organized as batches. Based on the detection result, the multi-object tracking method of vehicle speed prediction in key frames is used to obtain the vehicle trajectory. Then according to the vehicle trajectory obtained in a single scene, the vehicle trajectory is reidentified and associated in the continuous monitoring scene to construct a long-distance vehicle trajectory spatiotemporal map. Finally, according to the distribution and generation status of the trajectory in the spatiotemporal map, traffic incidents such as vehicle parking, vehicle speeding, and vehicle congestion are analyzed. Experimental results show that the proposed method greatly increases the speed of vehicle detection and tracking and obtains high mAP, MOTA, and MOTP indicators. The global spatiotemporal map constructed by trajectory reidentification can achieve high detection rates for traffic incidents, reduce the average elapsed time, and avoid the problems of the inaccuracy of analyzing image features. [ABSTRACT FROM AUTHOR]

Blood pressure (BP) monitoring is vital in daily healthcare, especially for cardiovascular diseases. However, BP values are mainly acquired through a contact-sensing method, which is inconvenient and unfriendly for BP monitoring. This paper proposes an efficient end-to-end network for estimating BP values from a facial video to achieve remote BP estimation in daily life. The network first derives a spatiotemporal map of a facial video. Then, it regresses the BP ranges with a designed blood pressure classifier and simultaneously calculates the specific value with a blood pressure calculator in each BP range based on the spatiotemporal map. In addition, an innovative oversampling training strategy was developed to handle the problem of unbalanced data distribution. Finally, we trained the proposed blood pressure estimation network on a private dataset, MPM-BP, and tested it on a popular public dataset, MMSE-HR. As a result, the proposed network achieved a mean absolute error (MAE) and root mean square error (RMSE) of 12.35 mmHg and 16.55 mmHg on systolic BP estimations, and those for diastolic BP were 9.54 mmHg and 12.22 mmHg, which were better than the values obtained in recent works. It can be concluded that the proposed method has excellent potential for camera-based BP monitoring in the indoor scenarios in the real world.

Geographical information is gaining new momentum as an analysis and visualization tool for collections of cultural objects. It provides all kinds of users with new opportunities to contextualize and understand these objects in ways that resemble our ordinary spatially-located experience and to do so better than textual narratives. The SeMap project has built an online resource that shows more than 200,000 cultural objects through spatiotemporal maps, thus enabling new experiences and perspectives around these objects. Data come from the CER.ES repository and were created by a network of more than 100 Spanish museums. This article explains the refinement of the data provided by the repository, mostly by adding a semantic structure thanks to the CIDOC-CRM ontology, and by simplifying the exceedingly complex terminologies employed in the original records. Particular attention is paid to the methods for geolocating the information, as well as adding temporal filters (among others) to user queries. The functionalities, interface, and technical requirements are also explored at length.

Remote photoplethysmography (rPPG) is an effective way of measuring Heart Rate (HR) from facial video of a person. Several methods have been proposed but measurement in realistic situation i.e, uncontrolled motion and illumination, is still a challenging task. It is observed that the performance of state-of-the-art methods often gets degraded in weekly illuminated environment. In this paper, a simple fusion based approach is proposed to reduce the performance degradation due to non-uniform illumination. An algorithm is proposed to fuse two complimentary color spaces i.e, Red, Green and Blue (RGB) and Multi Scale Retinex (MSR). The methodology includes salient spatiotemporal map generation from fusion of RGB and MSR. CNN is employed to map spatiotemporal features to corresponding HR value. To prove the efficacy of the proposed method, comparison is done with the state-of-the art methods with and without deep learning approach. Achieved experimental results proves that the proposed method yields comparable result for both inter and intra database testing on publicly available databases. • A novel HR estimation method, using RGB and MSR images for varying illumination. • Spatiotemporal maps are formed to improve the HR detection accuracy. • CNN is used to estimate HR from spatiotemporal maps. [ABSTRACT FROM AUTHOR]

Background Commensal bacteria such as probiotics that are neuroactive acutely affect the amplitudes of intestinal migrating motor complexes (MMCs). What is lacking for an improved understanding of these motility effects are region specific measurements of velocity and frequency. We have combined intraluminal pressure recordings with spatiotemporal diameter maps to analyze more completely effects of different strains of beneficial bacteria on motility. Methods Intraluminal peak pressure (PPr) was measured and video recordings made of mouse ex vivo jejunum and colon segments before and after intraluminal applications of Lactobacillus rhamnosus (JB-1) or Lactobacillus reuteri (DSM 17938). Migrating motor complex frequency and velocity were calculated. Key Results JB-1 decreased jejunal frequencies by 56% and 34% in colon. Jejunal velocities increased 171%, but decreased 31% in colon. Jejunal PPr decreased by 55% and in colon by 21%. DSM 17938 increased jejunal frequencies 63% and in colon 75%; jejunal velocity decreased 57%, but increased in colon 146%; jejunal PPr was reduced 26% and 12% in colon. TRAM-34 decreased frequency by 71% and increased velocity 200% for jejunum, but increased frequency 46% and velocity 50% for colon; PPr was decreased 59% for jejunum and 39% for colon. Conclusions & Inferences The results show that probiotics and other beneficial bacteria have strain and region-specific actions on gut motility that can be successfully discriminated using spatiotemporal mapping of diameter changes. Effects are not necessarily the same in colon and jejunum. Further research is needed on the detailed effects of the strains on enteric neuron currents for each gut region. [ABSTRACT FROM AUTHOR]

