Accelerometry: providing an integrated, practical method for long-term, ambulatory monitoring of human movement

By M. Mathie, A. Coster, N. Lovell, B. Celler. Physiological Measurement, 2004

868 citations recorded by the source corpus.

Subfields: Biomedical Engineering, Computer Vision and Pattern Recognition, Physical Therapy, Sports Therapy and Rehabilitation

View Paper: https://www.semanticscholar.org/paper/c05ce08ccfc029bdc47d33fb0c3da9809ed35c6e

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In Biomedical Engineering

In Computer Vision and Pattern Recognition

In Physical Therapy, Sports Therapy and Rehabilitation

Citations in the corpus

Sensible Organizations: Technology and Methodology for Automatically Measuring Organizational Behavior (2008, background): “The three-axis accelerometer signal is sampled at fs = 250 Hz, which should be able to capture the range of human movement and could be as low as 30 Hz since 99% of the acceleration power during daily human activities is contained below 15 Hz [35].”
Direct measurement of human movement by accelerometry. (2008, methodology): “Accelerometers can also e used to measure tilt (body posture) making them supeior to those devices that have no ability to measure static haracteristics [38,39].”
Comparison of low-complexity fall detection algorithms for body attached accelerometers. (2008, background): “Waist attached accelerometers are located near the body’s center of gravity, providing reliable information on subject body movements, with the exception of specific movements of arms and legs [15].”
Distributed recognition of human actions using wearable motion sensor networks (2009, neutral): “There have been other systems that tackle more general problems of recognizing multiple different human actions that would be commonplace in people’s daily lives [8,19,21,22].”
Assessment of physical activity in youth. (2008, background): “Acceleration is a change in velocity with respect to time (SI unit; m/s(2)), enabling accelerometers to quantify the intensity of movement for that body part (20, 22, 40, 65).”
A Review of Accelerometry-Based Wearable Motion Detectors for Physical Activity Monitoring (2010, background): “Accelerometers have been widely accepted as useful and practical sensors for wearable devices to measure and assess PA in either clinical/laboratory settings or free-living environments [8].”
Detection of Daily Activities and Sports With Wearable Sensors in Controlled and Uncontrolled Conditions (2008, background): “Accelerometers are currently among the most widely studied wearable sensors for activity recognition, thanks to their accuracy in the detection of human body movements, small size, and reasonable power consumption [ 10 ].”
Human Activity Recognition Using Inertial/Magnetic Sensor Units (2010, background): “References [5,6,7] provide comprehensive surveys on the use of inertial sensors in motion recognition and analysis.”
A survey on fall detection: Principles and approaches (2013, background): “Mathie et al. [38] used an integrated approach of waist-mounted accelerometry .”
Optimal Placement of Accelerometers for the Detection of Everyday Activities (2013, background): “The acceleration signal recorded from the body depends upon the location of the sensing device and the activity being performed [4].”
Comparative study on classifying human activities with miniature inertial and magnetic sensors (2010, background): “A 016/j.patcog.2010.04.019 esponding author. ail address: billur@ee.bilkent.edu.tr (B. Barsha a b s t r a c t This paper provides a comparative study on the different techniques of classifying human activities that are performed using body-worn miniature inertial and magnetic sensors.”
Activity classification using realistic data from wearable sensors (2006, background): “The studies using accelerometry for monitoring human movement have been recently reviewed in [9] and [10].”
Window Size Impact in Human Activity Recognition (2014, background): “A wide range of heuristics [67], time/frequency domain [44,45] and other sophisticated mathematical and statistic functions [68] are commonly used.”
Gait Analysis Using Wearable Sensors (2012, background): “[85,86] reviewed the use of accelerometer-based systems in human movement, such as monitoring a range of different movements, measuring physical activity levels and identifying and classify movements performed by subjects, and discussed a real-time human movement classifier using a triaxial accelero”