This paper investigates the capability of Kinect sensor as interactive technology and discusses how it can assist and improve teaching and learning. The Kinect sensor is a motion sensor that provides a natural user interface. It was implemented by Microsoft for the Xbox 360 video-game console to create a new control-free experience for the user without any intermediary device. The Kinect sensor can enhance kinesthetic pedagogical practices to profit learners with strong bodily-kinesthetic intelligence (body smart). As a learning tool, the Kinect sensor has potential to create interactive games, to increase learner motivation, and to enhance learning efficiency via its multimedia and multisensory capacity. Many students must learn spatial skills to improve learning achievement in science, mathematics, and engineering. This paper will focus on developing the Kinect sensor-assisted game-based learning system with ARCS model to provide kinesthetic pedagogical practices for learning spatial skills, motivating students, and enhancing students’ effectiveness. The responses to the System Usability Scale indicated that our system demonstrated usability and learnability. We conclude that the Kinect sensor-assisted learning system promotes the development of students’ spatial visualization skills and encourages them to become active learners.

Study Objectives: Kleine-Levin syndrome (KLS) is a rare recurrent hypersomnia. Our study aimed at monitoring the movements of patients with KLS using actigraphy and evaluating their circadian rhythm. Methods: Twenty young patients with KLS and 14 age-matched controls were recruited. Each individual wore an actigraphy for more than 6 months to monitor at least two attacks. Controls kept wearing the device for at least 7 days. The activity counts were averaged in hourly basis and the day-to-night amplitude was quantified by the differences of the averaged activity counts during daytime and nighttime. The hourly activities of different days were aligned and averaged to construct the circadian profile. Parametric and nonparametric estimation of circadian rhythm was calculated. We applied detrended fluctuation analysis to evaluate the temporal correlations beneath the activity fluctuations at multiple time scales. Results: Circadian rhythm in asymptomatic period showed no significant difference compared to the controls. During hypersomnia attack, the amplitude of the circadian rest–active rhythms drastically decreased and decreased interdaily stability (IS) was found, as well as significant decreased M10 and short-time fractal correlation (α1). Drastically decreased mean and standard deviation of activity were noted, compared to the pre-attack phase and recovery phase. α1 and M10 increased during the late attack phase, and overcompensated IS was noted in the recovery phase. Conclusions: This study confirmed that circadian rest–active rhythms was affected when KLS hypersomnia attack. Several parameters including M10, IS, and α1 may be physiological markers of KLS, which can help to predict the end of hypersomnia episodes.

In this paper, a system for lower-limb amputees to collect and analyze their locomotion activities is developed. Wearable Gait Lab (WGL) system is a pair of smart insoles that can collect plantar pressure data and foot motion data of subjects. A reinforcement learning model is trained to imitate the walking pattern of the lower-limb amputee on a musculoskeletal model by introducing realistic velocity data into the training process. The plantar pressure data collected from our Wearable Gait Lab were used to recognize the locomotion modes of the amputees. Experiments showed that the outcome of the musculoskeletal model can be a reference for analyzing muscle activities of the amputee. The system also shows the promising and stable performance of recognizing locomotion modes in amputees’ daily life. The accuracy of locomotion mode recognition reaches 98.02Monitoring muscle activities and locomotion modes of lowerlimb amputees can help them prevent secondary impairments in rehabilitation.

