Featured Articles

Speed adaptable prosthetic foot; concept description, prototyping and initial user testing
Author(s)3: Heimir Tryggvason, Felix Starker, Anna L. Armannsdottir, Christophe Lecomte, Fjola Jonsdottir
Speed adaptable prosthetic foot; concept description, prototyping and initial user testing 604 277 Transactions on Neural Systems and Rehabilitation Engineering (TNSRE)
This paper presents a novel design of a prosthetic foot that features adaptable stiffness that changes according to the speed of ankle motion. The motivation is the natural graduation in stiffness of a biological ankle over a range of ambulation tasks. read more

Deep Learning Architecture to Assist with Steering a Powered Wheelchair
Author(s)3: Malik J. Haddad, David A. Sanders
Deep Learning Architecture to Assist with Steering a Powered Wheelchair 582 322 Transactions on Neural Systems and Rehabilitation Engineering (TNSRE)
This paper describes a novel Deep Learning architecture to assist with steering a powered wheelchair. A rule-based approach is utilized to train and test a Long Short Term Memory (LSTM) Neural Network. It is the first time a LSTM has been used for steering a powered wheelchair. read more

Promoting Functional and Independent Sitting in Children with Cerebral Palsy Using the Robotic Trunk Support Trainer
Author(s)3: Victor Santamaria, Moiz Khan, Tatiana Luna, Jiyeon Kang, Joseph Dutkowsky, Andrew Gordon, Sunil Agrawal
Promoting Functional and Independent Sitting in Children with Cerebral Palsy Using the Robotic Trunk Support Trainer 515 334 Transactions on Neural Systems and Rehabilitation Engineering (TNSRE)
Seated postural abilities are critical to functional independence and participation in children with cerebral palsy, Gross Motor Functional Classification System (GMFCS) levels III-IV. In this proof-of-concept study, we investigated the feasibility of a motor learning–based seated postural training with a robotic Trunk-Support-Trainer (TruST) in a longitudinal single-subject-design (13y, GMFCS IV), and its potential effectiveness in a group of 3 children (6-14y, GMFCS III-IV). read more

Two-Dimensional Stockwell Transform and Deep Convolutional Neural Network for Multi-Class Diagnosis of Pathological Brain
Author(s)3: Mohsen Soleimani, Aram Vahidi, Behrouz Vaseghi
Two-Dimensional Stockwell Transform and Deep Convolutional Neural Network for Multi-Class Diagnosis of Pathological Brain 983 415 Transactions on Neural Systems and Rehabilitation Engineering (TNSRE)
Since brain lesion detection and classification is a vital diagnosis task, in this paper, the problem of brain magnetic resonance imaging (MRI) classification is investigated. read more

12 Degrees of Freedom Muscle Force Driven Fibril-Reinforced Poroviscoelastic Finite Element Model of the Knee Joint
Author(s)3: A. Esrafilian, L. Stenroth, M. E. Mononen, P. Tanska, S. V. Rossom, D. G. Lloyd, I. Jonkers, R. K. Korhonen
12 Degrees of Freedom Muscle Force Driven Fibril-Reinforced Poroviscoelastic Finite Element Model of the Knee Joint 495 630 Transactions on Neural Systems and Rehabilitation Engineering (TNSRE)
Accurate knowledge of the joint kinematics, kinetics, and soft tissue mechanical responses is essential in the evaluation of musculoskeletal (MS) disorders. read more

Plantar or Palmar Tactile Augmentation Improves Lateral Postural Balance with Significant Influence from Cognitive Load
Author(s)3: Jacob Azbell, Jaekwan K. Park, Shuo-Hsiu Chang, Mariklle PKJ Engelen, Hangue Park
Plantar or Palmar Tactile Augmentation Improves Lateral Postural Balance with Significant Influence from Cognitive Load 550 371 Transactions on Neural Systems and Rehabilitation Engineering (TNSRE)
Although it seems intuitive to address the issue of reduced plantar cutaneous feedback by augmenting it, many approaches have adopted compensatory sensory cues, such as tactile input from another part of the body, for multiple reasons including easiness and accessibility. read more

Adaptive Electrode Calibration Method based on Muscle Core Activation Regions and Its Application in Myoelectric Pattern Recognition
Author(s)3: Ruochen Hu, Xiang Chen, Xu Zhang, Xun Chen
Adaptive Electrode Calibration Method based on Muscle Core Activation Regions and Its Application in Myoelectric Pattern Recognition 471 356 Transactions on Neural Systems and Rehabilitation Engineering (TNSRE)
To reduce the bad effect of electrode shifts on myoelectric pattern recognition, this paper presents an adaptive electrode calibration method based on core activation regions of muscles. read more

Improving the Intelligibility of Speech for Simulated Electric and Acoustic Stimulation Using Fully Convolutional Neural Networks
Author(s)3: Natalie Yu-Hsien Wang, Hsiao-Lan Sharon Wang, Tao-Wei Wang, Szu-Wei Fu, Xugan Lu, Hsin-Min Wang, Yu Tsao
Improving the Intelligibility of Speech for Simulated Electric and Acoustic Stimulation Using Fully Convolutional Neural Networks 1019 367 Transactions on Neural Systems and Rehabilitation Engineering (TNSRE)
Combined electric and acoustic stimulation (EAS) has demonstrated better speech recognition than conventional cochlear implant (CI) and yielded satisfactory performance under quiet conditions. However, when noise signals are involved, both the electric signal and the acoustic signal may be distorted, thereby resulting in poor recognition performance. read more

Multi-directional Ankle Impedance During Standing Postures
Author(s)3: Guilherme A. Ribeiro, Lauren N. Knop, Mo Rastgaar
Multi-directional Ankle Impedance During Standing Postures 592 1000 Transactions on Neural Systems and Rehabilitation Engineering (TNSRE)
In this study, we estimated the multi-directional ankle mechanical impedance in two degrees-of-freedom (DOF) during standing, and determined how the stiffness, damping, and inertia vary with ankle angle and ankle torque at different postures. read more

Inter-and Intra-Subject Transfer Reduces Calibration Effort for High-Speed SSVEP-based BCIs
Author(s)3: Chi Man Wong, Ze Wang, Boyu Wang, Ka Fai Lao, Agostinho Rosa, Peng Xu, Tzyy-Ping Jung, C. L. Philip Chen, Feng Wan
Inter-and Intra-Subject Transfer Reduces Calibration Effort for High-Speed SSVEP-based BCIs 1000 920 Transactions on Neural Systems and Rehabilitation Engineering (TNSRE)
Steady-state visual evoked potential (SSVEP)-based brain-computer interfaces (BCIs) that can deliver high information transfer rate (ITR) usually require subject’s calibration data to learn the class-and subject-specific model parameters (e.g. the spatial filters and SSVEP templates). Normally, the amount of the calibration data for learning is proportional to the number of classes (or visual stimuli), which could be huge and consequently lead to a time-consuming calibration. read more

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TNSRE serves the community of biomedical engineers and clinical researchers who work at the intersection of neuroscience and physical medicine. We publish novel approaches and technologies for better understanding neural systems, human movement, and the relationships between them, with a focus on assistive devices that improve life for patients, for practicing clinicians, and for everyday use.

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