Publications by authors named "Annemarie F Laudanski"
Article Synopsis
- The development of human-robot interaction in robotic gait assistance relies on understanding individual human motion to personalize support.* -
- Traditional gait analysis methods are limited by their inability to account for individual differences, prompting a shift towards using regression models and Artificial Neural Networks (ANN) for better gait pattern generation.* -
- This article presents a new approach that enhances gait assistance by incorporating three-dimensional spatial predictions, resulting in high accuracy metrics that promise improved rehabilitation outcomes for users.*
High knee flexion postures, despite their association with increased incidences of osteoarthritis, are frequently adopted in occupational childcare. This study sought to define and quantify high flexion postures typically adopted in childcare to evaluate any increased likelihood of knee osteoarthritis development. Through video analysis of eighteen childcare workers caring for infant, toddler, and preschool-aged children, eight high knee flexion postures were identified and quantified by duration and frequency.
View Article and Find Full Text PDFBackground: High knee flexion postures are often adopted in occupational settings and may lead to increased risk of knee osteoarthritis. Pattern recognition algorithms using wireless electromyographic (EMG) signals may be capable of detecting and quantifying occupational exposures throughout a working day.
Objective: To develop a k-Nearest Neighbor (kNN) algorithm for the classification of eight high knee flexion activities frequently observed in childcare.