Identify the Object’s Shape using Augmented Reality Marker-based Technique.

At present, new technology affects daily life in both direct and indirect ways. Internet technology can connect people around the world through social networks. It can facilitate online shopping or e-commerce, which is the popular culture of today business. Contents provided in the online shopping must be in the form that customer can interact with, i.e., it must be converted from analog data to digital information. For apparel or clothing business, only picture and information of the dresses, such as size, color, etc., may not be enough, since the customer did not know whether it will fit their bodies or not. To make sure that the dress they wanted to buy fit their body, the body size of the customers must be known. With the known body size, generating the 3D model of the customer to try on the 3D virtual model of the dress is possible, and the decision to buy is possible. There are many ways to find the exact body size and generate a 3D model of the customers i.e. using 3D scanner, using Photogrammetry technique (merging many photographs of the customers’ bodies to create the 3d model) or generating 3D model with known information using 3d computer graphic software such as Autodesk Maya, 3D max. The techniques mentioned above have some drawback because it required either an expensive device or expert to create a 3D model which may take a long time. Therefore in this research, we present the technique using marker-based Augmented Reality to acquire the shape of the objects. By wrapping the markers around the surface of the object that we want to measure, each marker’s position can be identified, and when combined, the shape and sizes of the object can be created. This technique takes a shorter time than other method and does not require any sophisticated device but still give good results. We separate the experiment into three groups, group one, testing the concept with five objects with different sizes and shapes with one row markers and group two, testing cylindrical objects with four row markers, and group three, testing with a mannequin to find the shape of human’s body. we have found that the shape and size of the objects that we have created are very close to the real one with the maximum error of less than 5%. It possible to generate the whole 3D object which can be adjusted to support virtual fitting room

Interactive Marker-based Augmented Reality for CPR Training

CPR, or Cardiopulmonary Resuscitation, is a lifesaving technique useful for the case in which someone’s heartbeat or breathing has stopped due to heart attack. Without proper CPR, nine out of ten patients die. The American Heart Association recommends CPR with chest compressions in the event of witnessing such an incident. For proper CPR training, taking a class with a CPR instructor is usually the best choice, but it is not practical and costly for mass training, especially in schools and universities. There are many new techniques available that can replace traditional CPR training and Augmented Reality (AR) is one of them. AR is the technology that integrates virtual objects or environments, created by digital technology, with the real world. Augmented Reality using marker-based technique is a good option, since a trainee can have a realistic look at the patient, know the position of the hand on the chest, identify the number of chest compressions per minute, and also know the pressure that he or she puts on the chest. Besides that, the status of the operation can be displayed along with a recording system for analysis. In this research, we chose marker-based AR due to its precision in distance measurement. For measuring the pressure on the chest, we use a marker-marker interaction technique. Unity 3D cross-platform game engine and Qualcomm's Vuforia—an augmented reality software development kit (SDK) for mobile devices that enables the creation of augmented reality applications—are required. The results from our experiment with a group of people with non-CPR training confirm that the configuration increases the speed and accuracy of CPR training

Enhancing Exercise Monitoring and Guidance Through Mobile Augmented Reality: A Comparative Study of RGB and LiDAR

Augmented Reality (AR) technology for motion tracking is often used on mobile devices with an RGB front camera or LiDAR sensor rear camera. While there are various AR applications for exercise, there is a lack of comparative studies investigating the specific effects of these technologies on the AR exercise experience. This study evaluated the performance and usability of using the RGB camera and the LiDAR sensor for exercise monitoring with a mobile AR application. We examined their performance in different environmental room conditions: a solid wall, a glass wall, and a wall with objects. Focusing on a marching-in-place use case, we assessed accuracy and usability across participants with varying body mass index (BMI). Our application provided display and audio notifications for correct posture compared with validation by an expert physical therapist. The results indicated that differences in BMI did not significantly affect accuracy. Algorithm 1. The LiDAR provided higher accuracy in various environments, while the RGB camera provided higher scores in usability. The results suggested that standing position affected the detection both RGB and LiDAR cameras had better accuracy when standing at a 45-degree angle than directly facing the camera. This study showed the potential of both technologies for telehealth scenarios, emphasizing the significance of practical usage in households and ease of use to support exercise monitoring and empower users to achieve fitness goals and telehealth

The Design and Development of a Foot-Detection Approach Based on Seven-Foot Dimensions: A Case Study of a Virtual Try-On Shoe System Using Augmented Reality Techniques

