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Received 7 January 2024, accepted 21 February 2024, date of publication 26 February 2024, date of current version 7 March 2024. Digital Object Identifier 10.1 109/ACCESS.2024.3370684 MediSign: An Attention-Based CNN-BiLSTM Approach of Classifying Word Level Signs for Patient-Doctor Interaction in Hearing Impaired Community MD

. Digital Object Identifier 10.1 109/ACCESS.2024.3370684 MediSign: An Attention-Based CNN-BiLSTM Approach of Classifying Word Level Signs for Patient-Doctor Interaction in Hearing Impaired Community MD. AMIMUL IHSAN 1, ABRAR FAIAZ ERAM 2, LUTFUN NAHAR 1, AND MUHAMMAD ABDUL KADIR 1, (Member, IEEE) 1Department of Biomedical Physics and Technology, University of Dhaka, Dhaka 1000, Bangladesh 2Department of Electrical and Electronic Engineering, Bangladesh University of Engineering and Technology, Dhaka 1000, Bangladesh Corresponding author: Muhammad Abdul Kadir (<PRESIDIO_ANONYMIZED_EMAIL_ADDRESS>) This work was supported by the International Science Program (ISP) of Uppsala University, Sweden

M. A. Ihsan et al.: MediSign: An Attention-Based CNN-BiLSTM Approach the provision of patient-centered care and the establishment of trust. Despite legal requirements for American Sign Language (ASL) medical interpreters in the United States [1], many clinicians still rely on inadequate communication methods, such as writing notes or assuming patients can lip-read [2]. This can lead to misunderstandings, misdiagnoses, and inadequate treatment, which can have serious consequences for the patient’s health and well-being

. A word-level sign language interpretation system that is aimed toward detecting medically relevant signs can allow smooth communication between doctors and hearing impaired patients, ensuring seamless medical care. To that end, a dataset from twenty distinct signers of diverse backgrounds performing 30 frequently used words in patient-doctor interaction was created. The proposed system has been built employing MobileNetV2 in conjunction with an attention-based Bidirectional LSTM network to achieve robust classification, where the validation accuracy and f1- scores were 95.83% and 93%, respectively

. This work involved human subjects or animals in its research. Approval of all ethical and experimental procedures and protocols was granted by the Research Review Committee of the Department of Biomedical Physics and Technology, University of Dhaka. ABSTRACT Along with day-to-day communication, receiving medical care is quite challenging for the hearing impaired and mute population, especially in developing countries where medical facilities are not as modernized as in the West. A word-level sign language interpretation system that is aimed toward detecting medically relevant signs can allow smooth communication between doctors and hearing impaired patients, ensuring seamless medical care

. The hearing impaired person who is facing health challenges may not be able to properly explain his symptoms if the human interpreter is not well-versed in the sign language or is uncooperative. Research has indicated that the presence of inadequate communication between healthcare providers and patients who are hearing impaired or hard of hearing (HOH) remains a significant obstacle in VOLUME 12, 2024 2024 The Authors. This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 License. For more information, see https://creativecommons.org/licenses/by-nc-nd/4.0/ 33803

. However, when people with speech and hearing impairments The associate editor coordinating the review of this manuscript and approving it for publication was Ganesh Naik . speak with those who do not understand sign language, this method of communication is ineffective. Along with day-to-day communication, receiving medical care is quite challenging for the hearing impaired and mute population, especially in developing countries. A capable individual needs to accompany them when they go to medical centers and explain their symptoms to the medical professionals

. Along with day-to-day communication, receiving medical care is quite challenging for the hearing impaired and mute population, especially in developing countries. A capable individual needs to accompany them when they go to medical centers and explain their symptoms to the medical professionals. The hearing impaired person who is facing health challenges may not be able to properly explain his symptoms if the human interpreter is not well-versed in the sign language or is uncooperative

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