AIMC Topic: Accelerometry

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Improved Activity Recognition Combining Inertial Motion Sensors and Electroencephalogram Signals.

International journal of neural systems Sep 11, 2020
Human activity recognition and neural activity analysis are the basis for human computational neureoethology research dealing with the simultaneous analysis of behavioral ethogram descriptions and neural activity measurements. Wireless electroencepha...
Humans Machine Learning Standing Position Accelerometry Sitting Position Human Activities Adult Electroencephalography Walking Monitoring, Ambulatory
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Machine Learning Models for Classifying Physical Activity in Free-Living Preschool Children.

Sensors (Basel, Switzerland) Aug 5, 2020
Machine learning (ML) activity classification models trained on laboratory-based activity trials exhibit low accuracy under free-living conditions. Training new models on free-living accelerometer data, reducing the number of prediction windows compr...
Monitoring, Ambulatory Accelerometry Aged Exercise Humans Child, Preschool Machine Learning Wrist
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Predicting children's energy expenditure during physical activity using deep learning and wearable sensor data.

European journal of sport science Jul 16, 2020
This study examined a series of machine learning models, evaluating their effectiveness in assessing children's energy expenditure, in terms of the metabolic equivalents (MET) of physical activity (PA), from triaxial accelerometery. The study also de...
Humans Energy Metabolism White People Linear Models Accelerometry Deep Learning Calorimetry, Indirect Female Wearable Electronic Devices Ankle Child Male Wrist Exercise
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Inferring transportation mode from smartphone sensors: Evaluating the potential of Wi-Fi and Bluetooth.

PloS one Jul 2, 2020
Understanding which transportation modes people use is critical for smart cities and planners to better serve their citizens. We show that using information from pervasive Wi-Fi access points and Bluetooth devices can enhance GPS and geographic infor...
Automobile Driving Urban Population Accelerometry Denmark Motor Vehicles Walking Wireless Technology Humans Supervised Machine Learning City Planning Transportation Geographic Information Systems Railroads Smartphone
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Complementing subjective with objective data in analysing expertise: A machine-learning approach applied to badminton.

Journal of sports sciences Jun 17, 2020
This study aimed to assess which combination of subjective and empirical data might help to identify the expertise level. A group of 10 expert coaches classified 40 participants in 5 different expertise groups based on the video footage of the rallie...
Female Young Adult Adult Male Humans Machine Learning Algorithms Motor Skills Time and Motion Studies Racquet Sports Adolescent Principal Component Analysis Athletic Performance Accelerometry
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Binary CorNET: Accelerator for HR Estimation From Wrist-PPG.

IEEE transactions on biomedical circuits and systems Jun 11, 2020
Research on heart rate (HR) estimation using wrist-worn photoplethysmography (PPG) sensors have progressed rapidly owing to the prominence of commercial sensing modules, used widely for lifestyle monitoring. Reported methodologies have been fairly su...
Adolescent Wearable Electronic Devices Photoplethysmography Equipment Design Signal Processing, Computer-Assisted Wrist Heart Rate Accelerometry Algorithms Young Adult Adult Middle Aged Humans Neural Networks, Computer
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A Lean and Performant Hierarchical Model for Human Activity Recognition Using Body-Mounted Sensors.

Sensors (Basel, Switzerland) May 29, 2020
Here we propose a new machine learning algorithm for classification of human activities by means of accelerometer and gyroscope signals. Based on a novel hierarchical system of logistic regression classifiers and a relatively small set of features ex...
Machine Learning Algorithms Wearable Electronic Devices Wrist Activities of Daily Living Accelerometry Humans
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Estimating Lower Extremity Running Gait Kinematics with a Single Accelerometer: A Deep Learning Approach.

Sensors (Basel, Switzerland) May 22, 2020
Abnormal running kinematics are associated with an increased incidence of lower extremity injuries among runners. Accurate and unobtrusive running kinematic measurement plays an important role in the detection of gait abnormalities and the prevention...
Humans Biomechanical Phenomena Accelerometry Deep Learning Gait Analysis Lower Extremity Running
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Machine learning to quantify habitual physical activity in children with cerebral palsy.

Developmental medicine and child neurology May 18, 2020
AIM: To investigate whether activity-monitors and machine learning models could provide accurate information about physical activity performed by children and adolescents with cerebral palsy (CP) who use mobility aids for ambulation.
Habits Female Male Humans Exercise Machine Learning Adolescent Child Monitoring, Ambulatory Cerebral Palsy Accelerometry
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Improving energy expenditure estimates from wearable devices: A machine learning approach.

Journal of sports sciences Apr 6, 2020
A means of quantifying continuous, free-living energy expenditure (EE) would advance the study of bioenergetics. The aim of this study was to apply a non-linear, machine learning algorithm (random forest) to predict minute level EE for a range of act...
Bicycling Adult Galvanic Skin Response Jogging Male Fitness Trackers Middle Aged Calorimetry, Indirect Humans Exercise Sedentary Behavior Machine Learning Body Mass Index Heart Rate Algorithms Body Composition Energy Metabolism Female Walking Body Temperature Activities of Daily Living Accelerometry
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