The prediction of sensor data can help the exoskeleton control system to get the human motion intention and target position in advance, so as to reduce the human-machine interaction force. In this paper, an improved method for the prediction algorithm of exoskeleton sensor data is proposed. Through an algorithm simulation test and two-link simulation experiment, the algorithm improves the prediction accuracy by 14.23 ± 0.5%, and the sensor data is smooth. Input the predicted signal into the two-link model, and use the calculated torque method to verify the prediction accuracy data and smoothness. The simulation results showed that the algorithm can predict the joint angle of the human body and can be used for the follow-up control of the swinging legs of the exoskeleton.
Download full-text PDF |
Source |
|---|---|
| http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7843196 | PMC |
| http://dx.doi.org/10.1155/2021/8850348 | DOI Listing |
Publication Analysis
Top Keywords
Similar Publications
Internet of Things (IoT) is one of the most important emerging technologies that supports Metaverse integrating process, by enabling smooth data transfer among physical and virtual domains. Integrating sensor devices, wearables, and smart gadgets into Metaverse environment enables IoT to deepen interactions and enhance immersion, both crucial for a completely integrated, data-driven Metaverse. Nevertheless, because IoT devices are often built with minimal hardware and are connected to the Internet, they are highly susceptible to different types of cyberattacks, presenting a significant security problem for maintaining a secure infrastructure.
View Article and Find Full Text PDFA structural health monitoring data reconstruction method based on VMD and SSA-optimized GRU model.
Sci Rep
January 2025
School of Civil Engineering, Qingdao University of Technology, Qingdao, 266525, China.
In the field of Structural Health Monitoring (SHM), complete datasets are fundamental for modal identification analysis and risk prediction. However, data loss due to sensor failures, transmission interruptions, or hardware issues is a common problem. To address this challenge, this study develops a method combining Variational Mode Decomposition (VMD) and Sparrow Search Algorithm (SSA)-optimized Gate Recurrent Unit (GRU) for recovering structural response data.
View Article and Find Full Text PDFDigital Home-Based Self-Monitoring System for People with Heart Failure: Protocol for Development of SmartHeart and Evaluation of Feasibility and Acceptability.
JMIR Res Protoc
January 2025
School of Exercise and Nutrition Sciences, Institute for Physical Activity and Nutrition, Deakin University, Burwood, Australia.
Background: Heart failure (HF) is a chronic, progressive condition where the heart cannot pump enough blood to meet the body's needs. In addition to the daily challenges that HF poses, acute exacerbations can lead to costly hospitalizations and increased mortality. High health care costs and the burden of HF have led to the emerging application of new technologies to support people living with HF to stay well while living in the community.
View Article and Find Full Text PDFUse of Augmented Reality for Training Assistance in Laparoscopic Surgery: Scoping Literature Review.
J Med Internet Res
January 2025
I3A, LoUISE Research Group, University of Castilla-La Mancha, Albacete, Spain.
Background: Laparoscopic surgery training is a demanding process requiring technical and nontechnical skills. Surgical training has evolved from traditional approaches to the use of immersive digital technologies such as virtual, augmented, and mixed reality. These technologies are now integral to laparoscopic surgery training.
View Article and Find Full Text PDFComparative analysis of spinal flexion angles during smartphone use in toilet: a randomized cross-over with three-period study.
Acta Bioeng Biomech
June 2024
1Department of Rehabilitation Medicine, Southern Medical University Nanfang Hospital, Guangzhou, China.
: The purpose of this study was to quantify the impact of smartphone use while sitting on the toilet on the spinal flexion angles and the time effect. : Measurements of the spinal flexion angles in the sagittal plane were made by thirty participants while they sat on the toilet for 10 min, using a smartphone in either one, both, or neither hand. The individual's forehead, cervical, thoracic and lumbar spinal areas were each fitted with five different inertial motion sensors.
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!