AIMC Topic: Bicycling

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

Medical & biological engineering & computing Jul 19, 2024
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...
Male Deep Learning Adult Biomechanical Phenomena Humans Neural Networks, Computer Signal Processing, Computer-Assisted Female Brain-Computer Interfaces Young Adult Bicycling Algorithms Lower Extremity Electroencephalography
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Comparing the advantages and disadvantages of physics-based and neural network-based modelling for predicting cycling power.

Journal of biomechanics May 7, 2024
Models of physical phenomena can be developed using two distinct approaches: using expert knowledge of the underlying physical principles or using experimental data to train a neural network. Here, our aim was to better understand the advantages and ...
Female Young Adult Adult Humans Neural Networks, Computer Models, Biological Bicycling Biomechanical Phenomena Male
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Perceptions of vulnerable roadway users on autonomous vehicle regulations.

Journal of safety research Feb 23, 2024
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 ...
Adult Walking Perception Aged Humans Male Pedestrians Bicycling Young Adult Adolescent Middle Aged Female Accidents, Traffic Automobiles Surveys and Questionnaires Safety
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Forward dynamics computational modelling of a cyclist fall with the inclusion of protective response using deep learning-based human pose estimation.

Journal of biomechanics Jan 19, 2024
Single bicycle crashes, i.e., falls and impacts not involving a collision with another road user, are a significantly underestimated road safety problem. The motions and behaviours of falling people, or fall kinematics, are often investigated in the ...
Motion Bicycling Deep Learning Accidents, Traffic Humans Computer Simulation
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Automated classification of time-activity-location patterns for improved estimation of personal exposure to air pollution.

Environmental health : a global access science source Dec 9, 2022
BACKGROUND: Air pollution epidemiology has primarily relied on measurements from fixed outdoor air quality monitoring stations to derive population-scale exposure. Characterisation of individual time-activity-location patterns is critical for accurat...
Air Pollution Bicycling Humans Artificial Intelligence
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Cadence Detection in Road Cycling Using Saddle Tube Motion and Machine Learning.

Sensors (Basel, Switzerland) Aug 17, 2022
Most commercial cadence-measurement systems in road cycling are strictly limited in their function to the measurement of cadence. Other relevant signals, such as roll angle, inclination or a round kick evaluation, cannot be measured with them. This w...
Motion Bicycling Machine Learning
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Green Recycling Supplier Selection of Shared Bicycles: Interval-Valued Pythagorean Fuzzy Hybrid Weighted Methods Based on Self-Confidence Level.

International journal of environmental research and public health Apr 20, 2022
In the face of practical problems such as the increasing demand for shared bicycles and the number of faulty vehicles which are hard to handle and repair in time, shared bicycles operators tend to outsource recycling services to suppliers. To solve t...
Fuzzy Logic Bicycling Decision Making
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Bike-Sharing Demand Prediction at Community Level under COVID-19 Using Deep Learning.

Sensors (Basel, Switzerland) Jan 29, 2022
An important question in planning and designing bike-sharing services is to support the user's travel demand by allocating bikes at the stations in an efficient and reliable manner which may require accurate short-time demand prediction. This study f...
COVID-19 SARS-CoV-2 Bicycling Deep Learning Humans Pandemics
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Smart Electrically Assisted Bicycles as Health Monitoring Systems: A Review.

Sensors (Basel, Switzerland) Jan 8, 2022
This paper aims to provide a review of the electrically assisted bicycles (also known as e-bikes) used for recovery of the rider's physical and physiological information, monitoring of their health state, and adjusting the "medical" assistance accord...
Transportation Electricity Humans Artificial Intelligence Bicycling Accidents, Traffic
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CNN-GRU-AM for Shared Bicycles Demand Forecasting.

Computational intelligence and neuroscience Dec 6, 2021
The demand forecast of shared bicycles directly determines the utilization rate of vehicles and projects operation benefits. Accurate prediction based on the existing operating data can reduce unnecessary delivery. Since the use of shared bicycles is...
Forecasting Neural Networks, Computer Bicycling
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