AIMC Topic: Oxygen Consumption

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Work-rate-guided exercise testing in patients with incomplete spinal cord injury using a robotics-assisted tilt-table.

Disability and rehabilitation. Assistive technology
PURPOSE: Robotics-assisted tilt-table (RTT) technology allows neurological rehabilitation therapy to be started early thus alleviating some secondary complications of prolonged bed rest. This study assessed the feasibility of a novel work-rate-guided...

Developments in Digital Wearable in Heart Failure and the Rationale for the Design of TRUE-HF (Ted Rogers Understanding of Exacerbations in Heart Failure) Apple CPET Study.

Circulation. Heart failure
BACKGROUND: Heart failure (HF) is a highly prevalent condition characterized by exercise intolerance, an important metric for ambulatory prognostication. However, current methods to assess exercise capacity are often limited to tertiary HF centers, l...

Predictive athlete performance modeling with machine learning and biometric data integration.

Scientific reports
The Purpose of this study is to propose a new integrative framework for athletic performance prediction based on state-of-the-art machine learning analysis and biometric data biometric scanning. By merging physiological signals i.e., Heart rate varia...

Development of deep-learning models for real-time anaerobic threshold and peak VO2 prediction during cardiopulmonary exercise testing.

European journal of preventive cardiology
AIMS: Exercise intolerance is a clinical feature of patients with heart failure (HF). Cardiopulmonary exercise testing (CPET) is the first-line examination for assessing exercise capacity in patients with HF. However, the need for extensive experienc...

PycnoRacer®, a fitness drink including Pycnogenol®, improves recovery and training in the Cooper test.

Panminerva medica
BACKGROUND: This study evaluates the effects of training (on running distance measured with a Cooper test) in 3 weeks in non-professional athletes using PycnoRacer®, a fitness drink (FD) including Pycnogenol® during the training period.

Using Machine Learning to Predict Lower-Extremity Injury in US Special Forces.

Medicine and science in sports and exercise
INTRODUCTION: Musculoskeletal injury rates in military personnel remain unacceptably high. Application of machine learning algorithms could be useful in multivariate models to predict injury in this population. The purpose of this study was to invest...

An improved least squares SVM with adaptive PSO for the prediction of coal spontaneous combustion.

Mathematical biosciences and engineering : MBE
The problem of coal spontaneous combustion prediction is very complex, and there are many factors that affect the prediction results. In order to solve the issues of high dimension and redundancy among features and limited samples in the prediction o...

Applying neural network to VO2 estimation using 6-axis motion sensing data.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
This paper focuses on oxygen consumption (VO2) estimation using 6-axis motion data (3-axis acceleration and 3-axis angular velocity) that are obtained from small motion sensors attached to people playing sports with different intensities. In order to...

VO2 estimation using 6-axis motion sensor with sports activity classification.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
In this paper, we focus on oxygen consumption (VO2) estimation using 6-axis motion sensor (3-axis accelerometer and 3-axis gyroscope) for people playing sports with diverse intensities. The VO2 estimated with a small motion sensor can be used to calc...