Lower body kinematics estimation from wearable sensors for walking and running: A deep learning approach
Abstract Background: Inertial measurement units (IMUs) are promising tools for collecting
human movement data. Model-based filtering approaches (eg Extended Kalman Filter) have …
human movement data. Model-based filtering approaches (eg Extended Kalman Filter) have …
A data-driven approach to predict fatigue in exercise based on motion data from wearable sensors or force plate
Fatigue increases the risk of injury during sports training and rehabilitation. Early detection
of fatigue during exercises would help adapt the training in order to prevent over-training …
of fatigue during exercises would help adapt the training in order to prevent over-training …
Model-based data augmentation for user-independent fatigue estimation
Objective User-independent recognition of exercise-induced fatigue from wearable motion
data is challenging, due to inter-participant variability. This study aims to develop algorithms …
data is challenging, due to inter-participant variability. This study aims to develop algorithms …
Enhancing biomechanical machine learning with limited data: generating realistic synthetic posture data using generative artificial intelligence
Objective: Biomechanical Machine Learning (ML) models, particularly deep-learning
models, demonstrate the best performance when trained using extensive datasets …
models, demonstrate the best performance when trained using extensive datasets …
[HTML][HTML] Data should be made as simple as possible but not simpler: The method chosen for dimensionality reduction and its parameters can affect the clustering of …
Dimensionality reduction is a critical step for the efficacy and efficiency of clustering analysis.
Despite the multiple available methods, biomechanists have often defaulted to Principal …
Despite the multiple available methods, biomechanists have often defaulted to Principal …
Adversarial autoencoder and multi-armed bandit for dynamic difficulty adjustment in immersive virtual reality for rehabilitation: Application to hand movement
Motor rehabilitation is used to improve motor control skills to improve the patient's quality of
life. Regular adjustments based on the effect of therapy are necessary, but this can be time …
life. Regular adjustments based on the effect of therapy are necessary, but this can be time …
[HTML][HTML] Latent Space Representation of Human Movement: Assessing the Effects of Fatigue
Fatigue plays a critical role in sports science, significantly affecting recovery, training
effectiveness, and overall athletic performance. Understanding and predicting fatigue is …
effectiveness, and overall athletic performance. Understanding and predicting fatigue is …
Latent Space Representation of Adversarial AutoEncoder for Human Activity Recognition: Application to a low-cost commercial force plate and inertial measurement …
Abstract Human Activity Recognition (HAR) is a key component of a home rehabilitation
system that provides real-time monitoring and personalized feedback. This research …
system that provides real-time monitoring and personalized feedback. This research …
Machine Learning in Biomechanics: Key Applications and Limitations in Walking, Running and Sports Movements
This chapter provides an overview of recent and promising Machine Learning applications,
ie pose estimation, feature estimation, event detection, data exploration and clustering and …
ie pose estimation, feature estimation, event detection, data exploration and clustering and …
Towards adaptive federated semi-supervised learning for visual recognition
M Wen - 2021 - spectrum.library.concordia.ca
Internet of Things (IoT) devices such as smart phones and wireless sensors have
proliferated in smart cities over the past few years. Various applications, including …
proliferated in smart cities over the past few years. Various applications, including …