Background: Inflammation is often considered relating to pediatric obstructive sleep apnea (OSA). We conducted a study investigating cytokines, including Il-17 and Il-23, in children with OSA before and after adenotonsillectomy (T&A), compared with controls. Methods: Children with OSA between age 4 and 12 receiving T&A were prospectively followed. Evaluation before and reevaluation six months after the treatment were done, including polysomnography (PSG), blood tests, and questionnaires. Blood samples were obtained to determine the values of high-sensitivity-C-reactive-protein (HS-CRP); tumor-necrosis-factor-alpha (TNF-α); and interleukin (IL)-1, 6, 10, 12, 17, and 23. We compared the results with an age-matched control group. Results: We included 55 OSA children and 32 controls. Children with OSA presented significant improvement after T&A in complaints, signs, apnea hypopnea index (AHI) (p < 0.001), mean oxygen desaturation index (p < 0.001), and mean oxygen saturation (p = 0.010). Upon entering this study, children with OSA had significantly higher cytokine levels than the controls and significant changes in HS-CRP (p = 0.013), TNF-α (p = 0.057), IL-1β (p = 0.022), IL-10 (p = 0.035), and IL-17 (p = 0.010) after T&A. Children with improved but persistently abnormal AHI did not have all cytokine levels normalized, particularly IL-23 and HS-CRP. Conclusion: Sleep-disordered breathing can persist after T&A and can continue to have a negative inflammatory effect. HS-CRP and IL-23 may serve as blood markers for the persistence of sleep-disordered breathing after T&A.

Background: Children with attention-deficit/hyperactivity disorder (ADHD), a neurobehavioral disorder, display behaviors of inattention, hyperactivity, or impulsivity, which can affect their ability to learn and establish proper family and social relationships. Various tools are currently used by child and adolescent psychiatric clinics to diagnose, evaluate, and collect information and data. The tools allow professional physicians to assess if patients need further treatment, following a thorough and careful clinical diagnosis process. Objective: We aim to determine potential indicators extracted from a mobile electroencephalography (EEG) device (Mindset; NeuroSky) and an actigraph (MotionWatch 8; CamNtech) and to validate them for diagnosis of ADHD. The 3 indicators are (1) attention, measured by the EEG; (2) meditation, measured by the EEG; and (3) activity, measured by the actigraph. Methods: A total of 63 participants were recruited. The case group comprised 40 boys and 9 girls, while the control group comprised 5 boys and 9 girls. The groups were age matched. The test was divided into 3 stages-pretest, in-test, and posttest-with a testing duration of 20 minutes each. We used correlation analysis, repeated measures analysis of variance, and regression analysis to investigate which indicators can be used for ADHD diagnosis. Results: With the EEG indicators, the analysis results show a significant correlation of attention with both hit reaction time (RT) interstimulus interval (ISI) change (r=-0.368; P=.003) and hit standard error (SE) ISI change (r=-0.336; P=.007). This indicates that the higher the attention of the participants, the smaller both the hit RT change and the hit SE ISI change. With the actigraph indicator, confidence index (r=0.352; P=.005), omissions (r=0.322; P=.01), hit RT SE (r=0.393; P=.001), and variability (r=0.351; P=.005) were significant. This indicates that the higher the activity amounts, the higher the impulsive behavior of the participants and the more target omissions in the continuous performance test (CPT). The results show that the participants with ADHD present a significant difference in activity amounts (P<0.001). The actigraph outperforms the EEG in screening ADHD. Conclusions: When the participants with ADHD are stimulated under restricted conditions, they will present different amounts of activity than in unrestricted conditions due to participants' inability to exercise control over their concentration. This finding could be a new electronic physiological biomarker of ADHD. An actigraph can be used to detect the amount of activity exhibited and to help physicians diagnose the disorder in order to develop more objective, rapid auxiliary diagnostic tools.

The purpose of this article was to describe the development and preliminary effectiveness of a digital case management education program. The e-learning program was built through the collaboration of a nurse educator and an informatics professor. The program was then developed according to the following steps: (1) building a visual interface, (2) scripting each unit, (3) preparing the course material and assessment tests, (4) using teaching software to record audio and video courses, (5) editing the audio recordings, (6) using instructional media or hyperlinks to finalize the interactions, (7) creating the assessment and obtaining feedback, and (8) testing the overall operation. The digital program consisted of five learning modules, self-assessment questions, learning cases, sharing experiences, and learning resources. Forty nurses participated in this study and fully completed the questionnaires both before and after the program. The knowledge and confidence levels in the experimental group were significantly higher over time than those of the comparison group. The results supported the use of educational technology to provide a more flexible and effective presentation method for continuing education programs.