Automated methods for diagnosis of Parkinson's disease and predicting severity level

Z Ayaz, S Naz, NH Khan, I Razzak, M Imran - Neural Computing and …, 2023 - Springer
The recent advancements in information technology and bioinformatics have led to
exceptional contributions in medical sciences. Extensive developments have been recorded …

Detection and prediction of freezing of gait with wearable sensors in Parkinson's disease

W Zhang, H Sun, D Huang, Z Zhang, J Li, C Wu… - Neurological …, 2024 - Springer
Freezing of gait (FoG) is one of the most distressing symptoms of Parkinson's Disease (PD),
commonly occurring in patients at middle and late stages of the disease. Automatic and …

Measuring freezing of gait during daily-life: an open-source, wearable sensors approach

M Mancini, VV Shah, S Stuart, C Curtze… - … of neuroengineering and …, 2021 - Springer
Background Although a growing number of studies focus on the measurement and detection
of freezing of gait (FoG) in laboratory settings, only a few studies have attempted to measure …

A survey of deep learning techniques based Parkinson's disease recognition methods employing clinical data

A ul Haq, JP Li, BLY Agbley, CB Mawuli, Z Ali… - Expert Systems with …, 2022 - Elsevier
Parkinson's disease (PD) is a critical neurological ailment that affects millions of individuals
worldwide. A correct diagnosis of Parkinson's disease is required for effective treatment …

Prediction and detection of freezing of gait in Parkinson's disease from plantar pressure data using long short-term memory neural-networks

G Shalin, S Pardoel, ED Lemaire, J Nantel… - … of neuroengineering and …, 2021 - Springer
Background Freezing of gait (FOG) is a walking disturbance in advanced stage Parkinson's
disease (PD) that has been associated with increased fall risk and decreased quality of life …

[HTML][HTML] WiFOG: Integrating deep learning and hybrid feature selection for accurate freezing of gait detection

Z Habib, MA Mughal, MA Khan, M Shabaz - Alexandria Engineering …, 2024 - Elsevier
This study investigates the feasibility of utilizing non-invasive WiFi sensing using the 4.8
GHz operating frequency band of the 5 G spectrum, which is suitable for Internet of Things …

Machine learning algorithms based on signals from a single wearable inertial sensor can detect surface-and age-related differences in walking

B Hu, PC Dixon, JV Jacobs, JT Dennerlein… - Journal of …, 2018 - Elsevier
The aim of this study was to investigate if a machine learning algorithm utilizing triaxial
accelerometer, gyroscope, and magnetometer data from an inertial motion unit (IMU) could …

Machine learning for neurodegenerative disorder diagnosis—survey of practices and launch of benchmark dataset

A Tagaris, D Kollias, A Stafylopatis… - … Journal on Artificial …, 2018 - World Scientific
Neurodegenerative disorders, such as Alzheimer's and Parkinson's, constitute a major factor
in long-term disability and are becoming more and more a serious concern in developed …

The classification of minor gait alterations using wearable sensors and deep learning

A Turner, S Hayes - IEEE Transactions on Biomedical …, 2019 - ieeexplore.ieee.org
Objective: This paper describes how non-invasive wearable sensors can be used in
combination with deep learning to classify artificially induced gait alterations without the …

Early detection of Parkinson disease using deep neural networks on gait dynamics

L Aversano, ML Bernardi, M Cimitile… - 2020 International Joint …, 2020 - ieeexplore.ieee.org
Parkinson's disease is a degenerative movement disorder causing considerable disability.
However, the early detection of this syndrome and of its progression rates may be decisive …