Criteria for Comparison of Robot Movement Trajectories and Manual Movements of a Doctor for Performing Maxillofacial Surgeries

Abstract Cutting-edge technologies are extremely useful to develop new workflows in studying ecological data, particularly to understand animal behaviour and movement trajectories at the individual level. Although parental care is a well-studied phenomenon, most studies have been focused on direct observational or video recording data, as well as experimental manipulation. Therefore, what happens out of our sight still remains unknown. Using high-frequency GPS/GSM dataloggers and tri-axial accelerometers we monitored 25 Bonelli’s eagles (Aquila fasciata) during the breeding season to understand parental activities from a broader perspective. We used recursive data, measured as number of visits and residence time, to reveal nest attendance patterns of biparental care with role specialization between sexes. Accelerometry data interpreted as the Overall Dynamic Body Acceleration, a proxy of energy expenditure, showed strong differences in parental effort throughout the breeding season and between sexes. Thereby, males increased substantially their energetic requirements, due to the increased workload, while females spent most of the time on the nest. Furthermore, during critical phases of the breeding season, a low percentage of suitable hunting spots in eagles’ territories led them to increase their ranging behaviour in order to find food, with important consequences in energy consumption and mortality risk. Our results highlight the crucial role of males in raptor species exhibiting biparental care. Finally, we exemplify how biologging technologies are an adequate and objective method to study parental care in raptors as well as to get deeper insight into breeding ecology of birds in general.

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Targets, Grievances, and Social Movement Trajectories

Comparative Political Studies ◽

10.1177/0010414018806532 ◽

2018 ◽

pp. 001041401880653 ◽

Cited By ~ 1

Author(s):

Erica S. Simmons

Keyword(s):

Social Movement ◽

Movement Trajectories

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Recognizing human activities based on head movement trajectories

2014 5th IEEE Conference on Cognitive Infocommunications (CogInfoCom) ◽

10.1109/coginfocom.2014.7020460 ◽

2014 ◽

Cited By ~ 3

Author(s):

Kornel Bertok ◽

Attila Fazekas

Keyword(s):

Human Activities ◽

Head Movement ◽

Movement Trajectories

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OP43 Robotic Or Conventional Gait Training Rehabilitation? A Health Technology Assessment Study

International Journal of Technology Assessment in Health Care ◽

10.1017/s026646231800096x ◽

2018 ◽

Vol 34 (S1) ◽

pp. 16-17

Author(s):

Martina Andellini ◽

Francesco Faggiano ◽

Roxana di Mauro ◽

Pietro Derrico ◽

Matteo Ritrovato

Keyword(s):

Health Technology Assessment ◽

Technology Assessment ◽

Conventional Therapy ◽

Health Technology ◽

Gait Training ◽

Core Model ◽

Gait Rehabilitation ◽

Alternative Technologies ◽

Movement Trajectories ◽

Robotic Gait

Introduction:The purpose of this study is to gather evidence on safety and overall effectiveness of three alternative technologies for gait rehabilitation in diplegic children with Cerebral Palsy: robotic, conventional and joint conventional and robotic gait training.Methods:A new methodology, decision-oriented health technology assessment (DoHTA), was applied to assess the technology on clinical, technical, organizational, economic, social and ethical, legal and safety domains. This method, conceived as a hospital-based HTA tool for supporting the introduction of innovative technologies, has been implemented merging the EUnetHTA Core Model® with the Multi-Criteria Decision Analysis. In particular, the general items of the EUnetHTA Core Model® are re-formulated as performance indicators and re-placed along a decision tree structure that, from the one hand, respects the original top-down design of the EUnetHTA model (growing level of detail from domains to issues) and, from the other hand, allows obtaining a quantitative evaluation of each identified performance indicator.Results:The multiple indicators, which have been identified for the seven domains, play important and different roles in the alternative technologies evaluation. DoHTA results showed that robotic system offers the possibility to control more accurately the exerted forces and movement trajectories than the traditional therapy. It gives the possibility to measure the task performances parameters and to receive the patient feedback simultaneously. To carry out robotic gait rehabilitation fewer therapists are required compared with the conventional therapy, resulting in lower therapists’ physical workload.Conclusions:Despite the great perspectives that robotics offer to motor rehabilitation, it seems that robotic gait training could not provide greater benefits in terms of motor and functional recovery compared to the conventional therapy. Preliminary results, supported by most recent literature evidence, lead to the hypothesis that joint use of robotic and conventional therapy can produce better clinical outcomes than the separate use of the two rehabilitation techniques.

