Posture Estimation
Posture Estimation - Related Videos
06:21
Postural Organization of Gait Initiation for Biomechanical Analysis Using Force Platform Recordings
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Cited by 3 •
2022
This paper describes the material and method developed to investigate the postural organization of gait initiation. The method is based on force platform recordings and on the direct principle of mechanics to compute center of gravity and center of pressure kinematics.
09:37
Substantiating Appropriate Motion Capture Techniques for the Assessment of Nordic Walking Gait and Posture in Older Adults
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Cited by 5 •
2016
The aim was to substantiate optimal use of data collection techniques for Nordic walking gait and posture analysis. Three-dimensional motion capture should be used during short duration analysis (i.e. single gait cycle), while accelerometry should be employed for longer duration analysis (i.e. repeated cycles) like a 6 Minute Walk Test.
14:52
Computerized Dynamic Posturography for Postural Control Assessment in Patients with Intermittent Claudication
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Cited by 55 •
2013
Individuals with intermittent claudication exhibit poor balance compared to healthy controls. Computerized dynamic posturography is an objective method for measuring an individual's postural responses to balance disturbances. This provides an objective reflection of the person’s ability to respond to situations under which sensory stimuli are altered and unexpected perturbations occur.
12:18
An Instrumented Pull Test to Characterize Postural Responses
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Cited by 1 •
2019
Impairment of postural reflexes, termed postural instability, is difficult to quantify. Clinical assessments such as the pull test suffer issues with reliability and scaling. Here, we present an instrumented version of the pull test to objectively characterize postural responses.
01:06
What are Estimates?
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2023
It isn't easy to measure a parameter such as the mean height or the mean weight of a population. So, we draw samples from the population and calculate the mean height or mean weight of the individuals in the sample. This sample data acts as a representative measure of the population parameter. These sample statistics are known as estimates. The estimate for the mean of a sample is denoted by ͞x, whereas the mean of the population is designated as μ. Further, parameters such as the mean,...
FAQs
Most posture estimation systems first identify anatomical landmarks and then organize them into a skeletal representation. Depending on the input, computer vision or depth sensing supplies the observations, while a machine-learning model estimates landmark locations in two or three dimensions. This representation gives downstream engineering software structured coordinates for analyzing body configuration rather than relying on raw pixels alone.
Two-dimensional posture estimation represents anatomical landmarks in a 2D skeletal arrangement, whereas three-dimensional estimation represents them in 3D. The choice determines the spatial information available for analysis. Engineers can select between these representations according to the sensing setup and the posture information required for applications such as motion analysis, ergonomic assessment, or interaction with machines.
Temporal analysis adds a frame-to-frame dimension to landmark estimates. By examining how the skeletal representation changes over time, a system can track movement and position instead of treating every image as an isolated observation. This matters in engineering applications that respond to human behavior in real time, because changing posture can guide monitoring or coordination decisions.
A typical workflow begins by collecting images, video, or sensor data, followed by detecting anatomical landmarks with computer-vision, depth-sensing, or machine-learning components. The landmarks are connected into a 2D or 3D skeletal representation, and temporal analysis can track changes across frames. Engineers can then use those estimates to quantify posture or drive responsive systems.
Engineers can use estimated body configurations to quantify awkward positions during work. The skeletal representation supplies a structured basis for examining how a person is positioned, supporting ergonomic risk assessment and identifying conditions relevant to workplace design or worker safety monitoring. These uses depend on obtaining reliable estimates of the person’s posture and movement.
In collaborative robotics, posture estimates can help a machine interpret a person’s position and movement. That information supports coordination between worker and machine, including systems designed to respond to human behavior in real time. The engineering value lies in converting observed body configuration into a form that can inform interaction and safety monitoring.
Beyond ergonomics and robotics, the method supports human-computer interaction, motion analysis, and safety monitoring. In these settings, landmark-based skeletal representations provide a way to interpret body position or movement for a system. The resulting estimates can help applications respond to human behavior, analyze motion, or monitor potentially relevant postures over time.