Machine Learning Methods for Environmental-Enrichment-Related Variations in Behavioral Responses of Laboratory Rats

Ipiña, Karmele López de; Cepeda, Hodei; Requejo, Catalina; Fernández, Elsa; Calvo, Pilar M.; Lafuente, José Vicente

doi:10.1007/978-3-030-19591-5_43

Cited by 2 publications

(5 citation statements)

References 7 publications

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“…This is the Use case 1 and it was a coordinated Cobot learning task between the two-arms of Cobot and a worker ( Figure 3 ). The monitoring video sequences acquired by the external high-quality camera were processed by a custom toolbox in MATLAB to create activity time-series [ 36 , 37 ].…”

Section: Methodsmentioning

confidence: 99%

“…The monitoring video sequences were acquired by a high-quality camera, and processed by a custom toolbox in MATLAB in order to create activity time-series [ 36 , 37 , 38 ]. Then, during the pre-processing the activity areas (motion detection) were calculated based on a frame difference method (Frame absolute difference) between two consecutive frames.…”

Section: Methodsmentioning

confidence: 99%

“…The evolution and coordination of the components in the system (Cobots and human) was modelled by the trajectories of N activity centroids along time. In this sense as in [ 36 , 37 , 38 ] k-means algorithm was selected because the centroids need to capture the information provided by the main activity areas in order to analyse the environment coordination. In addition, as in previous works [ 36 , 37 , 38 , 39 , 40 ] there was essential knowledge on the task (R/H activity distributed by areas, behaviour features,) and also there were critical requirements of real-time.…”

Section: Methodsmentioning

confidence: 99%

“…In this sense as in [ 36 , 37 , 38 ] k-means algorithm was selected because the centroids need to capture the information provided by the main activity areas in order to analyse the environment coordination. In addition, as in previous works [ 36 , 37 , 38 , 39 , 40 ] there was essential knowledge on the task (R/H activity distributed by areas, behaviour features,) and also there were critical requirements of real-time. Thus, within each frame in the binarized image, the coordinates of the centres of all the activity areas were calculated and then k-means was applied to find the centroids of the activity clusters (centres, with x and y coordinates).…”

Section: Methodsmentioning

confidence: 99%

See 3 more Smart Citations

HUMANISE: Human-Inspired Smart Management, towards a Healthy and Safe Industrial Collaborative Robotics

López-de-Ipiña

Iradi

Fernández

et al. 2023

Sensors

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The workplace is evolving towards scenarios where humans are acquiring a more active and dynamic role alongside increasingly intelligent machines. Moreover, the active population is ageing and consequently emerging risks could appear due to health disorders of workers, which requires intelligent intervention both for production management and workers’ support. In this sense, the innovative and smart systems oriented towards monitoring and regulating workers’ well-being will become essential. This work presents HUMANISE, a novel proposal of an intelligent system for risk management, oriented to workers suffering from disease conditions. The developed support system is based on Computer Vision, Machine Learning and Intelligent Agents. Results: The system was applied to a two-arm Cobot scenario during a Learning from Demonstration task for collaborative parts transportation, where risk management is critical. In this environment with a worker suffering from a mental disorder, safety is successfully controlled by means of human/robot coordination, and risk levels are managed through the integration of human/robot behaviour models and worker’s models based on the workplace model of the World Health Organization. The results show a promising real-time support tool to coordinate and monitoring these scenarios by integrating workers’ health information towards a successful risk management strategy for safe industrial Cobot environments.

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Section: Methodsmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

See 2 more Smart Citations

HUMANISE: Human-Inspired Smart Management, towards a Healthy and Safe Industrial Collaborative Robotics

López-de-Ipiña

Iradi

Fernández

et al. 2023

Sensors

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“…Finally, [134] presents a method for automatic analysis of behavioral variables of laboratory rats to describe their activity, based on ML and image analysis techniques. This work present a set of experiments to investigate whether rat strain influences the behavioral and physiologic measures typically used to assess stress responses.…”

Section: Processing Neuroimaging Studiesmentioning

confidence: 99%

Artificial intelligence within the interplay between natural and artificial computation: Advances in data science, trends and applications

et al. 2020

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Artificial intelligence and all its supporting tools, e.g. machine and deep learning in computational intelligence-based systems, are rebuilding our society (economy, education, life-style, etc.) and promising a new era for the social welfare state. In this paper we summarize recent advances in data science and artificial intelligence within the interplay between natural and artificial computation. A review of recent works published in the latter field and the state the art are summarized in a comprehensive and self-contained way to provide a baseline framework for the international community in artificial intelligence. Moreover, this paper aims to provide a complete analysis and some relevant discussions of the current trends and insights within several theoretical and application fields covered in the essay, from theoretical models in

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Machine Learning Methods for Environmental-Enrichment-Related Variations in Behavioral Responses of Laboratory Rats

Cited by 2 publications

References 7 publications

HUMANISE: Human-Inspired Smart Management, towards a Healthy and Safe Industrial Collaborative Robotics

HUMANISE: Human-Inspired Smart Management, towards a Healthy and Safe Industrial Collaborative Robotics

Artificial intelligence within the interplay between natural and artificial computation: Advances in data science, trends and applications

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