Background: Depending on the level of lesion, spinal cord injury (SCI) individuals have limited ability to stand and walk. They have to use various assistive devices to restore their abilities. The aim of this study was to evaluate the stability of SCI individuals during walking and quiet standing.
Material And Methods: Three groups: normal subjects and SCI individuals with complete and incomplete lesions, were enrolled. Stability of the subjects was evaluated based on center of pressure (COP) sways in quiet standing and spatiotemporal gait parameters in walking. The difference between the stability of normal and SCI subjects was determined by use of the two-sample t test. The correlation between the mean values of stability parameters in standing and walking and lesion level was determined by use of Pearson's correlation.
Results: The stability of SCI subjects during quiet standing was better than that of normal subjects. How-ever, their dynamic stability was significantly less than normal subjects. The dynamic stability of complete and incomplete SCI subjects did not differ significantly (P-value<0.05). There was no correlation between lesion level and stability parameters.
Conclusions: 1. SCI individuals suffer mostly from lack of dynamic stability, which does not depend on their lesion levels. 2. It seems that this problem may be due to rehabilitation methods used to improve stability in these patients. 3. It is recommended that new methods of rehabilitation or assistive devices should be used to improve stability of these individuals.
Download full-text PDF |
Source |
|---|---|
| http://dx.doi.org/10.5604/01.3001.0014.0636 | DOI Listing |
Publication Analysis
Top Keywords
Similar Publications
Sub-5 nm Silicon Nanopore Sensors: Scalable Fabrication via Self-Limiting Metal-Assisted Chemical Etching.
ACS Appl Mater Interfaces
January 2025
Division of Micro and Nanosystems, KTH Royal Institute of Technology, Malvinas väg 10, Stockholm 100 44, Sweden.
Solid-state nanopores offer unique possibilities for biomolecule sensing; however, scalable production of sub-5 nm pores with precise diameter control remains a manufacturing challenge. In this work, we developed a scalable method to fabricate sub-5 nm nanopores in silicon (Si) nanomembranes through metal-assisted chemical etching (MACE) using gold nanoparticles. Notably, we present a previously unreported self-limiting effect that enables sub-5 nm nanopore formation from both 10 and 40 nm nanoparticles in the 12 nm thick monocrystalline device layer of a silicon-on-insulator substrate.
View Article and Find Full Text PDFA spiking neural network for active efficient coding.
Front Robot AI
January 2025
Life- and Neurosciences, Frankfurt Institute for Advanced Studies, Frankfurt am Main, Germany.
Biological vision systems simultaneously learn to efficiently encode their visual inputs and to control the movements of their eyes based on the visual input they sample. This autonomous joint learning of visual representations and actions has previously been modeled in the Active Efficient Coding (AEC) framework and implemented using traditional frame-based cameras. However, modern event-based cameras are inspired by the retina and offer advantages in terms of acquisition rate, dynamic range, and power consumption.
View Article and Find Full Text PDFDynamic nonlinear control strategies for resilient heterogeneous vehicle platooning and handling Byzantine attacks in communication networks.
Heliyon
January 2025
Department of Mathematics and Statistics, The University of Lahore, Sargodha 40100, Pakistan.
This paper addresses the challenges of maintaining stability in heterogeneous vehicle platooning under the influence of communication disruptions caused by Byzantine attacks within a leader-follower framework. To enhance resilience, we propose a nonlinear control strategy tailored for a third-order heterogeneous dynamic model, integrating leader-follower interconnections with adaptable control gains. Utilizing a constant time headway spacing policy with gap adjustments, we derive control gains that secure internal platoon stability.
View Article and Find Full Text PDFDeep reinforcement learning and robust SLAM based robotic control algorithm for self-driving path optimization.
Front Neurorobot
January 2025
School of Information and Communication Engineering, Hainan University, Haikou, China.
A reward shaping deep deterministic policy gradient (RS-DDPG) and simultaneous localization and mapping (SLAM) path tracking algorithm is proposed to address the issues of low accuracy and poor robustness of target path tracking for robotic control during maneuver. RS-DDPG algorithm is based on deep reinforcement learning (DRL) and designs a reward function to optimize the parameters of DDPG to achieve the required tracking accuracy and stability. A visual SLAM algorithm based on semantic segmentation and geometric information is proposed to address the issues of poor robustness and susceptibility to interference from dynamic objects in dynamic scenes for SLAM based on visual sensors.
View Article and Find Full Text PDFMajor change in swine influenza virus diversity in France owing to emergence and widespread dissemination of a newly introduced H1N2 1C genotype in 2020.
Virus Evol
December 2024
ANSES, Ploufragan-Plouzané-Niort Laboratory, Swine Virology Immunology Unit, National Reference Laboratory for Swine Influenza, BP53, Ploufragan 22440, France.
Swine influenza A viruses (swIAVs) are a major cause of respiratory disease in pigs worldwide, presenting significant economic and health risks. These viruses can reassort, creating new strains with varying pathogenicity and cross-species transmissibility. This study aimed to monitor the genetic and antigenic evolution of swIAV in France from 2019 to 2022.
View Article and Find Full Text PDFWant AI Summaries of new PubMed Abstracts delivered to your In-box?
Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!