Autonomous Flight Using UWB-Based Positioning System with Optical Flow Sensors in a GPS-Denied Environment

This study presents the positioning method and autonomous flight of a quadrotor drone using ultra-wideband (UWB) communication and an optical flow sensor. UWB communication obtains the distance between multiple ground stations and a mobile station on a robot, and the position is calculated based on a multilateration method similar to global positioning system (GPS). The update rate of positioning using only UWB communication devices is slow;hence, we improved the update rate by combining the UWB and inertial measurement unit (IMU) sensor in the prior study. This study demonstrates the improvement of the positioning method and accuracy by sensor fusion of the UWB device, an IMU, and an optical flow sensor using the extended Kalman filter. The proposed method is validated by hovering and position control experiments and also realizes a sufficient rate and accuracy for autonomous flight.

Advanced Dance Choreography System Using Bidirectional LSTMs

Recently, the craze of K-POP contents is promoting the development of Korea's cultural and artistic industries. In particular, with the development of various K-POP contents, including dance, as well as the popularity of K-POP online due to the non-face-to-face social phenomenon of the Coronavirus Disease 2019 (COVID-19) era, interest in Korean dance and song has increased. Research on dance Artificial Intelligent (AI), such as artificial intelligence in a virtual environment, deepfake AI that transforms dancers into other people, and creative choreography AI that creates new dances by combining dance and music, is being actively conducted. Recently, the dance creative craze that creates new choreography is in the spotlight. Creative choreography AI technology requires the motions of various dancers to prepare a dance cover. This process causes problems, such as expensive input source datasets and the cost of switching to the target source to be used in the model. There is a problem in that different motions between various dance genres must be considered when converting. To solve this problem, it is necessary to promote creative choreography systems in a new direction while saving costs by enabling creative choreography without the use of expensive motion capture devices and minimizing the manpower of dancers according to consideration of various genres. This paper proposes a system in a virtual environment for automatically generating continuous K-POP creative choreography by deriving postures and gestures based on bidirectional long-short term memory (Bi-LSTM). K-POP dance videos and dance videos are collected in advance as input. Considering a dance video for defining a posture, users who want a choreography, a 3D dance character in the source movie, a new choreography is performed with Bi-LSTM and applied. For learning, considering creativity and popularity at the same time, the next motion is evaluated and selected with probability. If the proposed method is used, the effort for dataset collection can be reduced, and it is possible to provide an intensive AI research environment that generates creative choreography from various existing online dance videos.

Tele-Snap: a joint impedance estimation system using snap motor and openPose for remote rehabilitation diagnosis

We propose a remote joint impedance estimation system called Tele-snap for a rehabilitation diagnosis under the COVID-19 pandemic. Dynamic resistance of the human joint is essential physical information reflecting the motor function. The resistance is assessed based on the touching sensation of the doctor (physiotherapist), but the pandemic restricts such an in-person manner. Our proposing system aims to provide this physical information quantified by the joint impedance for a diagnosis in the telerehabilitation context. The proposed system employs a compact impulsive perturbation generator called the snap motor and a marker-less motion capture technology called the OpenPose. The subsystem installed in the patient's place is then simplified remarkably, which consists of the wearable snap motor and Raspberry Pi with a built-in camera module. The proposed system can collect the dataset for impedance estimation through the examiner's teleoperation of the snap motor and camera via a virtual private network, with no need for the operation by the patient. We verify the proposed system through an in-person experiment and then demonstrate the remote impedance estimation scheme. [ FROM AUTHOR] Copyright of Advanced Robotics is the property of Taylor & Francis Ltd and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full . (Copyright applies to all s.)

