A best practice for gamification in large companies: An extensive study focusing inter-generational acceptance

Gamification is increasingly successful in the field of education and health. However, beyond call-centers and applications in human resources, its utilization within companies remains limited. In this paper, we examine the acceptance of gamification in a large company (with over 17,000 employees) across three generations, namely X, Y, and Z. Furthermore, we investigate which gamification elements are suited for business contexts, such as the dissemination of company principles and facts, or the organization of work tasks. To this end, we conducted focus group discussions, developed the prototype of a gamified company app, and performed a large-scale evaluation with 367 company employees. The results reveal statistically significant intergenerational disparities in the acceptance of gamification: younger employees, especially those belonging to Generation Z, enjoy gamification more than older employees and are most likely to engage with a gamified app in the workplace. The results further show a nuanced range of preferences regarding gamification elements: avatars are popular among all generations, badges are predominantly appreciated by Generations Z and Y, while leaderboards are solely liked by Generation Z. Drawing upon these insights, we provide recommendations for future gamification projects within business contexts. We hope that the results of our study regarding the preferences of the gamification elements and understanding generational differences in acceptance and usage of gamification will help to create more engaging and effective apps, especially within the corporate landscape

Recent advances in rehabilitation for Parkinson’s Disease with Exergames: A Systematic Review

Objective: The goal of this contribution is to gather and to critically analyze recent evidence regarding the potential of exergaming for Parkinson’s disease (PD) rehabilitation and to provide an up-to-date analysis of the current state of studies on exergame-based therapy in PD patients. Methods: We performed our search based on the conclusions of a previous systematic review published in 2014. Inclusion criteria were articles published in the indexed databases Pubmed, Scopus, Sciencedirect, IEEE and Cochrane published since January 1, 2014. Exclusion criteria were papers with a target group other than PD patients exclusively, or contributions not based on exergames. Sixty-four publications out of 525 matches were selected. Results: The analysis of the 64 selected publications confirmed the putative improvement in motor skills suggested by the results of the previous review. The reliability and safety of both Microsoft Kinect and Wii Balance Board in the proposed scenarios was further confirmed by several recent studies. Clinical trials present better (n = 5) or similar (n = 3) results than control groups (traditional rehabilitation or regular exercise) in motor (TUG, BBS) and cognitive (attention, alertness, working memory, executive function), thus emphasizing the potential of exergames in PD. Pilot studies (n = 11) stated the safety and feasibility of both Microsoft Kinect and Wii Balance Board, potentially in home scenarios as well. Technical papers (n = 30) stated the reliability of balance and gait data captured by both devices. Related metaanalyses and systematic reviews (n = 15) further support these statements, generally citing the need for adaptation to patient’s skills and new input devices and sensors as identified gaps. Conclusion: Recent evidence indicates exergame-based therapy has been widely proven to be feasible, safe, and at least as effective as traditional PD rehabilitation. Further insight into new sensors, best practices and different cognitive stadiums of PD (such as PD with Mild Cognitive Impairment), as well as task specificity, are required. Also, studies linking game parameters and results with traditional assessment methods, such as UPDRS scores, are required. Outcomes for randomized controlled trials (RCTs) should be standardized, and follow-up studies are required, particularly for motor outcomes

Full-Body Motion Tracking In Immersive Virtual Reality - Full-Body Motion Reconstruction and Recognition for Immersive Multiplayer Serious Games

The release of consumer-grade virtual reality head-mounted displays contributed to the development of immersive applications that convey an illusion of being present in the virtual environment. This great potential of virtual reality is promising not only for the entertainment industry but also for education and health. However, the head-mounted display obstructs the players' view of the real environment, causing them to see neither the real environment nor their bodies or those of their teammates and opponents. Therefore, full-body motion reconstruction is essential to improve the sense of presence and interaction among users. Nevertheless, due to the lack of users' motion data, many popular virtual reality games focus solely on upper-body movements and show only controllers or floating hands. Moreover, full-body motion recognition is crucial to ensure that users perform desired physical activities correctly, either to improve health outcomes or to lower the risk of injury. The contributions in this thesis include the reconstruction and recognition of full-body movements using off-the-shelf virtual reality devices. However, such a motion tracking system requires many sensors to be attached to the body, making it difficult to set up and uncomfortable to wear. Therefore, as the first contribution, the number of sensors is reduced to not restrict the user's movements. A reduction in sensors is also required in health-based applications as patients with physical limitations often cannot hold or wear additional devices. To this end, inverse kinematics methods are explored and their parameters are optimized to estimate the full-body pose with high accuracy and low latency. Because high latency between the user's movements and the corresponding visual feedback on the head-mounted display causes cybersickness, the effect of increased end-to-end latency on user experience and performance is investigated as the second contribution. Here, an end-to-end latency threshold that elicits significant cybersickness and causes users to need significantly more time to complete a task is identified. As the third contribution, machine learning algorithms are employed to identify suitable sensor positions for reliable full-body motion recognition. Thereby, the entire movement is analyzed and potential activity execution errors are identified. The elaborated model on full-body motion reconstruction and recognition is prototypically implemented and validated in the context of two serious games: (1) an exergame designed to motivate players to train specific movements and (2) a multiplayer training simulation for police forces to enable training of stressful situations. In the exergame, the system's capability has been demonstrated to recognize the activity execution errors and provide appropriate feedback so that players can improve their movements. By means of the training simulation, statistical significance and effect sizes have been analyzed to examine the impact of full-body avatars in contrast to an abstract representation with head and hands on stress level. Thereby, an empirical study with police forces showed the added value of full-body avatars, which improve the feeling of presence and enable communication via body language and gestures

