IEEE Transactions on Neural Systems and Rehabilitation Engineering

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• [Front cover]

Publication Year: 2017, Page(s): C1
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• IEEE Transactions on Neural Systems and Rehabilitation Engineering publication information

Publication Year: 2017, Page(s): C2
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Publication Year: 2017, Page(s):2215 - 2216
| PDF (175 KB)
• A Method for Removal of Deep Brain Stimulation Artifact From Local Field Potentials

Publication Year: 2017, Page(s):2217 - 2226
| | PDF (2220 KB)

This paper presents a signal processing method for the electrophysiology simultaneously recorded during deep brain stimulation (DBS) as a research tool. Regarding the local field potential (LFP) signals recorded during stimulation, a novel method was proposed for removal of stimulation artifacts caused by the much stronger stimulating pulse compared to typical LFP. This artifact suppression method... View full abstract»

• A 128-Channel FPGA-Based Real-Time Spike-Sorting Bidirectional Closed-Loop Neural Interface System

Publication Year: 2017, Page(s):2227 - 2238
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A multichannel neural interface system is an important tool for various types of neuroscientific studies. For the electrical interface with a biological system, high-precision high-speed data recording and various types of stimulation capability are required. In addition, real-time signal processing is an important feature in the implementation of a real-time closed-loop system without unwanted su... View full abstract»

• Is Implicit Motor Imagery a Reliable Strategy for a Brain–Computer Interface?

Publication Year: 2017, Page(s):2239 - 2248
| | PDF (1279 KB)

Explicit motor imagery (eMI) is a widely used brain-computer interface (BCI) paradigm, but not everybody can accomplish this task. Here, we propose a BCI based on implicit motor imagery (iMI). We compared classification accuracy between eMI and iMI of hands. Fifteen able-bodied people were asked to judge the laterality of hand images presented on a computer screen in a lateral or medial orientatio... View full abstract»

• TiD—Introducing and Benchmarking an Event-Delivery System for Brain–Computer Interfaces

Publication Year: 2017, Page(s):2249 - 2257
| | PDF (3333 KB) |  Media

In this paper, we present and analyze an event distribution system for brain–computer interfaces. Events are commonly used to mark and describe incidents during an experiment and are therefore critical for later data analysis or immediate real-time processing. The presented approach, called Tools for brain–computer interaction interface D (TiD), delivers messages in XML format via a ... View full abstract»

• Mixed-Modality Stimulation to Evoke Two Modalities Simultaneously in One Channel for Electrocutaneous Sensory Feedback

Publication Year: 2017, Page(s):2258 - 2269
| | PDF (1761 KB)

One of the long-standing challenges in upper limb prosthetics is restoring the sensory feedback that is missing due to amputation. Two approaches have previously been presented to provide various types of sensory information to users, namely, multi-modality sensory feedback and using an array of single-modality stimulators. However, the feedback systems used in these approaches were too bulky to b... View full abstract»

• Seizure Classification From EEG Signals Using Transfer Learning, Semi-Supervised Learning and TSK Fuzzy System

Publication Year: 2017, Page(s):2270 - 2284
Cited by:  Papers (1)
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Recognition of epileptic seizures from offline EEG signals is very important in clinical diagnosis of epilepsy. Compared with manual labeling of EEG signals by doctors, machine learning approaches can be faster and more consistent. However, the classification accuracy is usually not satisfactory for two main reasons: the distributions of the data used for training and testing may be different, and... View full abstract»

• Detection of Interictal Discharges With Convolutional Neural Networks Using Discrete Ordered Multichannel Intracranial EEG

Publication Year: 2017, Page(s):2285 - 2294
| | PDF (1652 KB)

Detection algorithms for electroencephalography (EEG) data, especially in the field of interictal epileptiform discharge (IED) detection, have traditionally employed handcrafted features, which utilized specific characteristics of neural responses. Although these algorithms achieve high accuracy, mere detection of an IED holds little clinical significance. In this paper, we consider deep learning ... View full abstract»

