Machine learning for the diagnosis of Parkinson's disease: a review of literature
Diagnosis of Parkinson's disease (PD) is commonly based on medical observations and
assessment of clinical signs, including the characterization of a variety of motor symptoms …
assessment of clinical signs, including the characterization of a variety of motor symptoms …
Machine learning in human movement biomechanics: Best practices, common pitfalls, and new opportunities
Traditional laboratory experiments, rehabilitation clinics, and wearable sensors offer
biomechanists a wealth of data on healthy and pathological movement. To harness the …
biomechanists a wealth of data on healthy and pathological movement. To harness the …
Early detection of Parkinson's disease using deep learning and machine learning
Accurately detecting Parkinson's disease (PD) at an early stage is certainly indispensable
for slowing down its progress and providing patients the possibility of accessing to disease …
for slowing down its progress and providing patients the possibility of accessing to disease …
Evaluation of handwriting kinematics and pressure for differential diagnosis of Parkinson's disease
Abstract Objective We present the PaHaW Parkinson's disease handwriting database,
consisting of handwriting samples from Parkinson's disease (PD) patients and healthy …
consisting of handwriting samples from Parkinson's disease (PD) patients and healthy …
Handwriting dynamics assessment using deep neural network for early identification of Parkinson's disease
The etiology of Parkinson's disease (PD) remains unclear. Symptoms usually appear after
approximately 70% of dopamine-producing cells have stopped working normally. PD cannot …
approximately 70% of dopamine-producing cells have stopped working normally. PD cannot …
Sequence-based dynamic handwriting analysis for Parkinson's disease detection with one-dimensional convolutions and BiGRUs
Parkinson's disease (PD) is commonly characterized by several motor symptoms, such as
bradykinesia, akinesia, rigidity, and tremor. The analysis of patients' fine motor control …
bradykinesia, akinesia, rigidity, and tremor. The analysis of patients' fine motor control …
Machine learning-based classification of simple drawing movements in Parkinson's disease
C Kotsavasiloglou, N Kostikis… - … Signal Processing and …, 2017 - Elsevier
This work explores the use of a pen-and-tablet device to study differences in hand
movement and muscle coordination between healthy subjects and Parkinson's disease …
movement and muscle coordination between healthy subjects and Parkinson's disease …
Handwritten dynamics assessment through convolutional neural networks: An application to Parkinson's disease identification
Background and objective Parkinson's disease (PD) is considered a degenerative disorder
that affects the motor system, which may cause tremors, micrography, and the freezing of …
that affects the motor system, which may cause tremors, micrography, and the freezing of …
Dysgraphia detection through machine learning
P Drotár, M Dobeš - Scientific reports, 2020 - nature.com
Dysgraphia, a disorder affecting the written expression of symbols and words, negatively
impacts the academic results of pupils as well as their overall well-being. The use of …
impacts the academic results of pupils as well as their overall well-being. The use of …
Dynamic handwriting analysis for the assessment of neurodegenerative diseases: a pattern recognition perspective
Neurodegenerative diseases, for instance Alzheimer's disease (AD) and Parkinson's
disease (PD), affect the peripheral nervous system, where nerve cells send messages that …
disease (PD), affect the peripheral nervous system, where nerve cells send messages that …