Application of artificial intelligence in wearable devices: Opportunities and challenges
D Nahavandi, R Alizadehsani, A Khosravi… - Computer Methods and …, 2022 - Elsevier
Background and objectives: Wearable technologies have added completely new and fast
emerging tools to the popular field of personal gadgets. Aside from being fashionable and …
emerging tools to the popular field of personal gadgets. Aside from being fashionable and …
Wearable devices for continuous monitoring of biosignals: Challenges and opportunities
The ability for wearable devices to collect high-fidelity biosignals continuously over weeks
and months at a time has become an increasingly sought-after characteristic to provide …
and months at a time has become an increasingly sought-after characteristic to provide …
Machine learning for detecting COVID-19 from cough sounds: An ensemble-based MCDM method
This research aims to analyze the performance of state-of-the-art machine learning
techniques for classifying COVID-19 from cough sounds and to identify the model (s) that …
techniques for classifying COVID-19 from cough sounds and to identify the model (s) that …
Automated lung sound classification using a hybrid CNN-LSTM network and focal loss function
Respiratory diseases constitute one of the leading causes of death worldwide and directly
affect the patient's quality of life. Early diagnosis and patient monitoring, which …
affect the patient's quality of life. Early diagnosis and patient monitoring, which …
Hardware implementation of deep network accelerators towards healthcare and biomedical applications
The advent of dedicated Deep Learning (DL) accelerators and neuromorphic processors
has brought on new opportunities for applying both Deep and Spiking Neural Network …
has brought on new opportunities for applying both Deep and Spiking Neural Network …
A lightweight CNN model for detecting respiratory diseases from lung auscultation sounds using EMD-CWT-based hybrid scalogram
Listening to lung sounds through auscultation is vital in examining the respiratory system for
abnormalities. Automated analysis of lung auscultation sounds can be beneficial to the …
abnormalities. Automated analysis of lung auscultation sounds can be beneficial to the …
Lung sound classification using co-tuning and stochastic normalization
T Nguyen, F Pernkopf - IEEE Transactions on Biomedical …, 2022 - ieeexplore.ieee.org
Computational methods for lung sound analysis are beneficial for computer-aided diagnosis
support, storage and monitoring in critical care. In this paper, we use pre-trained ResNet …
support, storage and monitoring in critical care. In this paper, we use pre-trained ResNet …
Respirenet: A deep neural network for accurately detecting abnormal lung sounds in limited data setting
Auscultation of respiratory sounds is the primary tool for screening and diagnosing lung
diseases. Automated analysis, coupled with digital stethoscopes, can play a crucial role in …
diseases. Automated analysis, coupled with digital stethoscopes, can play a crucial role in …
A review of wearable and unobtrusive sensing technologies for chronic disease management
With the rapidly increasing number of patients with chronic disease, numerous recent
studies have put great efforts into achieving long-term health monitoring and patient …
studies have put great efforts into achieving long-term health monitoring and patient …
Deep learning-based lung sound analysis for intelligent stethoscope
Auscultation is crucial for the diagnosis of respiratory system diseases. However, traditional
stethoscopes have inherent limitations, such as inter-listener variability and subjectivity, and …
stethoscopes have inherent limitations, such as inter-listener variability and subjectivity, and …