We used high definition radial, strain rate and intensity spatiotemporal mapping to quantify contractile movements of the body and associated structures of the rabbit caecum when the terminal ileum was being perfused with saline at a constant rate. This perfusion caused gradual distension of the caecum as a result of relative restriction of outflow from the ampulla caecalis. The body of the caecum exhibited two patterns of motility that appeared autonomous, i.e. occurred independently of any contractile activity at the inlet or outlet. Firstly, the pattern that we termed ladder activity consisted of an orderly sequential contraction of bundles of axially oriented circular muscle between the spiral turns of longitudinal muscle and proceeded either from base to tip or from tip to base at a similar frequency and velocity. Secondly, less-localised, rapidly propagating synchronous contractions of both circular and longitudinal muscle, which were more common when the caecum was distended, that were termed mass peristalsis. Movements of the ileum and sacculus rotundus occurred at the same frequency and were broadly coordinated. Distension of the distal sacculus occurred synchronously with contraction of the ileum and did not propagate in an orderly manner across the structure, i.e. was instantaneous. This pattern was consistent with hydrostatic distension. Contractions propagated through the ampulla caecalis in either an orad or an aborad direction at a similar frequency to, and broadly correlated with, those in the ileum. The frequencies of distension of the sacculus and of contraction in the ileum and ampulla were momentarily augmented during mass peristalsis. The authors conclude that there was some coordination between the contractile activity of the terminal ileum and the caecal ampulla during periods of ongoing inflow from the ileum and between these structures and the caecum during mass peristalsis. [ABSTRACT FROM AUTHOR]

Abstract: The first Kavli Prize in Neuroscience recognizes a confluence of career achievements that together provide a fundamental understanding of how brain and spinal cord circuits are assembled during development and function in the adult. The members of the Kavli Neuroscience Prize Committee have decided to reward three scientists (Sten Grillner, Thomas Jessell, and Pasko Rakic) jointly “for discoveries on the developmental and functional logic of neuronal circuits”. Pasko Rakic performed groundbreaking studies of the developing cerebral cortex, including the discovery of how radial glia guide the neuronal migration that establishes cortical layers and for the radial unit hypothesis and its implications for cortical connectivity and evolution. Thomas Jessell discovered molecular principles governing the specification and patterning of different neuron types and the development of their synaptic interconnection into sensorimotor circuits. Sten Grillner elucidated principles of network organization in the vertebrate locomotor central pattern generator, along with its command systems and sensory and higher order control. The discoveries of Rakic, Jessell and Grillner provide a framework for how neurons obtain their identities and ultimate locations, establish appropriate connections with each other, and how the resultant neuronal networks operate. Their work has significantly advanced our understanding of brain development and function and created new opportunities for the treatment of neurological disorders. Each has pioneered an important area of neuroscience research and left a legacy of exceptional scientific achievement, insight, communication, mentoring and leadership. [Copyright &y& Elsevier]

Spontaneous regular gut motility in zebrafish begins around 4 days post fertilisation (d.p.f.) and is modulated by release of acetylcholine and nitric oxide. The role of intrinsic or extrinsic innervation for initiating and propagating the spontaneous contractions, however, is not well understood. By creating spatiotemporal maps, we could examine spontaneous motility patterns in zebrafish larvae in vivo at 4 and 7 d.p.f. in more detail. Tetrodotoxin (TTX) was added to elucidate the importance of nervous control. Anterograde and retrograde contraction waves originated in the same region, just posterior to the intestinal bulb. This area correlates well with the distribution of Hu (human neuronal protein C/D)-immunoreactive nerve cell bodies. Whereas numerous immunoreactive nerve cells were present in the mid and distal intestine at both 4 and 7 d.p.f., fewer cells were seen anterior to the origin of contractions. The overall frequency of contractions (1.16±0.15 cycles min-1, N=14 at 4 d.p.f.; 1.05±0.09 cycles min-1, N=13 at 7 d.p.f.) and the interval between individual anterograde contraction waves (54.8±7.9 s at 4 d.p.f., N=14; 56.9±4.4 s, N=13 at 7 d.p.f.) did not differ between the two stages but the properties of the contractions were altered. The distance travelled by each wave increased from 591.0±43.8 μm at 4 d.p.f. (N=14) to 719.9±33.2 μm at 7 d.p.f. (N=13). By contrast, the velocity decreased from 4 d.p.f. (49.5 ±5 .5 μm s-1, N=12) to 7 d.p.f. (27.8±3.6 μm s-1, N=13). At 4 d.p.f., TTX did not affect any of the parameters whereas at 7 d.p.f. anterograde frequency (control 1.07±0.12 cycles min-1, N=8; TTX 0.55±0.13 cycles min-1, N=8) and distance travelled (control 685.1±45.9 μm, N=8; TTX 318.7±88.7 μm, N=6) were decreased. In conclusion, enteric or extrinsic innervation does not seem to be necessary to initiate spontaneous contractions of the gut in zebrafish larvae. However, later in development, nerves have an increasingly important role as modulators of intestinal activity. [ABSTRACT FROM AUTHOR]