Revolutionizing the early detection of Alzheimer's disease through non-invasive biomarkers: the role of artificial intelligence and deep learning

AG Vrahatis, K Skolariki, MG Krokidis, K Lazaros… - Sensors, 2023 - mdpi.com
Alzheimer's disease (AD) is now classified as a silent pandemic due to concerning current
statistics and future predictions. Despite this, no effective treatment or accurate diagnosis …

A Comprehensive review on AI-enabled models for Parkinson's disease diagnosis

S Dixit, K Bohre, Y Singh, Y Himeur, W Mansoor… - Electronics, 2023 - mdpi.com
Parkinson's disease (PD) is a devastating neurological disease that cannot be identified with
traditional plasma experiments, necessitating the development of a faster, less expensive …

Detection and classification of early stages of Parkinson's disease through wearable sensors and machine learning

A Shcherbak, E Kovalenko… - IEEE Transactions on …, 2023 - ieeexplore.ieee.org
Parkinson's disease (PD) is a neurodegenerative disease which is among the most spread
and growing common neurodegenerative disorders. It significantly limits the physical and …

Machine-learning-based predictions of imprinting quality using ensemble and non-linear regression algorithms

B Yarahmadi, SM Hashemianzadeh… - Scientific Reports, 2023 - nature.com
The molecularly imprinted polymers are artificial polymers that, during the synthesis, create
specific sites for a definite purpose. These polymers due to their characteristics such as …

Non-Invasive Biosensing for Healthcare Using Artificial Intelligence: A Semi-Systematic Review

T Islam, P Washington - Biosensors, 2024 - mdpi.com
The rapid development of biosensing technologies together with the advent of deep learning
has marked an era in healthcare and biomedical research where widespread devices like …

Feasibility of electrodermal activity and photoplethysmography data acquisition at the foot using a sock form factor

AF Ferreira, HP da Silva, H Alves, N Marques, A Fred - Sensors, 2023 - mdpi.com
Wearable devices have been shown to play an important role in disease prevention and
health management, through the multimodal acquisition of peripheral biosignals. However …

Exploring the application and challenges of fNIRS technology in early detection of Parkinson's disease

P Hui, Y Jiang, J Wang, C Wang, Y Li… - Frontiers in Aging …, 2024 - frontiersin.org
Background Parkinson's disease (PD) is a prevalent neurodegenerative disorder that
significantly benefits from early diagnosis for effective disease management and …

Challenges and Opportunities of Activity Recognition in Clinical Pathways

C Garcia, S Inoue - Human Activity and Behavior Analysis, 2024 - taylorfrancis.com
In this paper, we survey the activities in various clinical pathways and identified that there is
a large area of activities, medical professionals, and diseases affecting movement to be …

[HTML][HTML] Benchmarking of Sensor Configurations and Measurement Sites for Out-of-the-Lab Photoplethysmography

MN Supelnic, AF Ferreira, PJ Bota, L Brás-Rosário… - Sensors, 2023 - mdpi.com
Photoplethysmography (PPG) is used for heart-rate monitoring in a variety of contexts and
applications due to its versatility and simplicity. These applications, namely studies involving …

Investigation of Phase Shifts Using AUC Diagrams: Application to Differential Diagnosis of Parkinson's Disease and Essential Tremor

OS Sushkova, AA Morozov, IA Kershner… - Sensors, 2023 - mdpi.com
This study was motivated by the well-known problem of the differential diagnosis of
Parkinson's disease and essential tremor using the phase shift between the tremor signals …