• Interacting With Robots to Investigate the Bases of Social Interaction

Publication Year: 2017, Page(s):2295 - 2304
| | PDF (717 KB)

Humans show a great natural ability at interacting with each other. Such efficiency in joint actions depends on a synergy between planned collaboration and emergent coordination, a subconscious mechanism based on a tight link between action execution and perception. This link supports phenomena as mutual adaptation, synchronization, and anticipation, which cut drastically the delays in the interac... View full abstract»

• Home-Based Therapy After Stroke Using the Hand Spring Operated Movement Enhancer (HandSOME)

Publication Year: 2017, Page(s):2305 - 2312
| | PDF (4295 KB)

In previous work, we developed a lightweight wearable hand exoskeleton (Hand Spring Operated Movement Enhancer) that improves range of motion and function in laboratory testing. In this pilot study, we added the ability to log movement data for extended periods and recruited ten chronic stroke subjects to use the device during reach and grasp task practice at home for 1.5 h/day, five days per week... View full abstract»

• A Control Scheme to Minimize Muscle Energy for Power Assistant Robotic Systems Under Unknown External Perturbation

Publication Year: 2017, Page(s):2313 - 2327
| | PDF (3630 KB)

This paper proposes a novel control method to minimize muscle energy for power-assistant robotic systems that support the intended motions of a user under unknown external perturbations, using surface electromyogram (sEMG) signals. Conventional control methods based on force/torque (F/T) sensors have limitations to detect human intentions and could, presumably, misunderstand or distort such intent... View full abstract»

• The Importance of Haptics in Generating Exoskeleton Gait Trajectory Using Alternate Motor Inputs

Publication Year: 2017, Page(s):2328 - 2335
| | PDF (1335 KB)

Human gait requires both haptic and visual feedback to generate and control rhythmic movements, and navigate environmental obstacles. Current lower extremity wearable exoskeletons that restore gait to individuals with paraplegia due to spinal cord injury rely completely on visual feedback to generate limited pre-programmed gait variations, and generally provide little control by the user over the ... View full abstract»

• An Automated Classification of Pathological Gait Using Unobtrusive Sensing Technology

Publication Year: 2017, Page(s):2336 - 2346
| | PDF (1713 KB)

This paper integrates an unobtrusive and affordable sensing technology with machine learning methods to discriminate between healthy and pathological gait patterns as a result of stroke or acquired brain injury. A feature analysis is used to identify the role of each body part in separating pathological patterns from healthy patterns. Gait features, including the orientations of the hips and spine... View full abstract»

• Feasibility and Validity of Discriminating Yaw Plane Head-on-Trunk Motion Using Inertial Wearable Sensors

Publication Year: 2017, Page(s):2347 - 2354
| | PDF (2178 KB)

A consequence of vestibular loss is increased coupling of head-on-trunk motion, particularly in the yaw plane, which adversely affects community mobility in these patients. Inertial sensors may provide a means of better understanding normal decoupling behaviors in community environments, but demonstration of their validity and responsiveness is needed. This paper examined the validity and measurem... View full abstract»

• Bio-Inspired Adaptive Control for Active Knee Exoprosthetics

Publication Year: 2017, Page(s):2355 - 2364
| | PDF (2900 KB)

On the quest to bring function of prosthetic legs closer to their biological counterparts, the intuitive interplay of their control with the user’s impedance modulation is key. We present two control features to enable more physiological and more user-adaptive control of prosthetic legs: a neuromusculoskeletal impedance model ( $NeurImp$ View full abstract»

• A Nonlinear Dynamics-Based Estimator for Functional Electrical Stimulation: Preliminary Results From Lower-Leg Extension Experiments

Publication Year: 2017, Page(s):2365 - 2374
| | PDF (1978 KB)

Miniature inertial measurement units (IMUs) are wearable sensors that measure limb segment or joint angles during dynamic movements. However, IMUs are generally prone to drift, external magnetic interference, and measurement noise. This paper presents a new class of nonlinear state estimation technique called state-dependent coefficient (SDC) estimation to accurately predict joint angles from IMU ... View full abstract»

