Camera Setup and OpenPose Software without GPU for Calibration and Recording in Telerehabilitation Use

Yona, Yuval; Danan, Omer; Birman, Raz; Hadar, Ofer; Kutílek, Patrik; Hejda, Jan; Hourová, Michaela; Kral, Pavel; Lhotská, Lenka; Doležal, Jaromír; Adolf, Jindřich

doi:10.1109/ehb52898.2021.9657743

Cited by 5 publications

(2 citation statements)

References 4 publications

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“…It is important to notice that OpenPose (OP) requires a powerful GPU to process the video, an issue that might disturb the option to use our solution. In our previous work we have demonstrated where to use a more efficient solution without the need for a GPU to process the videos in real-time [22]. In our next study [23], we proved that OpenPose is robust in terms of quality, video resolution, and lighting changes.…”

Section: Introductionmentioning

confidence: 67%

Evaluation of functional tests performance using a camera-based and machine learning approach

Adolf,

Segal,

Turna

et al. 2023

PLoS ONE

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The objective of this study is to evaluate the performance of functional tests using a camera-based system and machine learning techniques. Specifically, we investigate whether OpenPose and any standard camera can be used to assess the quality of the Single Leg Squat Test and Step Down Test functional tests. We recorded these exercises performed by forty-six healthy subjects, extract motion data, and classify them to expert assessments by three independent physiotherapists using 15 binary parameters. We calculated ranges of movement in Keypoint-pair orientations, joint angles, and relative distances of the monitored segments and used machine learning algorithms to predict the physiotherapists’ assessments. Our results show that the AdaBoost classifier achieved a specificity of 0.8, a sensitivity of 0.68, and an accuracy of 0.7. Our findings suggest that a camera-based system combined with machine learning algorithms can be a simple and inexpensive tool to assess the performance quality of functional tests.

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Section: Introductionmentioning

confidence: 67%

Evaluation of functional tests performance using a camera-based and machine learning approach

Adolf,

Segal,

Turna

et al. 2023

PLoS ONE

Self Cite

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“…Remote healthcare utilizes human posture and gait for real-time medical rehabilitation [ 2 , 3 ]. The COVID-19 pandemic demonstrated the importance of remote diagnosis and treatment.…”

Section: Literature Reviewmentioning

confidence: 99%

Using EfficientNet-B7 (CNN), Variational Auto Encoder (VAE) and Siamese Twins’ Networks to Evaluate Human Exercises as Super Objects in a TSSCI Images

Segal

Hadar

Lhotská

2023

JPM

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In this article, we introduce a new approach to human movement by defining the movement as a static super object represented by a single two-dimensional image. The described method is applicable in remote healthcare applications, such as physiotherapeutic exercises. It allows researchers to label and describe the entire exercise as a standalone object, isolated from the reference video. This approach allows us to perform various tasks, including detecting similar movements in a video, measuring and comparing movements, generating new similar movements, and defining choreography by controlling specific parameters in the human body skeleton. As a result of the presented approach, we can eliminate the need to label images manually, disregard the problem of finding the start and the end of an exercise, overcome synchronization issues between movements, and perform any deep learning network-based operation that processes super objects in images in general. As part of this article, we will demonstrate two application use cases: one illustrates how to verify and score a fitness exercise. In contrast, the other illustrates how to generate similar movements in the human skeleton space by addressing the challenge of supplying sufficient training data for deep learning applications (DL). A variational auto encoder (VAE) simulator and an EfficientNet-B7 classifier architecture embedded within a Siamese twin neural network are presented in this paper in order to demonstrate the two use cases. These use cases demonstrate the versatility of our innovative concept in measuring, categorizing, inferring human behavior, and generating gestures for other researchers.

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Setting Up an Anonymous Gesture Database as Well as Enhancing It with a Verbal Script Simulator for Rehabilitation Applications

Hadar

2022

Cyber Security, Cryptology, and Machine Learning

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Camera Setup and OpenPose Software without GPU for Calibration and Recording in Telerehabilitation Use

Cited by 5 publications

References 4 publications

Evaluation of functional tests performance using a camera-based and machine learning approach

Evaluation of functional tests performance using a camera-based and machine learning approach

Using EfficientNet-B7 (CNN), Variational Auto Encoder (VAE) and Siamese Twins’ Networks to Evaluate Human Exercises as Super Objects in a TSSCI Images

Setting Up an Anonymous Gesture Database as Well as Enhancing It with a Verbal Script Simulator for Rehabilitation Applications

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