A Deep Learning Approach for Automatic and Objective Grading of the Motor Impairment Severity in Parkinson's Disease for Use in Tele-Assessments

Keyphrases

• Deep Learning Methods 100%
• Parkinson's Disease 100%
• Automatic Grading 100%
• Motor Impairment 100%
• Objective Grading 100%
• E-assessment 100%
• Healthy Adults 66%
• Training Data 66%
• Motion Data 50%
• Unsupervised Pre-training 50%
• Classification Performance 33%
• Wearable Sensors 33%
• Unified Parkinson's Disease Rating Scale (UPDRS) 33%
• Deep Learning Model 33%
• Hand Movement 33%
• Movement Disorder Society 33%
• Toe Tapping 33%
• Lower Extremity 16%
• Neurological Conditions 16%
• Initialize 16%
• Finger Tapping 16%
• Deployable 16%
• Viable Solutions 16%
• Home Monitoring 16%
• Movement Task 16%
• Upper Extremity 16%
• Disease Data 16%
• Low-cost Wearable 16%
• Adult Training 16%
• Pronation-supination 16%
• Leg Agility 16%
• Telemedicine Solutions 16%

Computer Science

• Learning Approach 100%
• Parkinson's Disease 100%
• Motor Impairment 100%
• Deep Learning Method 100%
• Training Dataset 50%
• Classification Performance 33%
• Deep Learning Model 33%
• Rating Scale 33%
• Modified Version 16%
• Training Data 16%

Psychology

• Rating Scale 100%
• Learning Model 100%
• Movement Disorder 100%
• Telemedicine 50%