AIMC Topic: Accelerometry
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Accuracy of Samsung Gear S Smartwatch for Activity Recognition: Validation Study.
JMIR mHealth and uHealth
Feb 6, 2019
BACKGROUND: Wearable accelerometers have greatly improved measurement of physical activity, and the increasing popularity of smartwatches with inherent acceleration data collection suggest their potential use in the physical activity research domain;...
Sprint Assessment Using Machine Learning and a Wearable Accelerometer.
Journal of applied biomechanics
Feb 5, 2019
Field-based sprint performance assessments rely on metrics derived from a simple model of sprinting dynamics parameterized by 2 constants, v and τ, which indicate a sprinter's maximal theoretical velocity and the time it takes to approach v, respecti...
Segmenting accelerometer data from daily life with unsupervised machine learning.
PloS one
Jan 9, 2019
PURPOSE: Accelerometers are increasingly used to obtain valuable descriptors of physical activity for health research. The cut-points approach to segment accelerometer data is widely used in physical activity research but requires resource expensive ...
Cricket fast bowling detection in a training setting using an inertial measurement unit and machine learning.
Journal of sports sciences
Dec 13, 2018
Fast bowlers are at a high risk of overuse injuries. There are specific bowling frequency ranges known to have negative or protective effects on fast bowlers. Inertial measurement units (IMUs) can classify movements in sports, however, some commercia...
Wrist accelerometer shape feature derivation methods for assessing activities of daily living.
BMC medical informatics and decision making
Dec 12, 2018
BACKGROUND: There has been an increasing interest in understanding the usefulness of wrist-based accelerometer data for physical activity (PA) assessment due to the ease of use and higher user compliance than other body placements. PA assessment stud...
Feasibility of Reidentifying Individuals in Large National Physical Activity Data Sets From Which Protected Health Information Has Been Removed With Use of Machine Learning.
JAMA network open
Dec 7, 2018
IMPORTANCE: Despite data aggregation and removal of protected health information, there is concern that deidentified physical activity (PA) data collected from wearable devices can be reidentified. Organizations collecting or distributing such data s...
Calibration and validation of accelerometer-based activity monitors: A systematic review of machine-learning approaches.
Gait & posture
Dec 5, 2018
BACKGROUND: Objective measures using accelerometer-based activity monitors have been extensively used in physical activity (PA) and sedentary behavior (SB) research. To measure PA and SB precisely, the field is shifting towards machine learning-based...
Machine learning algorithms for activity recognition in ambulant children and adolescents with cerebral palsy.
Journal of neuroengineering and rehabilitation
Nov 15, 2018
BACKGROUND: Cerebral palsy (CP) is the most common physical disability among children (2.5 to 3.6 cases per 1000 live births). Inadequate physical activity (PA) is a major problem effecting the health and well-being of children with CP. Practical, ye...
A Validation Study of Freezing of Gait (FoG) Detection and Machine-Learning-Based FoG Prediction Using Estimated Gait Characteristics with a Wearable Accelerometer.
Sensors (Basel, Switzerland)
Sep 30, 2018
One of the most common symptoms observed among most of the Parkinson's disease patients that affects movement pattern and is also related to the risk of fall, is usually termed as "freezing of gait (FoG)". To allow systematic assessment of FoG, objec...
Classifier Personalization for Activity Recognition Using Wrist Accelerometers.
IEEE journal of biomedical and health informatics
Sep 12, 2018
Intersubject variability in accelerometer-based activity recognition may significantly affect classification accuracy, limiting a reliable extension of methods to new users. In this paper, we propose an approach for personalizing classification rules...
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