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Feasibility Study on Eye Gazing in Socially Assistive Robotics: An Intensive Care Unit Scenario

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Social Robotics (ICSR 2023)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 14453 ))

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Abstract

Recently, there has been an increasing interest in the adoption of socially assistive robots to support and alleviate the workload of clinical personnel in hospital settings. This work proposes the adoption of a socially assistive robot in Intensive Care Units to evaluate the criticality scores of bedridden patients. Within this scenario, the human gaze represents a key clinical cue for assessing a patient’s conscious state. In this work, a user study involving 10 participants role-playing 4 levels of consciousness is performed. The collected videos were manually annotated considering 6 gazing directions and an open-source automatic tool was used to extract head pose and eye gazing features. Different feature sets and classification models were compared to find the most appropriate configuration to detect user gaze in this scenario. Results have suggested that the most accurate gazing estimation is obtained when the head pose information is combined with the eye orientation (0.85). Additionally, the framework proposed in this study seems to be user-independent, thereby encouraging the deployment of appropriate robotic solutions in real assistive contexts.

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Notes

  1. 1.

    http://wiki.ros.org/smach.

  2. 2.

    https://github.com/naggety/picotts.

  3. 3.

    https://learn.microsoft.com/en-us/azure/ai-services/speech-service/index-speech-to-text.

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Acknowledgements

This work has been partially supported by European Union - Next Generation EU under Project: “A novel public-private alliance to generate socioeconomic, biomedical and technological solutions for an inclusive Italian ageing society” (Age-IT), CUP: B83C22004800006 and by Piano Nazionale per gli Investimenti Complementari PNC-PNRR Fit for Medical Robotics (Fit4MedRob), CUP: B53C22006950001.

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Authors and Affiliations

  1. Department of Industrial Engineering, University of Florence, Florence, Italy

    Alessandra Sorrentino, Andrea Magnotta, Laura Fiorini & Filippo Cavallo

  2. BioRobotics Institute, Scuola Superiore Sant’Anna, Pontedera, Italy

    Laura Fiorini & Filippo Cavallo

  3. ITEM-OXYGEN S.R.L., Altamura, Bari, Italy

    Giovanni Piccinino, Alessandro Anselmo & Nicola Laurieri

Authors
  1. Alessandra Sorrentino
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  2. Andrea Magnotta
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  3. Laura Fiorini
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  4. Giovanni Piccinino
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  5. Alessandro Anselmo
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  6. Nicola Laurieri
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  7. Filippo Cavallo
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Corresponding author

Correspondence to Alessandra Sorrentino .

Editor information

Editors and Affiliations

  1. Qatar University, Doha, Qatar

    Abdulaziz Al Ali

  2. Qatar University, Doha, Qatar

    John-John Cabibihan

  3. Qatar University, Doha, Qatar

    Nader Meskin

  4. University of Naples Federico II, Napoli, Italy

    Silvia Rossi

  5. Qingdao University, Qingdao, China

    Wanyue Jiang

  6. The University of Alabama, Tuscaloosa, AL, USA

    Hongsheng He

  7. National University of Singapore, Queenstown, Singapore

    Shuzhi Sam Ge

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© 2024 The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

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Sorrentino, A. et al. (2024). Feasibility Study on Eye Gazing in Socially Assistive Robotics: An Intensive Care Unit Scenario. In: Ali, A.A., et al. Social Robotics. ICSR 2023. Lecture Notes in Computer Science(), vol 14453 . Springer, Singapore. https://doi.org/10.1007/978-981-99-8715-3_5

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  • DOI: https://doi.org/10.1007/978-981-99-8715-3_5

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  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-99-8714-6

  • Online ISBN: 978-981-99-8715-3

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