The use of virtual reality in reducing anxiety during cast removal: a randomized controlled trial

Purpose While virtual reality (VR) has been shown to be an effective distractor in children across a range of procedures, no studies have looked at its use within paediatric orthopaedics. The purpose of this study was to look at the use of VR in reducing anxiety levels in children during cast removal. In addition, the study aimed to find ways to enhance the efficiency of future VR trials in paediatrics. Methods A non-blinded randomized control trial took place in children aged four to 18 years. Intraprocedural anxiety was measured using the Children’s Emotional Manifestation Scale (CEMS), while pre- and post-procedural anxiety was measured using the Short State Anxiety Inventory Scale. Additional data was collected on trait anxiety, nausea levels, desire for future VR use and areas of improvement for future VR studies. Results A total of 90 subjects were included in the study (control n = 45, intervention n = 45) with a mean age of 10.25 years (sd 3.35). Post-procedural anxiety and intraprocedural anxiety were 18% (p = 0.03) and 24% (p = 0.01) lower in the VR group, respectively, with the CEMS facial component showing a 31% (p < 0.001) reduction in the VR group. In all, 99% (n = 89) of subjects experienced no nausea, with one patient experiencing mild nausea that may have been present prior to VR use. Finally, 90% (n = 81) of subjects said they would like to use VR again, 1% (n = 1) said ‘no’ and 9% (n = 8) said ‘maybe’. Conclusion VR appears to be an effective distraction technique in reducing anxiety levels in children during cast removal.

Facial Expression Recognition Complications with the Stages of Face Detection and Recognition

Facial expressions are the facial changes in light of a man's interior enthusiastic moods, aims, or social interchanges which are investigated by computer frameworks that endeavor to consequently examine and perceive facial movements and facial component changes from visual data. Now and again the facial expression recognition has been mistaken for feeling examination in the computer vision space prompts uncouth backings of acknowledgment process such as face detection, feature recognition and expression recognition in that way bringing about the issues of identifying impediments, enlightenments, posture varieties, acknowledgment, decrease in dimensionality, and so forth. Notwithstanding that, an appropriate computation and forecast of exact outcomes additionally enhances the execution of the facial Expression recognition. Henceforth, a detailed study was required about the strategies and systems utilized for unraveling the issues of facial expressions during the time of face detection, feature recognition and expression recognition. So thepaper displayed different current strategies and afterward basically considered the effort by the different researchers in the area of Facial Expression Recognition.

Improving the Component-Based Face Recognition Using Enhanced Viola–Jones and Weighted Voting Technique

This paper enhances the recognition capabilities of the facial component-based techniques using the concepts of better Viola–Jones component detection and weighting facial components. Our method starts with enhanced Viola–Jones face component detection and cropping. The facial components are detected and cropped accurately during all pose-changing circumstances. The cropped components are represented by the histogram of oriented gradients (HOG). The weight of each component was determined using a validation process. Combining these weights was done by a simple voting technique. Three public databases were used: the AT&T database, the PUT database, and the AR database. Several improvements are observed using the weighted voting recognition method presented in this paper.

An Accurate Facial Component Detection Using Gabor Filter

Face detection is a critical task to be resolved in a variety of applications. Since faces include various expressions it becomes a difficult task to detect the exact output. Face detection not only play a main role in personal identification but also in various fields which includes but not limited to image processing, pattern recognition, graphics and other application areas. The proposed system performs the face detection and facial components using Gabor filter. The results show accurate detection of facial components