Social Health Protection During the COVID-Pandemic Using IoT

Reddy, M. Aaschita; Reddy, B Manidweep; Mukund, C. S.; Venneti, Kiran; Preethi, D; Boopathi, Sampath

doi:10.4018/978-1-7998-8394-4.ch009

Cited by 82 publications

References 32 publications

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Early detection of cardiorespiratory complications and training monitoring using wearable ECG sensors and CNN

Lu,

Feng,

Zhang

2024

BMC Med Inform Decis Mak

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This research study demonstrates an efficient scheme for early detection of cardiorespiratory complications in pandemics by Utilizing Wearable Electrocardiogram (ECG) sensors for pattern generation and Convolution Neural Networks (CNN) for decision analytics. In health-related outbreaks, timely and early diagnosis of such complications is conclusive in reducing mortality rates and alleviating the burden on healthcare facilities. Existing methods rely on clinical assessments, medical history reviews, and hospital-based monitoring, which are valuable but have limitations in terms of accessibility, scalability, and timeliness, particularly during pandemics. The proposed scheme commences by deploying wearable ECG sensors on the patient’s body. These sensors collect data by continuously monitoring the cardiac activity and respiratory patterns of the patient. The collected raw data is then transmitted securely in a wireless manner to a centralized server and stored in a database. Subsequently, the stored data is assessed using a preprocessing process which extracts relevant and important features like heart rate variability and respiratory rate. The preprocessed data is then used as input into the CNN model for the classification of normal and abnormal cardiorespiratory patterns. To achieve high accuracy in abnormality detection the CNN model is trained on labeled data with optimized parameters. The performance of the proposed scheme is evaluated and gauged using different scenarios, which shows a robust performance in detecting abnormal cardiorespiratory patterns with a sensitivity of 95% and specificity of 92%. Prominent observations, which highlight the potential for early interventions include subtle changes in heart rate variability and preceding respiratory distress. These findings show the significance of wearable ECG technology in improving pandemic management strategies and informing public health policies, which enhances preparedness and resilience in the face of emerging health threats.

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Early detection of cardiorespiratory complications and training monitoring using wearable ECG sensors and CNN

Lu,

Feng,

Zhang

2024

BMC Med Inform Decis Mak

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Deep Learning Techniques Applied for Automatic Sentence Generation

Boopathi¹

2023

Advances in Educational Technologies and Instructional Design

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Automatic sentence generation is an important problem in natural language processing that has many applications, including language translation, summarization, and chatbots. Deep learning techniques, such as recurrent neural networks (RNNs) and transformer models, have been shown to be effective in generating coherent and diverse sentences. Recurrent neural networks (RNNs) have been widely used in natural language processing tasks, including automatic text generation. However, the traditional RNN suffers from the vanishing gradient problem, which hinders the learning of long-term dependencies. To address this issue, long short-term memory (LSTM) and gated recurrent unit (GRU) models have been introduced that can selectively forget or update certain information in the hidden state. These models have been shown to improve the quality of automatically generated text by better capturing the long-term dependencies in the input data.

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Sustainable Developments in Nano-Fluid Synthesis for Various Industrial Applications

Vijayakumar,

Domakonda,

Farooq

et al. 2023

Advances in Human and Social Aspects of Technology

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Nanofluids are a class of fluids that contain dispersed nanoparticles, offering unique properties and promising applications. This chapter explored different types of nanofluids and their synthesis methods, with the one-step method offering simplicity and efficiency, the two-step method providing precise control, the micro-emulsion method providing excellent stability, the sol-gel method providing well-defined nanoparticles, the chemical reduction method offering versatility, the laser ablation method offering high purity, the green synthesis method highlighting eco-friendliness, and the plasma-based method requiring sophisticated equipment.

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Social Health Protection During the COVID-Pandemic Using IoT

Cited by 82 publications

References 32 publications

Early detection of cardiorespiratory complications and training monitoring using wearable ECG sensors and CNN

Early detection of cardiorespiratory complications and training monitoring using wearable ECG sensors and CNN

Deep Learning Techniques Applied for Automatic Sentence Generation

Sustainable Developments in Nano-Fluid Synthesis for Various Industrial Applications

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