Virtual reality learning environments: Using high-fidelity avatars to enhance distance learning experience

Virtual Learning Environments (VLEs) became the primary space for education during the Coronavirus disease (COVID-19) lockdowns. One of the additions that specifically VR has to offer is its potential to incorporate some of the qualities that define interpersonal communication and typically lack in distance-learning VLEs. This study's aim is exploration of those qualities to appreciate Virtual Reality Learning Environments (VRLEs) as a supplementary tool for distance learning and its impact on knowledge acquisition processes, with the particular objectives of evaluating usability, usefulness, and realism of Non-Verbal Cues (NVCs) capture. Toward this end a multi-user VRLE prototype was developed and utilized for the delivery of a live lecture by a real professor of a MSc programme. The professor's body motion and facial expressions were captured in real-time and solved onto a high-fidelity avatar. In total, a group of 20 students audited the lecture via the VRLE and evaluated the modalities and experience offered compared to conventional VLEs. Additionally, knowledge acquisition was directly correlated to another group of 20 students, who audited the same lecture only via conventional VLEs. Evaluation results provide important insight regarding the learning experience between the two settings and how incorporation of NVCs can have a positive impact. (PsycInfo Database Record (c) 2022 APA, all rights reserved)

Non-contact Respiration Measurement by Using RGB-D Camera

With the global pandemic of COVID-19, it is expected to develop a respiratory function test system with less contamination of the sensor by aerosol. In this study, we proposed a simple non-contact respiratory measurement system using the REALSENSE DEPTH CAMERA D455, which is an RGB-D camera manufactured by Intel Corp. By applying the skeletal tracking library to the acquired depth images, the shoulder and hip joints of the upper body were detected, and the volume change inside the quadrilateral connecting them was obtained. The volume change waveform showed periodicity due to respiratory movement. As a result of a comparative experiment with a spirometer, it was clarified that the respiratory effort can be measured non-contactly by the proposed method. © 2022 IEEE.

Non-contact Respiration Measurement by Using RGB-D Camera

With the global pandemic of COVID-19, it is expected to develop a respiratory function test system with less contamination of the sensor by aerosol. In this study, we proposed a simple non-contact respiratory measurement system using the REALSENSE DEPTH CAMERA D455, which is an RGB-D camera manufactured by Intel Corp. By applying the skeletal tracking library to the acquired depth images, the shoulder and hip joints of the upper body were detected, and the volume change inside the quadrilateral connecting them was obtained. The volume change waveform showed periodicity due to respiratory movement. As a result of a comparative experiment with a spirometer, it was clarified that the respiratory effort can be measured non-contactly by the proposed method. © 2022 IEEE.

Radiant soma

The human body has historically been a constant source of fascination in the arts and sciences. With the impact of the COVID-19 pandemic, the debate over the virtues and disadvantages of physical versus virtual bodies has increased dramatically. One of the most difficult attributes of the human body to translate into other forms is the essence of human movement and, by extension, energy. Radiant Soma emphasizes the ephemerality of human movement by visualizing motion capture data with light. The installation of lasers and phosphorescent objects transforms choreography that the original performer can no longer perform into a constant stream of lively spirits. © 2022 Owner/Author.

Stage Together: Remote Rehearsal of Theater Blocking

The COVID-19 pandemic has forced many theater productions to shift to remote rehearsals and performances using online video conference platforms. Video conference software makes it possible to share individual performances, but loses the sense of presence together and provides no way to visualize blocking movements on the shared space of the stage. Rehearsal by video conference can cause productions to either omit blocking altogether or have only a few on stage rehearsals, sometimes just days before opening. This paper presents a Web-based system that enables productions to remotely rehearse blocking at any stage of the production. Remote performers can propose their own blocking, rehearse scripted cues and visualize movements in a shared virtual stage. This paper describes the design, implementation, and focus group evaluations of Stage Together with a college theater production of Medea by Euripides. © 2022 ACM.

