IEEE Neural Systems and Rehabilitation Engineering

Syndicate content
TOC Alert for Publication# 7333
Updated: 3 weeks 1 day ago

Automatic Musculoskeletal and Neurological Disorder Diagnosis With Relative Joint Displacement From Human Gait

Fri, 11/30/2018 - 23:00
Musculoskeletal and neurological disorders are common devastating companions of ageing, leading to a reduction in quality of life and increased mortality. Gait analysis is a popular method for diagnosing these disorders. However, manually analyzing the motion data is a labor-intensive task, and the quality of the results depends on the experience of the doctors. In this paper, we propose an automatic framework for classifying musculoskeletal and neurological disorders among older people based on 3D motion data. We also propose two new features to capture the relationship between joints across frames, known as 3D Relative Joint Displacement (3DRJDP) and 6D Symmetric Relative Joint Displacement (6DSymRJDP), such that the relative movement between joints can be analyzed. To optimize the classification performance, we adapt feature selection methods to choose an optimal feature set from the raw feature input. Experimental results show that we achieve a classification accuracy of 84.29% using the proposed relative joint features, outperforming existing features that focus on the movement of individual joints. Considering the limited open motion database for gait analysis focusing on such disorders, we construct a comprehensive, openly accessible 3D full-body motion database from 45 subjects.

Simple and Fast Compensation of sEMG Interface Rotation for Robust Hand Motion Recognition

Fri, 11/30/2018 - 23:00
Surface electromyography (sEMG) measurements have demonstrated the potential to recognize complex hand motions. In addition, sEMG enables natural recognition without disturbing movements, and thus, can be used in various fields such as teleoperation, assistant robots, and prosthetic hands. However, sEMG signals highly depend on electrode placements due to the complex muscle structures. A shift of the electrode can lead to inconsistent signal measurement. Thus, sEMG-based recognition is not practical for applications that require long-term and repeated usage. This paper proposes compensation of sEMG interface rotation for robust motion recognition. Once the relationship between sEMG signals and motions is trained, additional training for different electrode configurations is not necessary for a band-type interface. The proposed process is simple and fast. The interface rotation can be compensated for by performing only a single motion for approximately 2 s. The single motion for compensation is dependent on the muscle properties of the user. Generally, ulnar deviation may work. To demonstrate the proposed compensation, recognition of five hand motions is conducted. The experimental results indicate that the proposed compensation can cover the overall range of rotation. In addition, the proposed compensation is validated with a transradial amputee.

Unimanual Versus Bimanual Motor Imagery Classifiers for Assistive and Rehabilitative Brain Computer Interfaces

Fri, 11/30/2018 - 23:00
Bimanual movements are an integral part of everyday activities and are often included in rehabilitation therapies. Yet, electroencephalography (EEG)-based assistive and rehabilitative brain–computer interface (BCI) systems typically rely on motor imagination (MI) of one limb at the time. In this paper, we present a classifier which discriminates between uni-and bi-manual MI. Ten able-bodied participants took part in cue-based motor execution (ME) and MI tasks of the left (L), right (R) and both (B) hands. A 32-channel EEG was recorded. Three linear discriminant analysis classifiers, based on MI of L–B, B–R, and B–L hands were created, with features based on wide band common spatial patterns (CSP) 8–30 Hz, and band specifics common spatial patterns (CSPb). Event-related desynchronization (ERD) was significantly stronger during bimanual compared to unimanual ME on both hemispheres. Bimanual MI resulted in bilateral parietally shifted ERD of similar intensity to unimanual MI. The average classification accuracy for CSP and CSPb was comparable for the L–R task (73% ± 9% and 75% ± 10%, respectively) and for the L–B task (73% ± 11% and 70% ± 9%, respectively). However, for the R–B task (67% ± 3% and 72% ± 6%, respectively), it was significantly higher for CSPb ( $p = 0.0351$ ). Six participants whose L–R classification accuracy exceeded 70% were included in an online task a week - ater, using the unmodified offline CSPb classifier, achieving 69% ± 3% and 66% ± 3% accuracy for L–R and R–B tasks, respectively. Combined uni- and bi-manual BCI could be used for restoration of motor function of highly disabled patents and for motor rehabilitation of patients with motor deficits.

Brain Activation and Gait Alteration During Cognitive and Motor Dual Task Walking in Stroke—A Functional Near-Infrared Spectroscopy Study

Fri, 11/30/2018 - 23:00
This paper investigated the effects of cognitive and motor dual tasks on gait performance and brain activities in stroke; 23 stroke subjects performed single walking (SW), walking while performing cognitive task (WCT), and walking while performing motor task (WMT) at self-selected speed. The gait performance was recorded, including speed, cadence, stride time, stride length, and dual task cost (DTC). Brain activities in prefrontal cortex, premotor cortex (PMC), and supplementary motor areas (SMAs) were measured by functional near-infrared spectroscopy during walking. Results showed significant decrease in speed, cadence, and stride length, and increase in stride time was noted in both WCT and WMT compared with SW condition. There was no significant difference in DTC between WCT and WMT. The non-lesioned SMA and most channels of bilateral PMCs exhibited significant increases in the index of hemoglobin differential during WCT and WMT compared with SW. Moreover, gait performance was negatively correlated with bilateral PMCs and lesioned SMA during different walking tasks. In conclusion, deteriorated gait performance was noted in stroke attempting dual tasks. There is no significant difference between the two dual tasks on gait performance. Nevertheless, SMA and especially PMC were crucial in cognitive and motor dual task walking after stroke.

Correction for “Unbiased Estimation of Human Joint Intrinsic Mechanical Properties During Movement”

Fri, 11/30/2018 - 23:00
In [1], a typographical error occurred in the running head. The name Guarina should have appeared as Guarin.

IEEE Transactions on Neural Systems and Rehabilitation Engineering information for authors

Fri, 11/30/2018 - 23:00
These instructions give guidelines for preparing papers for this publication. Presents information for authors publishing in this journal.

HIVE is supported by the European Commission under the Future and Emerging Technologies program.

Syndicate content

Back to top