scholarly journals Applying Vision-Based Pose Estimation in a Telerehabilitation Application

2021 ◽  
Vol 11 (19) ◽  
pp. 9132
Author(s):  
Francisca Rosique ◽  
Fernando Losilla ◽  
Pedro J. Navarro
Keyword(s):  
Augmented Reality ◽  
Range Of Motion ◽  
Pose Estimation ◽  
Low Cost ◽  
The Other ◽  
Final Conclusion ◽  
Pose Detection ◽  
Human Pose ◽  
Positive Results ◽  
The Web

In this paper, an augmented reality mirror application using vision-based human pose detection based on vision-based pose detection called ExerCam is presented. ExerCam does not need any special controllers or sensors for its operation, as it works with a simple RGB camera (webcam type), which makes the application totally accessible and low cost. This application also has a system for managing patients, tasks and games via the web, with which a therapist can manage their patients in a ubiquitous and totally remote way. As a final conclusion of the article, it can be inferred that the application developed is viable as a telerehabilitation tool, as it has the resource of a task mode for the calculation of the range of motion (ROM) and, on the other hand, a game mode to encourage patients to improve their performance during the therapy, with positive results obtained in this aspect.

An integrated vision-based system for efficient robot arm teleoperation

2020 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Xin Wu ◽  
Canjun Yang ◽  
Yuanchao Zhu ◽  
Weitao Wu ◽  
Qianxiao Wei
Keyword(s):  
Pose Estimation ◽  
Low Cost ◽  
Extraction Process ◽  
Robot Arm ◽  
Mapping Procedure ◽  
Content Type ◽  
Qualitative And Quantitative ◽  
Motion Constraints ◽  
Teleoperation System ◽  
Human Pose

Purpose This paper aims to present a natural human–robot teleoperation system, which capitalizes on the latest advancements of monocular human pose estimation to simplify scenario requirements on heterogeneous robot arm teleoperation. Design/methodology/approach Several optimizations in the joint extraction process are carried on to better balance the performance of the pose estimation network. To bridge the gap between human joint pose in Cartesian space and heterogeneous robot joint angle pose in Radian space, a routinized mapping procedure is proposed. Findings The effectiveness of the developed methods on joint extraction is verified via qualitative and quantitative experiments. The teleoperation experiments on different robots validate the feasibility of the system controlling. Originality/value The proposed system provides an intuitive and efficient human–robot teleoperation method with low-cost devices. It also enhances the controllability and flexibility of robot arms by releasing human operator from motion constraints, paving a new way for effective robot teleoperation.

scholarly journals Designing an augmented reality video game to assist stroke patients with independent rehabilitation

2021 ◽  
Author(s):  
◽  
Regan Petrie
Keyword(s):  
Augmented Reality ◽  
Video Game ◽  
Real World ◽  
Lower Limb ◽  
Health Care Professionals ◽  
Mixed Reality ◽  
Low Cost ◽  
Stroke Patients ◽  
The Real ◽  
Positive Results

<p>Early, intense practice of functional, repetitive rehabilitation interventions has shown positive results towards lower-limb recovery for stroke patients. However, long-term engagement in daily physical activity is necessary to maximise the physical and cognitive benefits of rehabilitation. The mundane, repetitive nature of traditional physiotherapy interventions and other personal, environmental and physical elements create barriers to participation. It is well documented that stroke patients engage in as little as 30% of their rehabilitation therapies. Digital gamified systems have shown positive results towards addressing these barriers of engagement in rehabilitation, but there is a lack of low-cost commercially available systems that are designed and personalised for home use. At the same time, emerging mixed reality technologies offer the ability to seamlessly integrate digital objects into the real world, generating an immersive, unique virtual world that leverages the physicality of the real world for a personalised, engaging experience.  This thesis explored how the design of an augmented reality exergame can facilitate engagement in independent lower-limb stroke rehabilitation. Our system converted prescribed exercises into active gameplay using commercially available augmented reality mobile technology. Such a system introduced an engaging, interactive alternative to existing mundane physiotherapy exercises.  The development of the system was based on a user-centered iterative design process. The involvement of health care professionals and stroke patients throughout each stage of the design and development process helped understand users’ needs, requirements and environment to refine the system and ensure its validity as a substitute for traditional rehabilitation interventions.  The final output was an augmented reality exergame that progressively facilitates sit-to-stand exercises by offering immersive interactions with digital exotic wildlife. We hypothesize that the immersive, active nature of a mobile, mixed reality exergame will increase engagement in independent task training for lower-limb rehabilitation.</p>

5G

2019 ◽  
pp. 519-543 ◽  
Author(s):  
Nidhi Sharma ◽  
Rajeev Mohan Sharma
Keyword(s):  
Energy Efficiency ◽  
Augmented Reality ◽  
Precision Agriculture ◽  
New Technologies ◽  
Low Cost ◽  
The Other ◽  
Industrial Automation ◽  
Battery Lifetime

