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Running

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Effect of Health and Training on Ultrasensitive Cardiac Troponin in Marathon Runners.

The journal of applied laboratory medicine
PURPOSE: Cardiac troponin (cTn) is the gold standard biomarker for assessing cardiac damage. Previous studies have demonstrated increases in plasma cTn because of extreme exercise, including marathon running. We developed an easy-to-use, ultrasensiti...

Methodology and validation for identifying gait type using machine learning on IMU data.

Journal of medical engineering & technology
With the rising popularity of activity tracking, there is a desire to not only count the number of steps a person takes, but also identify the type of step (e.g., walking or running) they are taking. For rehabilitation and athletic training, this dif...

Markerless 2D kinematic analysis of underwater running: A deep learning approach.

Journal of biomechanics
Kinematic analysis is often performed with a camera system combined with reflective markers placed over bony landmarks. This method is restrictive (and often expensive), and limits the ability to perform analyses outside of the lab. In the present st...

Use of Machine Learning and Wearable Sensors to Predict Energetics and Kinematics of Cutting Maneuvers.

Sensors (Basel, Switzerland)
Changes of directions and cutting maneuvers, including 180-degree turns, are common locomotor actions in team sports, implying high mechanical load. While the mechanics and neurophysiology of turns have been extensively studied in laboratory conditio...

Machine learning algorithms can classify outdoor terrain types during running using accelerometry data.

Gait & posture
BACKGROUND: Running is a popular physical activity that benefits health; however, running surface characteristics may influence loading impact and injury risk. Machine learning algorithms could automatically identify running surface from wearable mot...

Accurate Ambulatory Gait Analysis in Walking and Running Using Machine Learning Models.

IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society
Wearable sensors have been proposed as alternatives to traditional laboratory equipment for low-cost and portable real-time gait analysis in unconstrained environments. However, the moderate accuracy of these systems currently limits their widespread...

A neural network method to predict task- and step-specific ground reaction force magnitudes from trunk accelerations during running activities.

Medical engineering & physics
Prediction of ground reaction force (GRF) magnitudes during running-based sports has several important applications, including optimal load prescription and injury prevention in athletes. Existing methods typically require information from multiple b...

Wi-Fi CSI-Based Outdoor Human Flow Prediction Using a Support Vector Machine.

Sensors (Basel, Switzerland)
This paper proposes a channel state information (CSI)-based prediction method of a human flow that includes activity. The objective of the paper is to predict a human flow in an outdoor road. This human flow prediction is useful for the prediction of...

Free-living Evaluation of Laboratory-based Activity Classifiers in Preschoolers.

Medicine and science in sports and exercise
UNLABELLED: Machine learning classification models for accelerometer data are potentially more accurate methods to measure physical activity in young children than traditional cut point methods. However, existing algorithms have been trained on labor...