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Motion Capture

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Predicting Free Achilles Tendon Strain From Motion Capture Data Using Artificial Intelligence.

IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society
The Achilles tendon (AT) is sensitive to mechanical loading, with appropriate strain improving tissue mechanical and material properties. Estimating free AT strain is currently possible through personalized neuromusculoskeletal (NMSK) modeling; howev...

Validity of artificial intelligence-based markerless motion capture system for clinical gait analysis: Spatiotemporal results in healthy adults and adults with Parkinson's disease.

Journal of biomechanics
Markerless motion capture methods are continuously in development to target limitations encountered in marker-, sensor-, or depth-based systems. Previous evaluation of the KinaTrax markerless system was limited by differences in model definitions, ga...

A systematic review of the applications of markerless motion capture (MMC) technology for clinical measurement in rehabilitation.

Journal of neuroengineering and rehabilitation
BACKGROUND: Markerless motion capture (MMC) technology has been developed to avoid the need for body marker placement during motion tracking and analysis of human movement. Although researchers have long proposed the use of MMC technology in clinical...

Artificial Intelligence Distinguishes Pathological Gait: The Analysis of Markerless Motion Capture Gait Data Acquired by an iOS Application (TDPT-GT).

Sensors (Basel, Switzerland)
Distinguishing pathological gait is challenging in neurology because of the difficulty of capturing total body movement and its analysis. We aimed to obtain a convenient recording with an iPhone and establish an algorithm based on deep learning. From...

CARRT-Motion Capture Data for Robotic Human Upper Body Model.

Sensors (Basel, Switzerland)
In recent years, researchers have focused on analyzing humans' daily living activities to study various performance metrics that humans subconsciously optimize while performing a particular task. In order to recreate these motions in robotic structur...

MocapMe: DeepLabCut-Enhanced Neural Network for Enhanced Markerless Stability in Sit-to-Stand Motion Capture.

Sensors (Basel, Switzerland)
This study examined the efficacy of an optimized DeepLabCut (DLC) model in motion capture, with a particular focus on the sit-to-stand (STS) movement, which is crucial for assessing the functional capacity in elderly and postoperative patients. This ...

Objective Falls Risk Assessment Using Markerless Motion Capture and Representational Machine Learning.

Sensors (Basel, Switzerland)
Falls are a major issue for those over the age of 65 years worldwide. Objective assessment of fall risk is rare in clinical practice. The most common methods of assessment are time-consuming observational tests (clinical tests). Computer-aided diagno...

Concurrent validity and test reliability of the deep learning markerless motion capture system during the overhead squat.

Scientific reports
Marker-based optical motion capture systems have been used as a cardinal vehicle to probe and understand the underpinning mechanism of human posture and movement, but it is time-consuming for complex and delicate data acquisition and analysis, labor-...

Reliability of artificial intelligence-driven markerless motion capture in gait analyses of healthy adults.

PloS one
The KinaTrax markerless motion capture system, used extensively in the analysis of baseball pitching and hitting, is currently being adapted for use in clinical biomechanics. In clinical and laboratory environments, repeatability is inherent to the q...

Research on acupuncture robots based on the OptiTrack motion capture system and a robotic arm.

Journal of traditional Chinese medicine = Chung i tsa chih ying wen pan
OBJECTIVE: To propose an automatic acupuncture robot system for performing acupuncture operations.