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Horizontal-vertical movement relationships: Adélie penguins forage continuously throughout provisioning trips

Movement Ecology ◽

10.1186/s40462-021-00280-8 ◽

2021 ◽

Vol 9 (1) ◽

Author(s):

Javed Riaz ◽

Sophie Bestley ◽

Simon Wotherspoon ◽

Louise Emmerson

Keyword(s):

Environmental Conditions ◽

Optimal Foraging ◽

Three Dimensional ◽

Spatial Location ◽

Vertical Movement ◽

Foraging Activity ◽

Directed Movement ◽

Vertical Movements ◽

Movement Trajectories ◽

Adélie Penguins

Abstract Background Diving marine predators forage in a three-dimensional environment, adjusting their horizontal and vertical movement behaviour in response to environmental conditions and the spatial distribution of prey. Expectations regarding horizontal-vertical movements are derived from optimal foraging theories, however, inconsistent empirical findings across a range of taxa suggests these behavioural assumptions are not universally applicable. Methods Here, we examined how changes in horizontal movement trajectories corresponded with diving behaviour and marine environmental conditions for a ubiquitous Southern Ocean predator, the Adélie penguin. Integrating extensive telemetry-based movement and environmental datasets for chick-rearing Adélie penguins at Béchervaise Island, we tested the relationships between horizontal move persistence (continuous scale indicating low [‘resident’] to high [‘directed’] movement autocorrelation), vertical dive effort and environmental variables. Results Penguins dived continuously over the course of their foraging trips and lower horizontal move persistence corresponded with less intense foraging activity, likely indicative of resting behaviour. This challenges the traditional interpretation of horizontal-vertical movement relationships based on optimal foraging models, which assumes increased residency within an area translates to increased foraging activity. Movement was also influenced by different environmental conditions during the two stages of chick-rearing: guard and crèche. These differences highlight the strong seasonality of foraging habitat for chick-rearing Adélie penguins at Béchervaise Island. Conclusions Our findings advance our understanding of the foraging behaviour for this marine predator and demonstrates the importance of integrating spatial location and behavioural data before inferring habitat use.

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Object detection and tracking in video sequences: formalization, metrics and results

Informatics ◽

10.37661/1816-0301-2021-18-1-43-60 ◽

2021 ◽

Vol 18 (1) ◽

pp. 43-60

Author(s):

R. P. Bohush ◽

S. V. Ablameyko

Keyword(s):

Moving Objects ◽

Human Movement ◽

Video Sequences ◽

Multiple Objects ◽

Movement Trajectories ◽

Detection And Tracking ◽

Form Features ◽

One And Many ◽

Tracking Objects

One of the promising areas of development and implementation of artificial intelligence is the automatic detection and tracking of moving objects in video sequence. The paper presents a formalization of the detection and tracking of one and many objects in video. The following metrics are considered: the quality of detection of tracked objects, the accuracy of determining the location of the object in a frame, the trajectory of movement, the accuracy of tracking multiple objects. Based on the considered generalization, an algorithm for tracking people has been developed that uses the tracking through detection method and convolutional neural networks to detect people and form features. Neural network features are included in a composite descriptor that also contains geometric and color features to describe each detected person in the frame. The results of experiments based on the considered criteria are presented, and it is experimentally confirmed that the improvement of the detector operation makes it possible to increase the accuracy of tracking objects. Examples of frames of processed video sequences with visualization of human movement trajectories are presented.

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Event-based pattern detection in active dendrites

10.1101/690792 ◽

2019 ◽

Cited By ~ 1

Author(s):

Johannes Leugering ◽

Pascal Nieters ◽

Gordon Pipa

Keyword(s):