Unsuitable shoe shapes and sizes are a critical reason for unhealthy feet, may severely contribute to chronic injuries such as foot ulcers in susceptible people (e.g., diabetes patients), and thus need accurate measurements in the manner of expert-based procedures. However, the manual measure of such accurate shapes and sizes is labor-intensive, time-consuming, and impractical to apply in a real-time system. This research proposes a foot-detection approach using expert-like measurements to address this concern. It combines the seven-foot dimensions model and the light detection and ranging sensor to encode foot shapes and sizes and detect the dimension surfaces. The graph-based algorithms are developed to present seven-foot dimensions and visualize the shoe’s model based on the augmented reality (AR) technique. The results show that our approach can detect shapes and sizes more effectively than the traditional approach, helps the system imitate expert-like measurements accurately, and can be employed in intelligent applications for susceptible people-based feet measurements

Application of Augmented Reality Technology for Chest ECG Electrode Placement Practice

This study presents an augmented reality application for training chest electrocardiography electrode placement. AR applications featuring augmented object displays and interactions have been developed to facilitate learning and training of electrocardiography (ECG) chest lead placement via smartphones. The AR marker-based technique was used to track the objects. The proposed AR application can project virtual ECG electrode positions onto the mannequin’s chest and provide feedback to trainees. We designed experimental tasks using the pre- and post-tests and practice sessions to verify the efficiency of the proposed AR application. The control group was assigned to learn chest ECG electrode placement using traditional methods, whereas the intervention group was introduced to the proposed AR application for ECG electrode placement. The results indicate that the proposed AR application can encourage learning outcomes, such as chest lead ECG knowledge and skills. Moreover, using AR technology can enhance students’ learning experiences. In the future, we plan to apply the proposed AR technology to improve related courses in medical science education

Teaching Fundamental Programming Using Augmented Reality

To learn a programming language, the students have to understand the logical flow of the commands as well as the syntax. The logical flow might be more difficult to understand when compared with a syntax which can detect easily. The primary flow of commands or the control structures includes the sequence, condition or selection, and iteration. The students construct the program flowchart by using these control structure. They also have to understand the result of each command execution, step by step. In this research, we propose the technique for developing the learning tool (AR flowchart) to simulate the result of the commands in program flowchart by using augmented reality (AR), so the learners can visualize the result. With this tool, the students can construct a program flowchart as a series of commands by using AR markers. The result of the execution of these commands can be displayed so the students can see whether the logic of the program is correct or not. The design of this tool aims at increasing student engagement and helping them to understand program logic better. The evaluation of the concept results by the group of university students supports our propose

Study of the Hand Anatomy Using Real Hand and Augmented Reality

Anatomy is considered one of the foundation studies for all of the health science students especially medical and nursing students. Anatomy of the hand is complicated. It composes of bones, nerves, blood veins, muscles, and tendon. Memorising all the details about all those parts is tedious work and need much imagination. With the advances in computer graphics and human-computer interaction techniques, understanding how those body parts move is easy to understand in a visual presentation. Augmented Reality (AR) is the technique that allowed the computer-generated objects to overlay on top of the real world. In this study, we concentrate on studying the bones only. We have selected the Leap Motion, which is the device that can detect the hands and fingers, like a tracking device, and marker-based AR technique for displaying the computer generated bones on top of the real hand. Since the Leap Motion detects the hands and shows the bone in real time, so when a user moves the hands such as waving, all the 3D virtual bones move to the new position just like the real hand. Besides using this tool as the educational tool to help the students have better learning about anatomy, it can also be used as an assessment tool for anatomy class as well. Results from testing this tool with volunteer students indicate that it helps them to understand the hand anatomy better and faster than traditional ways

Teaching Fundamental Programming Using Augmented Reality

To learn a programming language, the students have to understand the logical flow of the commands as well as the syntax. The logical flow might be more difficult to understand when compared with a syntax which can detect easily. The primary flow of commands or the control structures includes the sequence, condition or selection, and iteration. The students construct the program flowchart by using these control structure. They also have to understand the result of each command execution, step by step. In this research, we propose the technique for developing the learning tool (AR flowchart) to simulate the result of the commands in program flowchart by using augmented reality (AR), so the learners can visualize the result. With this tool, the students can construct a program flowchart as a series of commands by using AR markers. The result of the execution of these commands can be displayed so the students can see whether the logic of the program is correct or not. The design of this tool aims at increasing student engagement and helping them to understand program logic better. The evaluation of the concept results by the group of university students supports our propose