Preliminary Development of Virtual Try-On Platform for Batik Apparel Based on Mobile Augmented Intelligence Technology

During the COVID-19 pandemic, the government decided to suspend all arts cultural events to prevent the spread of the virus. This situation is a challenge for batik artisans to survive. This research aims to develop a virtual try-on platform that is an alternative medium for artisans to solve their problems. Development platforms based on augmented reality technology can be an option for the problems. Platform designed based on mobile devices has advantages in the practicality of use that is not limited by space and time. Implementation of human motion capture and hand gesture recognition provides an immersive experience for users. Motion capture is used for a virtual try-on scheme for batik apparel that can make users try batik apparel virtually and can automatically fit the user’s body. In addition, the implementation of hand gesture recognition allows users to apply batik motifs to virtual apparel interactively combined with material fitting function, which can assist users in positioning batik motifs. Apart from technical matters, this platform also provides information about the history of batik motifs. Alpha testing is used in testing the platform and confusion matrix to validate the accuracy of implementing the functions that exist on the platform. The results of testing the accuracy of hand gesture recognition reached 97%, and human motion capture reached 93%, which means the system can run well. This paper describes the initial efforts made to develop a virtual try-on platform for batik apparel based on Augmented Intelligence Technology. © 2022, ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering.

Healthcare applications of single camera markerless motion capture: a scoping review

Background Single camera markerless motion capture has the potential to facilitate at home movement assessment due to the ease of setup, portability, and affordable cost of the technology. However, it is not clear what the current healthcare applications of single camera markerless motion capture are and what information is being collected that may be used to inform clinical decision making. This review aims to map the available literature to highlight potential use cases and identify the limitations of the technology for clinicians and researchers interested in the collection of movement data. Survey Methodology Studies were collected up to 14 January 2022 using Pubmed, CINAHL and SPORTDiscus using a systematic search. Data recorded included the description of the markerless system, clinical outcome measures, and biomechanical data mapped to the International Classification of Functioning, Disability and Health Framework (ICF). Studies were grouped by patient population. Results A total of 50 studies were included for data collection. Use cases for single camera markerless motion capture technology were identified for Neurological Injury in Children and Adults;Hereditary/Genetic Neuromuscular Disorders;Frailty;and Orthopaedic or Musculoskeletal groups. Single camera markerless systems were found to perform well in studies involving single plane measurements, such as in the analysis of infant general movements or spatiotemporal parameters of gait, when evaluated against 3D marker-based systems and a variety of clinical outcome measures. However, they were less capable than marker-based systems in studies requiring the tracking of detailed 3D kinematics or fine movements such as finger tracking. Conclusions Single camera markerless motion capture offers great potential for extending the scope of movement analysis outside of laboratory settings in a practical way, but currently suffers from a lack of accuracy where detailed 3D kinematics are required for clinical decision making. Future work should therefore focus on improving tracking accuracy of movements that are out of plane relative to the camera orientation or affected by occlusion, such as supination and pronation of the forearm.

A remote rehabilitation training system using Virtual Reality

Τhe rehabilitation process of sports injuries, movement and balance of the elderly with mobility problems as well people with injuries, is of key importance for the best possible recovery of proper functioning and mobility of the limbs of these individuals. In most cases, rehabilitation is provided in specialized rehabilitation centers, through services and recovery programs that are carried out for a specific period of time. During the patient's stay in the rehabilitation center, professional gait and balance analysis systems are used to assess his condition. These systems are usually too expensive, difficult to use, and can not be easily replaced by lower cost devices that provide the same quality and reliability. Furthermore, due to COVID-19 pandemic, the physical presence of a person during the execution of rehabilitation program has become prohibitive in many cases. Our solution offers an at-home rehabilitation exercises system using Virtual Reality with a human-alike Virtual Coach. The exercises for each patient are defined by doctors providing a personalized record tracking the rehabilitation progress. © 2021 IEEE

Full-Body Interaction in a Remote Context: Adapting a Dance Piece to a Browser-Based Installation

This paper describes the process of adapting a dance piece to an interactive installation. To cope with COVID-19 restrictions, the installation runs on a browser, allowing for remote access, and is based on camera tracking of movement. We describe the adaptation of the dramaturgy, with a primary focus on translating the interaction design aspects from the performance to the browser-based installation. We invited five users to test our working prototype, and we report on their feedback. This paper offers insights on how to adapt a dance piece to an interactive browser-based installation. We also highlight the benefits of using machine learning for motion capture in this context. Finally, we identify the potential of using interaction design with sound for embodied perception. © 2021 Copyright held by the owner/author(s). Publication rights licensed to ACM.

