scholarly journals Pose-gait analysis for cetaceans with biologging tags

2021 ◽  
Author(s):  
Ding Zhang ◽  
Kari Goodbar ◽  
Nicole West ◽  
Veronique Lesage ◽  
Susan E Parks ◽  
...  

Biologging tags are a key enabling tool for investigating cetacean behavior and locomotion in their natural habitat. Identifying and then parameterizing gait from movement sensor data is critical for these investigations. But how best to characterize gait from tag data remains an open question. Further, the location and orientation of the tag on an animal in the field are variable and can change multiple times during deployment. As a result, the relative orientation of the tag with respect to (wrt) the animal must be determined before a wide variety of further analyses. Currently, custom scripts that involve specific manual heuristics methods tend to be used in the literature. These methods require a level of knowledge and experience that can affect the reliability and repeatability of the analysis. The authors of this work argue that an animal's gait is composed of a sequence of body poses observed by the tag, demonstrating a specific spatial pattern in the data that can be utilized for different purposes. This work presents an automated data processing pipeline (and software) that takes advantage of the common characteristics of pose and gait of the animal to 1) Identify time instances associated with occurrences of relative motion between the tag and animal; 2) Identify the relative orientation of tag wrt the animal’s body for a given data segment; and 3) Extract gait parameters that are invariant to pose and tag orientation. The authors included biologging tag data from bottlenose dolphins, humpback whales, and beluga whales in this work to validate and demonstrate the approach. Results show that the average relative orientation error of the tag wrt the dolphin’s body after processing was within 11 degrees in roll, pitch, and yaw directions. The average precision and recall for identifying relative tag motion were 0.87 and 0.89, respectively.  Examples of the resulting pose and gait analysis demonstrate the potential of this approach to enhance studies that use tag data to investigate movement and behavior. MATLAB source code and data presented in the paper were made available to the public (https://github.com/ding-z/cetacean-pose-gait-analysis.git), with suggestions related to tag data processing practices provided in this paper. The proposed analysis approach will facilitate the use of biologging tags to study cetacean locomotion and behavior.

Sensors ◽  
2021 ◽  
Vol 21 (22) ◽  
pp. 7517
Author(s):  
Vânia Guimarães ◽  
Inês Sousa ◽  
Miguel Velhote Correia

Gait performance is an important marker of motor and cognitive decline in older adults. An instrumented gait analysis resorting to inertial sensors allows the complete evaluation of spatiotemporal gait parameters, offering an alternative to laboratory-based assessments. To estimate gait parameters, foot trajectories are typically obtained by integrating acceleration two times. However, to deal with cumulative integration errors, additional error handling strategies are required. In this study, we propose an alternative approach based on a deep recurrent neural network to estimate heel and toe trajectories. We propose a coordinate frame transformation for stride trajectories that eliminates the dependency from previous strides and external inputs. Predicted trajectories are used to estimate an extensive set of spatiotemporal gait parameters. We evaluate the results in a dataset comprising foot-worn inertial sensor data acquired from a group of young adults, using an optical motion capture system as a reference. Heel and toe trajectories are predicted with low errors, in line with reference trajectories. A good agreement is also achieved between the reference and estimated gait parameters, in particular when turning strides are excluded from the analysis. The performance of the method is shown to be robust to imperfect sensor-foot alignment conditions.


2021 ◽  
Vol 85 ◽  
pp. 55-64
Author(s):  
Julian Rudisch ◽  
Thomas Jöllenbeck ◽  
Lutz Vogt ◽  
Thomas Cordes ◽  
Thomas Jürgen Klotzbier ◽  
...  

2020 ◽  
Vol 53 (2) ◽  
pp. 15990-15997
Author(s):  
Felix Laufer ◽  
Michael Lorenz ◽  
Bertram Taetz ◽  
Gabriele Bleser

2021 ◽  
Vol 237 ◽  
pp. 110810
Author(s):  
Chenli Wang ◽  
Jun Jiang ◽  
Thomas Roth ◽  
Cuong Nguyen ◽  
Yuhong Liu ◽  
...  

2017 ◽  
Vol 8 (2) ◽  
pp. 88-105 ◽  
Author(s):  
Gunasekaran Manogaran ◽  
Daphne Lopez

Ambient intelligence is an emerging platform that provides advances in sensors and sensor networks, pervasive computing, and artificial intelligence to capture the real time climate data. This result continuously generates several exabytes of unstructured sensor data and so it is often called big climate data. Nowadays, researchers are trying to use big climate data to monitor and predict the climate change and possible diseases. Traditional data processing techniques and tools are not capable of handling such huge amount of climate data. Hence, there is a need to develop advanced big data architecture for processing the real time climate data. The purpose of this paper is to propose a big data based surveillance system that analyzes spatial climate big data and performs continuous monitoring of correlation between climate change and Dengue. Proposed disease surveillance system has been implemented with the help of Apache Hadoop MapReduce and its supporting tools.


2018 ◽  
Vol 21 (4) ◽  
pp. 458-466
Author(s):  
Sadiq J. Hamandi ◽  
Marwa Azzawi ◽  
Waleed Abdulwahed

Total hip replacement (THR) is an elective surgical procedure with the primary indication being pain relief. The aim of this study is to analyze gait dynamics for patients after they underwent a unilateral THR surgery and compare it with normal parameters. To investigate the gait dynamics a gait analysis was performed on five patients after they underwent a unilateral THR surgery; only two of them were examined before the surgery. The gait analysis was performed using a digital video camera with two force plates. Kinematics data were obtained from 2D trajectories of seven passive markers using SkillSpector software. MATLAB software has been used for inverse dynamics computation. General gait parameters, Harris Hip Score, joints’ angles, forces, moments and powers were obtained during gait cycle. It was found that the average of improvement in Harris Hip Score (for four patients who were examined 1.5, 2.5, 3 and 9 months after surgery) is 61.8 points, which is an indication of pain relief. In the other hand, the general gait parameters were found slightly lower than normal after THR surgery. The average hip reaction force was found to be 2.988 N/BW, which is within normal range. Also, the average of maximum hip extension and maximum hip flexion angles were found to be 25.69 and -13.524 degree respectively, which both are within normal ranges. Furthermore, hip, knee and ankle moments and powers results showed some abnormality. Therefore as a conclusion, patient satisfaction and functional improvement are not related to general gait parameter. And it is not unusual that gait mechanics improvement would not reach normal after months of recovery. Also, the results of gait dynamics which are from the engineer’s perspective are compatible with Harris Hip Score, which is from the physician’s perspective, in quantifying surgical results and subsequent recovery progress.


2020 ◽  
Author(s):  
Christopher Mccullough ◽  
Tamara Bandikova ◽  
William Bertiger ◽  
Carmen Boening ◽  
Sung Byun ◽  
...  

<p>The Gravity Recovery and Climate Experiment Follow-On (GRACE-FO), launched in May 2018, provides invaluable information about mass change in the Earth system, continuing the legacy of GRACE. Fundamental requirements for successful mass change recovery are precise orbit determination and inter-satellite ranging, determination of the relative clock alignment of the ultra-stable oscillators (USOs), precise attitude determination, and accelerometry. NASA/Caltech Jet Propulsion Laboratory is the official Level-1 data processing and analysis center, and is currently processing software version 04. Here we present analysis of the aforementioned GRACE-FO sensor data, as well a preview of an upcoming GRACE reprocessing, and a discussion of measurement performance.</p>


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