Artificial intelligence techniques for automated diagnosis of neurological disorders
Background: Authors have been advocating the research ideology that a computer-aided
diagnosis (CAD) system trained using lots of patient data and physiological signals and …
diagnosis (CAD) system trained using lots of patient data and physiological signals and …
A recent investigation on detection and classification of epileptic seizure techniques using EEG signal
The benefits of early detection and classification of epileptic seizures in analysis, monitoring
and diagnosis for the realization and actualization of computer-aided devices and recent …
and diagnosis for the realization and actualization of computer-aided devices and recent …
Machine learning approach to detect focal-onset seizures in the human anterior nucleus of the thalamus
Objective. There is an unmet need to develop seizure detection algorithms from brain
regions outside the epileptogenic cortex. The study aimed to demonstrate the feasibility of …
regions outside the epileptogenic cortex. The study aimed to demonstrate the feasibility of …
Epilnet: A novel approach to iot based epileptic seizure prediction and diagnosis system using artificial intelligence
Epilepsy is a long lasting neurological disease that affects 70 million globally. It is not a
newly discovered disease traced back to 4000 BC. The disease is not spread by direct …
newly discovered disease traced back to 4000 BC. The disease is not spread by direct …
Improving the security of the ieee 802.15. 6 standard for medical bans
A Medical Body Area Network (MBAN) is an ensemble of collaborating, potentially
heterogeneous, medical devices located inside, on the surface of or around the human body …
heterogeneous, medical devices located inside, on the surface of or around the human body …
Sensing and monitoring of epileptical seizure under IoT platform
AK Gupta, C Chakraborty, B Gupta - Smart medical data sensing and …, 2020 - igi-global.com
Epilepsy is a disorder that affects the life of the patient. In this neurological disorder, patients
may suffer from different types of seizures. From epileptic patients, we may acquire …
may suffer from different types of seizures. From epileptic patients, we may acquire …
Adversarial Transferability in Embedded Sensor Systems: An Activity Recognition Perspective
RK Sah, H Ghasemzadeh - ACM Transactions on Embedded Computing …, 2024 - dl.acm.org
Machine learning algorithms are increasingly used for inference and decision-making in
embedded systems. Data from sensors are used to train machine learning models for …
embedded systems. Data from sensors are used to train machine learning models for …
Adversarial transferability in wearable sensor systems
RK Sah, H Ghasemzadeh - arXiv preprint arXiv:2003.07982, 2020 - arxiv.org
Machine learning is used for inference and decision making in wearable sensor systems.
However, recent studies have found that machine learning algorithms are easily fooled by …
However, recent studies have found that machine learning algorithms are easily fooled by …
Seizure detection by integrating multiple sensors for enhanced monitoring with a mobile application to assist patients
MN Hammed - AIP Conference Proceedings, 2024 - pubs.aip.org
Epilepsy is a neurological condition that causes damage to the nervous system and causes
sudden seizures. This article covers a new prototype device that detects seizures using …
sudden seizures. This article covers a new prototype device that detects seizures using …
[HTML][HTML] Application of a Low-Cost mHealth Solution for the Remote Monitoring of Patients With Epilepsy: Algorithm Development and Validation
Background: Implementing automated seizure detection in long-term
electroencephalography (EEG) analysis enables the remote monitoring of patients with …
electroencephalography (EEG) analysis enables the remote monitoring of patients with …