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Towards Artificial Intelligence Driven Emotion Aware Fall Monitoring Framework Suitable for Elderly People with Neurological Disorder

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Brain Informatics (BI 2020)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 12241))

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Abstract

The contemporary world’s emerging issue is how the mental health and falling of a senior citizen with a neurological disorder can be maintained living at their homes as the number of aged people is increasing with the rising of life expectancy. With the advancement of the Internet of Things (IoT) and big data analytics, several works had been done on smart home health care systems that deal with in house monitoring for fall detection. Despite so much work, the challenges remain for not considering emotional care in the fall detection system for the old ones. As a remedy to the problems mentioned above, we propose an emotion aware fall monitoring framework using IoT, Artificial Intelligence (AI) Algorithms, and Big data analytics, which will deal with emotion recognition of the aged people, predictions about health conditions, and real-time fall monitoring. In the case of an emergency, the proposed framework alerts about a situation of urgency to the predefined caregiver. A smart ambulance or mobile clinic will reach the older adult’s location at minimum time.

M. J. Al Nahian and T. Ghosh—Have contributed equally

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Acknowledgement

This research received funding from ICT division of the Government of the People’s Republic of Bangladesh.

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Authors and Affiliations

  1. Bangladesh University of Professionals, Mirpur Cantonment, Dhaka, Bangladesh

    M. Jaber Al Nahian, Tapotosh Ghosh, Mohammed Nasir Uddin & Md. Maynul Islam

  2. Nottingham Trent University, Clifton Campus, Nottingham, NG11 8NS, UK

    Mufti Mahmud

  3. Institute of Information Technology, Jahangirnagar University, Savar, Dhaka, 1342, Bangladesh

    M. Shamim Kaiser

Authors
  1. M. Jaber Al Nahian
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  2. Tapotosh Ghosh
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  3. Mohammed Nasir Uddin
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  4. Md. Maynul Islam
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  5. Mufti Mahmud
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  6. M. Shamim Kaiser
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Corresponding author

Correspondence to M. Jaber Al Nahian .

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Editors and Affiliations

  1. Nottingham Trent University, Nottingham, UK

    Mufti Mahmud

  2. University of Padua, Padua, Italy

    Stefano Vassanelli

  3. Jahangirnagar University, Dhaka, Bangladesh

    M. Shamim Kaiser

  4. Maebashi Institute of Technology, Maebashi, Japan

    Ning Zhong

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Al Nahian, M.J., Ghosh, T., Uddin, M.N., Islam, M.M., Mahmud, M., Kaiser, M.S. (2020). Towards Artificial Intelligence Driven Emotion Aware Fall Monitoring Framework Suitable for Elderly People with Neurological Disorder. In: Mahmud, M., Vassanelli, S., Kaiser, M.S., Zhong, N. (eds) Brain Informatics. BI 2020. Lecture Notes in Computer Science(), vol 12241. Springer, Cham. https://doi.org/10.1007/978-3-030-59277-6_25

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  • DOI: https://doi.org/10.1007/978-3-030-59277-6_25

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-59276-9

  • Online ISBN: 978-3-030-59277-6

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