Single Neuron ◽

Logic Gate ◽

Dendritic Tree ◽

Dendritic Morphology ◽

Neuron Models ◽

Plateau Potentials ◽

Computational Function ◽

Movement Trajectories ◽

Timing Variability ◽

Long Timescales

AbstractMany behavioural tasks require an animal to integrate information on a slow timescale that can exceed hundreds of milliseconds. How this is realized by neurons with membrane time constants on the order of tens of milliseconds or less remains an open question. We show, how the interaction of two kinds of events within the dendritic tree, excitatory postsynaptic potentials and locally generated dendritic plateau potentials, can allow a single neuron to detect specific sequences of spiking input on such slow timescales. Our conceptual model reveals, how the morphology of a neuron’s dendritic tree determines its computational function, which can range from a simple logic gate to the gradual integration of evidence to the detection of complex spatio-temporal spike-sequences on long timescales. As an example, we illustrate in a simulated navigation task how this mechanism can even allow individual neurons to reliably detect specific movement trajectories with high tolerance for timing variability. We relate our results to conclusive findings in neurobiology and discuss implications for both experimental and theoretical neuroscience.Author SummaryThe recognition of patterns that span multiple timescales is a critical function of the brain. This is a conceptual challenge for all neuron models that rely on the passive integration of synaptic inputs and are therefore limited to the rigid millisecond timescale of post-synaptic currents. However, detailed biological measurements recently revealed that single neurons actively generate localized plateau potentials within the dendritic tree that can last hundreds of milliseconds. Here, we investigate single-neuron computation in a model that adheres to these findings but is intentionally simple. Our analysis reveals how plateaus act as memory traces, and their interaction as defined by the dendritic morphology of a neuron gives rise to complex non-linear computation. We demonstrate how this mechanism enables individual neurons to solve difficult, behaviorally relevant tasks that are commonly studied on the network-level, such as the detection of variable input sequences or the integration of evidence on long timescales. We also characterize computation in our model using rate-based analysis tools, demonstrate why our proposed mechanism of dendritic computation cannot be detected under this analysis and suggest an alternative based on plateau timings. The interaction of plateau events in dendritic trees is, according to our argument, an elementary principle of neural computation which implies the need for a fundamental change of perspective on the computational function of neurons.

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Variation in winter site fidelity within and among individuals influences movement behavior in a partially migratory ungulate

PLoS ONE ◽

10.1371/journal.pone.0258128 ◽

2021 ◽

Vol 16 (9) ◽

pp. e0258128

Author(s):

Timothy J. Fullman ◽

Brian T. Person ◽

Alexander K. Prichard ◽

Lincoln S. Parrett

Keyword(s):

Site Fidelity ◽

Rangifer Tarandus ◽

First Passage Time ◽

Cost Benefit ◽

Movement Behavior ◽

Long Distance ◽

Directed Movement ◽

Movement Trajectories ◽

Wintering Areas ◽

Wintering Area

Many animals migrate to take advantage of temporal and spatial variability in resources. These benefits are offset with costs like increased energetic expenditure and travel through unfamiliar areas. Differences in the cost-benefit ratio for individuals may lead to partial migration with one portion of a population migrating while another does not. We investigated migration dynamics and winter site fidelity for a long-distance partial migrant, barren ground caribou (Rangifer tarandus granti) of the Teshekpuk Caribou Herd in northern Alaska. We used GPS telemetry for 76 female caribou over 164 annual movement trajectories to identify timing and location of migration and winter use, proportion of migrants, and fidelity to different herd wintering areas. We found within-individual variation in movement behavior and wintering area use by the Teshekpuk Caribou Herd, adding caribou to the growing list of ungulates that can exhibit migratory plasticity. Using a first passage time–net squared displacement approach, we classified 78.7% of annual movement paths as migration, 11.6% as residency, and 9.8% as another strategy. Timing and distance of migration varied by season and wintering area. Duration of migration was longer for fall migration than for spring, which may relate to the latter featuring more directed movement. Caribou utilized four wintering areas, with multiple areas used each year. This variation occurred not just among different individuals, but state sequence analyses indicated low fidelity of individuals to wintering areas among years. Variability in movement behavior can have fitness consequences. As caribou face the pressures of a rapidly warming Arctic and ongoing human development and activities, further research is needed to investigate what factors influence this diversity of behaviors in Alaska and across the circumpolar Arctic.

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LEARNING THE 3D POSE OF VEHICLES FROM 2D VEHICLE PATCHES

ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences ◽

10.5194/isprs-archives-xliii-b2-2020-683-2020 ◽

2020 ◽

Vol XLIII-B2-2020 ◽

pp. 683-688

Author(s):

C. Koetsier ◽

T. Peters ◽

M. Sester

Keyword(s):

Elevation Angle ◽

Training Data ◽

Training Dataset ◽

Image Patch ◽

Movement Trajectories ◽

Surveillance Camera ◽

Image Patches ◽

Ground Point ◽

Precise Movement ◽

Real Time Applications

Abstract. Estimating vehicle poses is crucial for generating precise movement trajectories from (surveillance) camera data. Additionally for real time applications this task has to be solved in an efficient way. In this paper we introduce a deep convolutional neural network for pose estimation of vehicles from image patches. For a given 2D image patch our approach estimates the 2D coordinates of the image representing the exact center ground point (cx, cy) and the orientation of the vehicle - represented by the elevation angle (e) of the camera with respect to the vehicle’s center ground point and the azimuth rotation (a) of the vehicle with respect to the camera. To train a accurate model a large and diverse training dataset is needed. Collecting and labeling such large amount of data is very time consuming and expensive. Due to the lack of a sufficient amount of training data we show furthermore, that also rendered 3D vehicle models with artificial generated textures are nearly adequate for training.

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