Analysis of Inverse Kinematics Solutions for Full-Body Reconstruction in Virtual Reality

Many Virtual Reality (VR) applications usually visualize only the VR controllers or floating hands. However, to create an immersive experience, a full-body avatar is essential. We reconstruct a full-body avatar by tracking the position and orientation of the head, hands, feet, and hip. To track the arm movements, the user has to hold two HTC Vive controllers. Additionally, the user has to bind Vive trackers to both ankles and the hip. We apply some of the most popular Inverse Kinematics (IK) methods to estimate the full-body pose. We perform parameter optimization to analyze the damping constant, the maximum number of iterations, and error value for the position as well as rotation. We made several tests between the IK methods in terms of the accuracy and the time to solve the IK problem. The results show that Damped Least Squares (DLS) outperforms the other methods. We furthermore conducted a user study to evaluate the subjective quality of the DLS method. Evaluation results show that the motion reconstruction for lower-body is very accurate; however, for the upper-body, some inaccuracies can occur. Such a motion reconstruction approach can be used in VR exergames, e.g., users can learn different poses while observing the movements in a virtual mirror and by looking down towards their own body

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

Full-Body Motion Recognition in Immersive- Virtual-Reality-Based Exergame

Exergames have beneficial effects on the player’s motivation to exercise. However, many current games lack accurate full-body motion recognition, resulting in players not performing the physical exercise the game requires. Therefore, we aim to develop an immersive virtual reality exergame that simultaneously recognizes and reconstructs full-body movements to motivate players to learn and practice yoga. The system analyzes the entire movement execution and identifies the player’s execution errors to provide appropriate feedback so that players can then improve their movements. Such a system can be used in exergames designed for rehabilitation purposes to assist patients or to monitor their improvement. To access recognition performance, we trained and tested hidden Markov models and applied the leave-one-out cross-validation. The results show that the system achieves an F1-score of 0.79 for yoga warrior I, 0.85 for yoga warrior II, and 0.66 for extended side angle. A user study with 32 participants revealed that the game was fun and that the players enjoyed it. Moreover, performance results show that players needed fewer attempts to correctly perform a pose as the exergame progressed

A survey of full-body motion reconstruction in immersive virtual reality applications

Due to recent advances in virtual reality (VR) technology, the development of immersive VR applications that track body motions and visualize a full-body avatar is attracting increasing research interest. This paper reviews related research to gather and to critically analyze recent improvements regarding the potential of full-body motion reconstruction in VR applications. We conducted a systematic literature search, matching VR and full-body tracking related keywords on IEEE Xplore, PubMed, ACM, and Scopus. Fifty-three publications were included and assigned in three groups: studies using markerless and marker-based motion tracking systems as well as systems using inertial measurement units. All analyzed research publications track the motions of the user wearing a head-mounted display and visualize a full-body avatar. The analysis confirmed that a full-body avatar can enhance the sense of embodiment and can improve the immersion within the VR. The results indicated that the Kinect device is still the most frequently used sensor (27 out of 53). Furthermore, there is a trend to track the movements of multiple users simultaneously. Many studies that enable multiplayer mode in VR use marker-based systems (7 out of 17) because they are much more robust and can accurately track full-body movements of multiple users in real-time

Development of a Directed Teleport Function for Immersive Training in Virtual Reality

Recent advances in Virtual Reality (VR) technology have contributed to the development of immersive applications for training and simulation. VR serious games can be utilized to support and supplement traditional training. In VR-based training environments, the player can make mistakes without serious consequences to gather experiences which help them to make better decisions in the future. However, it is difficult to guide the players attention throughout the VR game, since the player has the freedom to look anywhere anytime. Thus, many game designers create linear and restrictive experiences. In this paper, we develop a dynamic story and guide the players attention to the specific game elements. To this end, we propose a novel directed teleport function to show points of interest to the player. We evaluate the effect of the proposed function by conducting a user study among two groups of 20 participants: one group can use only the common teleport function, whereas the other group can additionally use the directed teleport function. The results of our study indicate that the directed teleport function is very effective, has a positive effect on the orientation, and is very easy to use. In particular, the directed teleport function not only helps the player to navigate through the virtual world but also reveals interesting points