Comparison of Geometrical Lung Models to Calculate Tidal Volumes during Spontaneous Breathing

Demographic changes, increasing air pollution and the ongoing Covid-19 pandemic, causing virus-induced respiratory failures, monitoring of respiratory parameters is the focus of international interest. In this study, motioncapture- system data was used to get circumferences of the human thorax while executing different breathing patterns. Four geometric models were used to model tidal volumes of the tracked person while using spirometry data as a reference. The results show that all four introduced models can be used for tidal volume calculation based on changes in the thoracic circumference. In terms of accuracy, the use-case must be considered © 2021 by Walter de Gruyter Berlin/Boston.

Recognizing Full-Body Exercise Execution Errors Using the Teslasuit.

Regular physical exercise is essential for overall health; however, it is also crucial to mitigate the probability of injuries due to incorrect exercise executions. Existing health or fitness applications often neglect accurate full-body motion recognition and focus on a single body part. Furthermore, they often detect only specific errors or provide feedback first after the execution. This lack raises the necessity for the automated detection of full-body execution errors in real-time to assist users in correcting motor skills. To address this challenge, we propose a method for movement assessment using a full-body haptic motion capture suit. We train probabilistic movement models using the data of 10 inertial sensors to detect exercise execution errors. Additionally, we provide haptic feedback, employing transcutaneous electrical nerve stimulation immediately, as soon as an error occurs, to correct the movements. The results based on a dataset collected from 15 subjects show that our approach can detect severe movement execution errors directly during the workout and provide haptic feedback at respective body locations. These results suggest that a haptic full-body motion capture suit, such as the Teslasuit, is promising for movement assessment and can give appropriate haptic feedback to the users so that they can improve their movements.

Remote visual line-of-sight: A Remote Platform for the Visualisation and Control of an Indoor Drone using Virtual Reality

The COVID-19 pandemic has created the distinct challenge for the piloting of drones/other UAVs for researchers and educators who are restricted to working remotely. We propose a Remote Visual Line-of-Sight system that leverages the advantages of Virtual Reality (VR) and motion capture to allow users to fly a real-world drone from a remote location. The system was developed while our researcher (VR operator) was remotely working in Vietnam with the enclosed real-world environment located in Australia. Our paper will present the system design and the challenges found during the development of our system. © 2021 Copyright held by the owner/author(s).

A review of the evolution of scientific literature on technology-assisted approaches using RGB-D sensors for musculoskeletal health monitoring.

The human musculoskeletal (MSK) system (also known as the locomotor system) provides strength and assistance to perform functional tasks and daily life activities. The MSK health monitoring plays a vital role in maintaining the body mobility and quality of life. Manual approaches for musculoskeletal health monitoring are subjective and require a clinician's intervention. The evolution in motion tracking technology enables us to capture the fine details of body movements. The research community has proposed various approaches to help clinicians in diagnosis and monitor treatment sessions. This paper succinctly reviews the evolution of technology-assisted approaches for musculoskeletal health monitoring, using motion capture sensors. To streamline the search through the literature database, the PICOS framework and PRISMA method have been incorporated. The present study reviews methods to transform motion capture data into kinematics variables and factors that affect the tracking performance of RGB-D sensors. Furthermore, widely utilized time-series filters for skeletal data denoising and smoothing for kinematics analysis, stochastic models for movement modeling, rule-based and template-based approaches for rehabilitation exercises assessment, and telerehabilitation sessions for remote health monitoring are explored. This article analyzes skeletal tracking methods by providing advantages and drawbacks of the state of the art rehabilitation sessions assessment, skeletal joint kinematics analysis, and MSK Telerehabilitation approaches. It also discusses the possible future research avenues to improve musculoskeletal disorder diagnosis and treatment monitoring. Our review signifies that RGB-D sensor-based approaches are inexpensive and portable for disorder diagnosis and treatment monitoring. It can also be a viable option for clinicians to provide contactless healthcare access to patients in the current scenario of the COVID-19 pandemic.