Predictive models

Multiangle Correlation Feature Extraction and Disease Prediction Model Construction for Patients With Post-Stroke Dysarthria
Multiangle Correlation Feature Extraction and Disease Prediction Model Construction for Patients With Post-Stroke Dysarthria 150 150 Transactions on Neural Systems and Rehabilitation Engineering (TNSRE)
The clinical diagnosis and treatment of motor dysarthria in post-stroke patients is often subjective and neglects the impact of psychological and emotional disorders on disease progression. This study aims to… read more

Fall Risk Prediction Using Instrumented Footwear in Institutionalized Older Adults
Fall Risk Prediction Using Instrumented Footwear in Institutionalized Older Adults 150 150 Transactions on Neural Systems and Rehabilitation Engineering (TNSRE)
This study presents a novel framework that utilizes instrumented footwear to predict fall risk in institutionalized older adults by leveraging stride-to-stride gait data. The older adults are categorized into fallers… read more

Theory-Driven EEG Indexes for Tracking Motor Recovery and Predicting the Effects of Hybridizing tDCS With Mirror Therapy in Stroke Patients
Theory-Driven EEG Indexes for Tracking Motor Recovery and Predicting the Effects of Hybridizing tDCS With Mirror Therapy in Stroke Patients 150 150 Transactions on Neural Systems and Rehabilitation Engineering (TNSRE)
Stroke remains a leading cause of adult disability, underscoring why research continues to focus on advancing new treatment methods and neurophysiological indexes. While these studies may be effective, many lack… read more

Lower Limb Torque Prediction for Sit-To-Walk Strategies Using Long Short-Term Memory Neural Networks
Lower Limb Torque Prediction for Sit-To-Walk Strategies Using Long Short-Term Memory Neural Networks 150 150 Transactions on Neural Systems and Rehabilitation Engineering (TNSRE)
Joint torque prediction is crucial when investigating biomechanics, evaluating treatments, and designing powered assistive devices. Controllers in assistive technology require reference torque trajectories to set the level of assistance for… read more

Improved Transfer Learning for Detecting Upper-Limb Movement Intention Using Mechanical Sensors in an Exoskeletal Rehabilitation System
Improved Transfer Learning for Detecting Upper-Limb Movement Intention Using Mechanical Sensors in an Exoskeletal Rehabilitation System 150 150 Transactions on Neural Systems and Rehabilitation Engineering (TNSRE)
The objective of this study was to propose a novel strategy for detecting upper-limb motion intentions from mechanical sensor signals using deep and heterogeneous transfer learning techniques. Three sensor types,… read more

Prediction of rTMS Efficacy in Patients With Essential Tremor: Biomarkers From Individual Resting-State EEG Network
Prediction of rTMS Efficacy in Patients With Essential Tremor: Biomarkers From Individual Resting-State EEG Network 150 150 Transactions on Neural Systems and Rehabilitation Engineering (TNSRE)
The pathogenesis of essential tremor (ET) remains unclear, and the efficacy of related drug treatment is inadequate for proper tremor control. Hence, in the current study, consecutive low-frequency repetitive transcranial… read more

Recurrent Neural Network Enabled Continuous Motion Estimation of Lower Limb Joints From Incomplete sEMG Signals
Recurrent Neural Network Enabled Continuous Motion Estimation of Lower Limb Joints From Incomplete sEMG Signals 150 150 Transactions on Neural Systems and Rehabilitation Engineering (TNSRE)
Decoding continuous human motion from surface electromyography (sEMG) in advance is crucial for improving the intelligence of exoskeleton robots. However, incomplete sEMG signals are prevalent on account of unstable data… read more

MEFFNet: Forecasting Myoelectric Indices of Muscle Fatigue in Healthy and Post-Stroke During Voluntary and FES-Induced Dynamic Contractions
MEFFNet: Forecasting Myoelectric Indices of Muscle Fatigue in Healthy and Post-Stroke During Voluntary and FES-Induced Dynamic Contractions 150 150 Transactions on Neural Systems and Rehabilitation Engineering (TNSRE)
Myoelectric indices forecasting is important for muscle fatigue monitoring in wearable technologies, adaptive control of assistive devices like exoskeletons and prostheses, functional electrical stimulation (FES)-based Neuroprostheses, and more. Non-stationary temporal… read more

An Adaptive Hammerstein Model for FES-Induced Torque Prediction Based on Variable Forgetting Factor Recursive Least Squares Algorithm
An Adaptive Hammerstein Model for FES-Induced Torque Prediction Based on Variable Forgetting Factor Recursive Least Squares Algorithm 150 150 Transactions on Neural Systems and Rehabilitation Engineering (TNSRE)
Modeling the muscle response to functional electrical stimulation (FES) is an important step during model-based FES control system design. The Hammerstein structure is widely used in simulating this nonlinear biomechanical… read more
Bilevel Optimization for Cost Function Determination in Dynamic Simulation of Human Gait

Bilevel Optimization for Cost Function Determination in Dynamic Simulation of Human Gait
Author(s)3: Vinh Q. Nguyen, Russell T. Johnson, Frank C. Sup, Brian R. Umberger
Bilevel Optimization for Cost Function Determination in Dynamic Simulation of Human Gait 780 435 Transactions on Neural Systems and Rehabilitation Engineering (TNSRE)

      Predictive simulation based on dynamic optimization using musculoskeletal models is a powerful approach for studying human gait. Predictive musculoskeletal simulation may be used for a variety of applications…

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