Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
40040017
The digital health industry's interest in gait analysis has driven research into sensor-enabled insoles for practical, everyday gait monitoring. Traditional methods, such as 3D motion capture systems, are costly and time-consuming. To address this, w...
Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
40039724
Home-based rehabilitation is a trend of post-stroke lower limb rehabilitation, aimed at a long-term and higher dose of therapy. Unsupervised gait assessments can help therapists to track patients' recovery progress and timely adjust rehabilitation in...
Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
40039710
Gait can be significantly impaired by neurological conditions such as Parkinson's disease (PD). Gait impairments can be quantified by using instrumented gait analysis techniques, but these instrumented techniques are expensive and suffer from limited...
Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
40039130
This study introduces a machine learning-based methodology for classifying healthy individuals and those with gait disorders, employing a merged data set from 'GaitRec' and 'Gutenberg.' Key gait features were extracted from the normalized ground reac...
Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
40039054
In this study, we propose a novel deep learning-based framework for automatic gait event detection (GED) in diverse and complex walking scenarios, aiming to address the challenge of accurately identifying biomechanical markers linked to movement diso...
Several studies have highlighted the advantages of employing artificial intelligence (AI) models in gait analysis. However, the credibility and practicality of integrating these models into clinical gait routines remain uncertain. This study critical...
Gait abnormality detection is a growing application in machine learning based health assessment due to its potential in domains from clinical health reviews to at home health monitoring. This latter application is of particular use for older adults, ...
Studies in health technology and informatics
40270402
BACKGROUND: Hip osteoarthritis (OA) is a degenerative joint disease that affects approximately 25% of individuals over their lifetime, with prevalence expected to rise due to population aging. Gait analysis is recognized as a valuable tool for unders...
The gait analysis has been applied in many fields, such as the assessment of falling, force evaluation in sports, and gait disorder detection for neuromuscular diseases. Its main recording techniques include video cameras and wearable sensors. Howeve...
BMC medical informatics and decision making
40170023
BACKGROUND: Cognitive impairment is common after a stroke, but it can often go undetected. In this study, we investigated whether using gait and dual tasks could help detect cognitive impairment after stroke.