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Face Recognition-Based Automatic Hospital Admission with SMS Alerts

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Abstract

When the person met with an accident is brought to the hospital, there are many official formalities (e.g., admission form to be filled) before the treatment that can be started. In some severe cases, these formalities can delay the treatment, which could be fatal to the patient. The automated system which can fill these forms with the help of face recognition could severely cut down the delays. But, in some cases, the injury and the blood on to the face fail facial recognition. To overcome this problem, we have proposed a facial vector-based algorithm. In the current work, we have also demonstrated, sending the SMS to the concerned authorities (police) and even to the relatives of the patient automatically using GSM modules. The patient’s information was received from centralized databases of different hospitals that are linked through the internet. We have tested the algorithm on more than 213K images from different databases like celebA, LFW, UCFI. We found that the maximum accuracy of our system was 98.23%. As a proof-of-concept, we tried testing on 51 real-time patient images and found that the accuracy is 94.11%. This automated form filling not only reduced the delay in hospital admission, but also also helped in treatment, because of the auto-filled medical history.

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Acknowledgements

First of all, we would like to express our sincere gratitude to the management, doctors, and supporting staff of Karve Hospital, without their support, we could not have verified the results in the field. Second, We would like to thank all the 51 anonymous patients of Karve Hospital for allowing us to use their cartoonized photos in the manuscript for a better understanding of our work. We are grateful to Mr. Ghone (stretcher boy) who helped us every time standing at the entrance of the special-case entry to pass the patient through the special-case entrance. Finally, we would like to thank all the colleagues of Ninad’s Research Lab and K. J. Somaiya College of Engineering who made this work possible.

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Authors and Affiliations

  1. K. J. Somaiya College of Engineering, Vidyanagar, Vidyavihar, Mumbai, 400077, Maharashtra, India

    Ninad Mehendale

  2. Ninad’s Research Lab, 103, Saraswati Niwas, M.G. Road, Naupada, Thane, 400602, Maharashtra, India

    Mamata Parab

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  1. Mamata Parab
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  2. Ninad Mehendale
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Correspondence to Ninad Mehendale.

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Authors M. Parab and N. Mehendale declare that they have no conflict of interest.

Involvement of Human Participant and Animals

This article does not contain any studies with animals or Humans performed by any of the authors. All the necessary permissions were obtained from the Institute Ethical Committee and concerned authorities to use video captures of patients.

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Informed consent was acquired from all human participants whose videos were used for this Novel work.

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Parab, M., Mehendale, N. Face Recognition-Based Automatic Hospital Admission with SMS Alerts. SN COMPUT. SCI. 2, 55 (2021). https://doi.org/10.1007/s42979-021-00448-4

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