• The VSPA Foot: A Quasi-Passive Ankle-Foot Prosthesis With Continuously Variable Stiffness

Publication Year: 2017, Page(s):2375 - 2386
| | PDF (3216 KB)

Most commercially available prosthetic feet do not exhibit a biomimetic torque-angle relationship, and are unable to modulate their mechanics to assist with other mobility tasks, such as stairs and ramps. In this paper, we present a quasi-passive ankle-foot prosthesis with a customizable torque-angle curve and an ability to quickly modulate ankle stiffness between tasks. The customizable torque-an... View full abstract»

• Knee Motion Generation Method for Transfemoral Prosthesis Based on Kinematic Synergy and Inertial Motion

Publication Year: 2017, Page(s):2387 - 2397
| | PDF (3133 KB)

Previous research has shown that the effective use of inertial motion (i.e., less or no torque input at the knee joint) plays an important role in achieving a smooth gait of transfemoral prostheses in the swing phase. In our previous research, a method for generating a timed knee trajectory close to able-bodied individuals, which leads to sufficient clearance between the foot and the floor and the... View full abstract»

• Compensation for Magnetic Disturbances in Motion Estimation to Provide Feedback to Wearable Robotic Systems

Publication Year: 2017, Page(s):2398 - 2406
| | PDF (1546 KB)

The direction of the Earth’s magnetic field is used as a reference vector to determine the heading in orientation estimation with wearable sensors. However, the magnetic field strength is weak and can be easily disturbed in the vicinity of ferromagnetic materials, which may result in inaccurate estimate of orientation. This paper presents a novel method for estimating and compensating for m... View full abstract»

• Grasp Performance of a Soft Synergy-Based Prosthetic Hand: A Pilot Study

Publication Year: 2017, Page(s):2407 - 2417
| | PDF (2177 KB) | HTML

Current prosthetic hands are frequently rejected in part due to limited functionality and versatility. We assessed the feasibility of a novel prosthetic hand, the SoftHand Pro (SHP), whose design combines soft robotics and hand postural synergies. Able-bodied subjects ( ${n} = {23}$ ) tracked cursor motion by opening and closin... View full abstract»

• Performance of Optimized Prosthetic Ankle Designs That Are Based on a Hydraulic Variable Displacement Actuator (VDA)

Publication Year: 2017, Page(s):2418 - 2426
| | PDF (1280 KB)

Current energy storage and return prosthetic feet only marginally reduce the cost of amputee locomotion compared with basic solid ankle cushioned heel feet, possibly due to their lack of push-off at the end of stance. To the best of our knowledge, a prosthetic ankle that utilizes a hydraulic variable displacement actuator (VDA) to improve push-off performance has not previously been proposed. Ther... View full abstract»

• Direction Modulation of Muscle Synergies in a Hand-Reaching Task

Publication Year: 2017, Page(s):2427 - 2440
| | PDF (3284 KB)

Functional tasks of the upper extremity can be executed by a variety of muscular patterns, independent of the direction, speed and load of the task. This large number of degrees of freedom imposes a significant control burden on the CNS. Previous studies suggested that the human cortex synchronizes a discrete number of neural functional units within the brainstem and spinal cord, i.e. muscle syner... View full abstract»

• Toward On-Demand Deep Brain Stimulation Using Online Parkinson’s Disease Prediction Driven by Dynamic Detection

Publication Year: 2017, Page(s):2441 - 2452
| | PDF (3180 KB)

In Parkinson’s disease (PD), on-demand deep brain stimulation is required so that stimulation is regulated to reduce side effects resulting from continuous stimulation and PD exacerbation due to untimely stimulation. Also, the progressive nature of PD necessitates the use of dynamic detection schemes that can track the nonlinearities in PD. This paper proposes the use of dynamic feature ext... View full abstract»

Aims & Scope

IEEE Transactions on Neural Systems and Rehabilitation Engineering focuses on the rehabilitative and neural aspects of biomedical engineering.

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Meet Our Editors

Editor-in-Chief
Paul Sajda
Columbia University