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Bicycling

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Perceptions of vulnerable roadway users on autonomous vehicle regulations.

Journal of safety research
INTRODUCTION: Development and implementation of autonomous vehicle (AV) related regulations are necessary to ensure safe AV deployment and wide acceptance among all roadway users. Assessment of vulnerable roadway users' perceptions on AV regulations ...

SE-MAConvLSTM: A deep learning framework for short-term traffic flow prediction combining Squeeze-and-Excitation Network and Multi-Attention Convolutional LSTM Network.

PloS one
Traffic flow prediction is an important part of transportation management and planning. For example, accurate demand prediction of taxis and online car-hailing can reduce the waste of resources caused by empty cars. The prediction of public bicycle f...

Machine learning prediction of pulmonary oxygen uptake from muscle oxygen in cycling.

Journal of sports sciences
The purpose of this study was to test whether a machine learning model can accurately predict VO across different exercise intensities by combining muscle oxygen (MO) with heart rate (HR). Twenty young highly trained athletes performed the following ...

Decoding lower-limb kinematic parameters during pedaling tasks using deep learning approaches and EEG.

Medical & biological engineering & computing
Stroke is a neurological condition that usually results in the loss of voluntary control of body movements, making it difficult for individuals to perform activities of daily living (ADLs). Brain-computer interfaces (BCIs) integrated into robotic sys...

Optimizing vehicle Front-End structure for e-bike rider Safety: An advanced Multi-Objective approach using injury prediction models.

Accident; analysis and prevention
A multi-objective optimization method based on an injury prediction model is proposed to address the increasingly prominent safety issues for e-bike riders in Chinese road traffic. This method aims to enhance the protective effect of vehicle front-en...

Kinematics-Based Predictions of External Loads during Handcycling.

Sensors (Basel, Switzerland)
The increased risk of cardiovascular disease in people with spinal cord injuries motivates work to identify exercise options that improve health outcomes without causing risk of musculoskeletal injury. Handcycling is an exercise mode that may be bene...

A hybrid approach for modeling bicycle crash frequencies: Integrating random forest based SHAP model with random parameter negative binomial regression model.

Accident; analysis and prevention
To effectively capture and explain complex, nonlinear relationships within bicycle crash frequency data and account for unobserved heterogeneity simultaneously, this study proposes a new hybrid framework that combines the Random Forest-based SHapley ...

What factors influence the willingness and intensity of regular mobile physical activity?- A machine learning analysis based on a sample of 290 cities in China.

Frontiers in public health
INTRODUCTION: This study, based on Volunteered Geographic Information (VGI) and multi-source data, aims to construct an interpretable macro-scale analytical framework to explore the factors influencing urban physical activities. Using 290 prefecture-...

A novel method for assessing cycling movement status: an exploratory study integrating deep learning and signal processing technologies.

BMC medical informatics and decision making
This study proposes a deep learning-based motion assessment method that integrates the pose estimation algorithm (Keypoint RCNN) with signal processing techniques, demonstrating its reliability and effectiveness.The reliability and validity of this m...

Validity of recurrent neural networks to predict pedal forces and lower limb kinetics in cycling.

Journal of biomechanics
Dynamic variables contribute to understand the mechanics of pedalling and can assist with injury prevention. Measuring pedal forces and joint moments and powers has a high cost, which can be mitigated by using trained artificial neural networks (ANN)...