Detection of Fall Risk in Multiple Sclerosis by Gait Analysis-An Innovative Approach Using Feature Selection Ensemble and Machine Learning Algorithms
Publication Year: 2022 / Journal: Brain Sciences
Machine Learning
Comparison of Machine Learning approaches for Classifying Upper Extremity Tasks in Individuals Post-Stroke
Publication Year: 2020 / Journal: IEEE
Transparent Quality Optimization for Machine Learning-Based Regression in Neurology
Publication Year: 2022 / Journal: Journal of Personalized Medicine
Positive impact of short-term gait rehabilitation in Parkinson patients: a combined approach based on statistics and machine learning
Publication Year: 2021 / Journal: Mathematical Biosciences and Engineering
Automated detection of multidirectional compensatory balance reactions: a step towards tracking naturally-occurring near-falls
Publication Year: 2019 / Journal: IEEE
Human Motion Identification for Rehabilitation Exercise Assessment of Knee Osteoarthritis
Publication Year: 2017 / Journal: IEEE
Use of Wearable Sensors and Machine Learning Methods in Promoting Total Joint Replacement Treatment Outcomes: A Survey
Publication Year: 2020 / Journal: Proceedings of the 2020 HFES 64th International Annual Meeting
An Analysis of Segmentation Approaches and Window Sizes in Wearable-based Critical Fall Detection Systems with Machine Learning Models
Publication Year: 2019 / Journal: IEEE
Decomposition of Reaching Movements Enables Detection and Measurement of Ataxia
Publication Year: 2021 / Journal: The Cerebellum
Prediction of individual progression rate in Parkinson’s disease using clinical measures and biomechanical measures of gait and postural stability
Publication Year: 2020 / Journal: IEEE