The internet of medical things and artificial intelligence: trends, challenges, and opportunities
High quality and efficient medical service is one of the major factors defining living
standards. Developed countries strive to make their healthcare systems as efficient and cost …
standards. Developed countries strive to make their healthcare systems as efficient and cost …
An overview of machine learning methods in enabling IoMT-based epileptic seizure detection
ALN Al-Hajjar, AKM Al-Qurabat - The Journal of Supercomputing, 2023 - Springer
The healthcare industry is rapidly automating, in large part because of the Internet of Things
(IoT). The sector of the IoT devoted to medical research is sometimes called the Internet of …
(IoT). The sector of the IoT devoted to medical research is sometimes called the Internet of …
[HTML][HTML] Insights into Internet of Medical Things (IoMT): Data fusion, security issues and potential solutions
Abstract The Internet of Medical Things (IoMT) has created a wide range of opportunities for
knowledge exchange in numerous industries. The opportunities include patient …
knowledge exchange in numerous industries. The opportunities include patient …
Removing artefacts and periodically retraining improve performance of neural network-based seizure prediction models
The development of seizure prediction models is often based on long-term scalp
electroencephalograms (EEGs) since they capture brain electrical activity, are non-invasive …
electroencephalograms (EEGs) since they capture brain electrical activity, are non-invasive …
Accuracy versus reliability-based modelling approaches for medical decision making
Forecasting in the medical domain is critical to the quality of decisions made by physicians,
patients, and health planners. Modeling is one of the most important components of decision …
patients, and health planners. Modeling is one of the most important components of decision …
Addressing data limitations in seizure prediction through transfer learning
According to the literature, seizure prediction models should be developed following a
patient-specific approach. However, seizures are usually very rare events, meaning the …
patient-specific approach. However, seizures are usually very rare events, meaning the …
IoMT-based seizure detection system leveraging edge machine learning
W Zhao, Y Wang, X Sun, S Zhang, X Li - IEEE Sensors Journal, 2023 - ieeexplore.ieee.org
As the fast growth of mHealth industry, seizure detection system (SDS) based on
electroencephalography (EEG) has become a research hotspot. Cloud-based approach for …
electroencephalography (EEG) has become a research hotspot. Cloud-based approach for …
Internet of Vehicles (IoV) based Framework for Vehicle Degradation using Multidimensional Dynamic Time Warping (MDTW)
The anomalies on highways impose wear-tear which may cause degradation in prolonging
of the vehicles. Although, past research has played an important role in detecting potholes …
of the vehicles. Although, past research has played an important role in detecting potholes …
Implementation of a non-linear SVM classification for seizure EEG signal analysis on FPGA
S Shanmugam, S Dharmar - Engineering Applications of Artificial …, 2024 - Elsevier
An automatic detection method for disease diagnosis plays an important role in the medical
field. A computer-aided diagnosis (CAD) system for seizure detection using …
field. A computer-aided diagnosis (CAD) system for seizure detection using …
Energy-efficient dynamic sensor time series classification for edge health devices
Y Wang, L Sun - Computer Methods and Programs in Biomedicine, 2024 - Elsevier
Abstract Background and Objective: Time series data plays a crucial role in the realm of the
Internet of Things Medical (IoMT). Through machine learning (ML) algorithms, online time …
Internet of Things Medical (IoMT). Through machine learning (ML) algorithms, online time …