The tactile internet works on opportunities, critical services, and skill-set transfer instead of data. The global scenario is how realistically a machine/device is going to communicate with the other machine/device. Machine/device connectivity in IoT architecture relies on scalability, signal simplification, low cost and long-term sensors for energy efficiency, and improved battery lifetime. While 5G designs are guided by increased user networking demands in the field of industrial automation, precision agriculture, and augmented reality, researchers are forced to consider the unison of new technologies instead of incremental additions to the LTE specifications.

scholarly journals Designing an augmented reality video game to assist stroke patients with independent rehabilitation

2021 ◽  
Author(s):  
◽  
Regan Petrie
Keyword(s):  
Augmented Reality ◽  
Video Game ◽  
Real World ◽  
Lower Limb ◽  
Health Care Professionals ◽  
Mixed Reality ◽  
Low Cost ◽  
Stroke Patients ◽  
The Real ◽  
Positive Results

<p>Early, intense practice of functional, repetitive rehabilitation interventions has shown positive results towards lower-limb recovery for stroke patients. However, long-term engagement in daily physical activity is necessary to maximise the physical and cognitive benefits of rehabilitation. The mundane, repetitive nature of traditional physiotherapy interventions and other personal, environmental and physical elements create barriers to participation. It is well documented that stroke patients engage in as little as 30% of their rehabilitation therapies. Digital gamified systems have shown positive results towards addressing these barriers of engagement in rehabilitation, but there is a lack of low-cost commercially available systems that are designed and personalised for home use. At the same time, emerging mixed reality technologies offer the ability to seamlessly integrate digital objects into the real world, generating an immersive, unique virtual world that leverages the physicality of the real world for a personalised, engaging experience.  This thesis explored how the design of an augmented reality exergame can facilitate engagement in independent lower-limb stroke rehabilitation. Our system converted prescribed exercises into active gameplay using commercially available augmented reality mobile technology. Such a system introduced an engaging, interactive alternative to existing mundane physiotherapy exercises.  The development of the system was based on a user-centered iterative design process. The involvement of health care professionals and stroke patients throughout each stage of the design and development process helped understand users’ needs, requirements and environment to refine the system and ensure its validity as a substitute for traditional rehabilitation interventions.  The final output was an augmented reality exergame that progressively facilitates sit-to-stand exercises by offering immersive interactions with digital exotic wildlife. We hypothesize that the immersive, active nature of a mobile, mixed reality exergame will increase engagement in independent task training for lower-limb rehabilitation.</p>

scholarly journals Yoga Pose Perfection using Deep Learning

2021 ◽  
Vol 10 (3) ◽  
Author(s):  
Satyam Goyal ◽  
Animesh Jain
Keyword(s):  
Artificial Intelligence ◽  
Deep Learning ◽  
Pose Estimation ◽  
Health Monitoring ◽  
Modern Society ◽  
Public Security ◽  
Pose Detection ◽  
Daunting Task ◽  
Human Pose

Abstract Even with lots of attention and work in the computer vision and artificial intelligence field, human body pose detection is still a daunting task. The application of human pose detection is wide-ranging from health monitoring to public security. This paper focuses on the application in yoga, an art that has been performed for over a millennium. In modern society yoga has become a common method of exercise and there-in arises a demand for instructions on how to do yoga properly. Doing certain yoga postures improperly may lead to injuries and fatigue and hence the presence of a trainer becomes important. As many people don’t have the resources to have a yoga instructor or guide, artificial intelligence can act as a substitute and advise people on their poses. Currently, the research surrounding pose estimation for yoga mainly discusses the classification of yogic poses. In this work, we propose a method, using the Tensorflow MoveNet Thunder model, that allows real-time pose estimation to detect the error in a person's pose, thereby allowing them to correct it.

scholarly journals AZURE KINECT BODY TRACKING UNDER REVIEW FOR THE SPECIFIC CASE OF UPPER LIMB EXERCISES

2021 ◽  
Vol 2021 (2) ◽  
pp. 4333-4341
Author(s):  
EUGENIO IVORRA ◽  
◽  
MARIO ORTEGA ◽  
MARIANO ALCANIZ
Keyword(s):  
Upper Limb ◽  
Pose Estimation ◽  
Motion Tracking ◽  
Tracking System ◽  
Low Cost ◽  
Pearson Correlation ◽  
Microsoft Kinect ◽  
Estimation Methods ◽  
Body Tracking ◽  
Human Pose

A tool for human pose estimation and quantification using consumer-level equipment is a long-pursued objective. Many studies have employed the Microsoft Kinect v2 depth camera but with recent release of the new Kinect Azure a revision is required. This work researches the specific case of estimating the range of motion in five upper limb exercises using four different pose estimation methods. These exercises were recorded with the Kinect Azure camera and assessed with the OptiTrack motion tracking system as baseline. The statistical analysis consisted of evaluation of intra-rater reliability with intra-class correlation, the Pearson correlation coefficient and Bland–Altman statistical procedure. The modified version of the OpenPose algorithm with the post-processing algorithm PoseFix had excellent reliability with most intra-class correlations being over 0.75. The Azure body tracking algorithm had intermediate results. The results obtained justify clinicians employing these methods, as quick and low-cost simple tools, to assess upper limb angles.

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