Arm Movement Analysis
Arm Movement Analysis - Related Videos
01:31
Muscles that Move the Arm
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2024
Nine muscles are involved in arm movements. Two of these, the pectoralis major and latissimus dorsi, originate from the axial skeleton and are called axial muscles. The other seven originate from the scapula and are called the scapular muscles. The pectoralis major has two origins. Its clavicular head originates on the medial half of the clavicle. In contrast, the sternocostal head originates on the costal cartilages of ribs 1-6, the sternum, and the aponeurosis of the external oblique of the...
10:32
Robotic Mirror Therapy System for Functional Recovery of Hemiplegic Arms
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Cited by 26 •
2016
We developed a real-time mirror robot system for functional recovery of hemiplegic arms using automatic control technology, conducted a clinical study on healthy subjects, and determined tasks through feedback from rehabilitation doctors. This simple mirror robot can be applied effectively to occupational therapy in stroke patients with a hemiplegic arm.
07:51
Video Movement Analysis Using Smartphones (ViMAS): A Pilot Study
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Cited by 21 •
2017
This manuscript describes the method to test the concurrent validity of kinematic measures recorded by the smartphone application in comparison to a 3D motion capture system in the sagittal plane. This protocol will enable clinicians to set up smartphones for video capture of human movement.
10:14
Tactile Conditioning And Movement Analysis Of Antennal Sampling Strategies In Honey Bees (Apis mellifera L.)
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Cited by 9 •
2012
In this protocol we show how to condition harnessed honey bees to tactile stimuli and introduce a 2D motion capture technique for analyzing the kinematics of fine-scale antennal sampling pattern.
08:06
Eye Movement Monitoring of Memory
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Cited by 10 •
2010
Eye movement monitoring (or eye tracking) reveals where in space the eyes linger, when and for how long. Here, we demonstrate how eye tracking can be used to investigate the integrity of memory in multiple participant populations, without requiring verbal, or otherwise explicit, reports.
FAQs
Each variable captures a different aspect of arm behavior. Position locates the limb, velocity describes how quickly location changes, acceleration captures changes in velocity, range of motion summarizes movement extent, and joint angles describe limb configuration. Considering them together lets researchers examine coordination and changes over time rather than relying on one observation. In behavior studies, this supports comparisons of intentional actions, spontaneous gestures, and learned movement.
Video recordings, motion-capture systems, and wearable sensors serve as measurement routes for tracking arm movement over time. They allow researchers to record changing limb position and derive measures such as velocity, acceleration, range of motion, and joint angles. Using these tools makes movement quantifiable for behavioral research, motor control, rehabilitation, performance, and studies of responses to environmental or social cues.
By quantifying movement and examining how it changes over time, researchers gain a measurable basis for distinguishing intentional actions from spontaneous gestures. Recording arm behavior while a person encounters environmental or social cues preserves the context in which movement occurs. This makes the method useful for connecting observable limb activity with behavioral responses rather than treating every gesture as equivalent.
Measured arm movement provides a behavioral link to processes that cannot be inferred from position alone. Changes in coordination, movement measures, or performance can be examined in studies of motor control and motor learning. The same measurements also help relate observable actions to underlying cognitive and physiological processes, making movement data relevant beyond description of limb motion.
A basic workflow starts with recording arm movements using video recordings, motion-capture systems, or wearable sensors. Researchers then quantify variables such as position, velocity, acceleration, range of motion, and joint angles, examining how these measures change over time. Finally, they interpret the measurements in relation to motor behavior, coordination, learning, or responses to environmental and social cues.
It is useful when investigators need measurable evidence about motor behavior or physical performance. Applications identified in the source include motor-control and motor-learning studies, rehabilitation, human-computer interaction, and research on disorders that alter coordination. Across these settings, quantified movement can reveal changes in coordination, document responses to cues, or connect observed actions with cognitive and physiological processes.
In human-computer interaction, quantified arm movement provides a way to study physical actions as observable behavioral data. Researchers can examine position, velocity, acceleration, range of motion, and joint angles while considering how movement changes over time. This supports analysis of interactions involving upper-limb behavior and links performance-related movement measures with broader studies of motor control and behavior.