To explore the reasons for low levels of physical activity in obese/overweight children and adolescents and to propose appropriate strategies to promote their physical activity (PA). This review ...followed the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines by searching and analyzing the literature of studies related to physical activity in obese/overweight children and adolescents published between January 2003 and January 2023 in Web of Science, Scopus, and PubMed databases. A total of 31 relevant studies were included for analysis, of which 16 were quantitative and 15 qualitative. According to these studies, the PA of obese/overweight children and adolescents is mainly constrained by negative factors: Individual, interpersonal, and environmental. Among these factors, low levels of individual motivation and psychological sensitivity and vulnerability, lack of family support, negative social feedback, insufficient protection from government policies, and inadequate support from the built environment are the main reasons that constrain their PA. The promotion of PA in obese/overweight children and adolescents, who are subject to more constraints at all levels, requires a system of security that involves the government, the community, the school, and the family to address the problems they encounter and enhance the sustainability of engagement in PA.
The development and innovation of biomechanical measurement methods provide a solution to the problems in ski jumping research. At present, research on ski jumping mostly focuses on the local ...technical characteristics of different phases, but studies on the technology transition process are less.
This study aims to evaluate a measurement system (i.e. the merging of 2D video recording, inertial measurement unit and wireless pressure insole) that can capture a wide range of sport performance and focus on the key transition technical characteristics.
The application validity of the Xsens motion capture system in ski jumping was verified under field conditions by comparing the lower limb joint angles of eight professional ski jumpers during the takeoff phase collected by different motion capture systems (Xsens and Simi high-speed camera). Subsequently, the key transition technical characteristics of eight ski jumpers were captured on the basis of the aforementioned measurement system.
Validation results indicated that the joint angle point-by-point curve during the takeoff phase was highly correlated and had excellent agreement (0.966 ≤ r ≤ 0.998, P < 0.001). Joint root-mean-square error (RMSE) differences between model calculations were 5.967° for hip, 6.856° for knee and 4.009° for ankle.
Compared with 2D video recording, the Xsens system shows excellent agreement to ski jumping. Furthermore, the established measurement system can effectively capture the key transition technical characteristics of athletes, particularly in the dynamic changes of straight turn into arc in inrun, the adjustment of body posture and ski movement during early flight and landing preparation.
BACKGROUNDExercise is a promising nonpharmacological treatment for improving depression in older adults with MCI, but it is unclear which exercises are most effective. The objectives of this study ...were to compare and rank the effectiveness of various exercise interventions for depression in mild cognitive impairment (MCI) and to investigate the effects of exercise on depression.METHODSThe PRISMA-NMA guidelines were applied to the development and reporting of review criteria. The Cochrane Library, Web of Science, PsycINFO, PubMed, EMBASE, CINAHL, and Scopus databases were systematically searched by combining search terms for randomized controlled trial studies (RCTs) published in English from individual databases with the earliest available date set to March 10, 2023. Two evaluators independently selected and evaluated eligible studies of changes in depression in older adults with MCI after an exercise intervention. A protocol for this systematic review was registered in PROSPERO (Registration number: CRD42022377052).RESULTSA network meta-analysis was conducted on 15 eligible RCTs consisting of 4271 subjects, including aerobic (n = 6), mind-body (n = 6) and multicomponent (n = 3) exercise trials. Compared to controls, mind-body exercise showed the strongest improvement in depressive symptoms (SMD = -0.63, 95% CI: -1.13, -0.14), followed by aerobic (SMD = -0.57, 95% CI: -0.88, -0.26) and multicomponent exercise (SMD = -0.53, 95% CI: -1.02, -0.03). Notably, there were no statistically significant differences between exercise types: aerobic vs. mind-body (SMD = 0.06, 95% PrI: -0.71, 0.84), multicomponent vs. mind-body (SMD = 0.11, 95% PrI: -0.75, 0.97), or multicomponent vs. aerobic (SMD = 0.04, 95% PrI: -0.771, 0.86).CONCLUSIONSIn this review, we found that mind-body exercise was most effective when compared to conventional controls and that multiple exercise modalities (aerobic, mind-body, and multicomponent exercise) had beneficial and comparable effects in reducing depressive states in older adults with MCI. These findings may guide clinical geriatric stakeholders and allied health professionals in providing more scientifically optimal exercise prescriptions for older adults with MCI. In the future, more high-quality, long-term clinical trials are needed to support the exploration of longer-term dynamic effects.
Pulse signals are widely used to evaluate the status of the human cardiovascular, respiratory, and circulatory systems. In the process of being collected, the signals are usually interfered by some ...factors, such as the spike noise and the poor-sensor-contact noise, which have severely affected the accuracy of the subsequent detection models. In recent years, some methods have been applied to processing the above noisy signals, such as dynamic time warping, empirical mode decomposition, autocorrelation, and cross-correlation. Effective as they are, those methods are complex and difficult to implement. It is also found that the noisy signals are tightly related to gross errors. The Chauvenet criterion, one of the gross error discrimination criterions, is highly efficient and widely applicable for being without the complex calculations like decomposition and reconstruction. Therefore, in this study, based on the Chauvenet criterion, a new pulse signal preprocessing method is proposed, in which adaptive thresholds are designed, respectively, to discriminate the abnormal signals caused by spike noise and poor-sensor-contact noise. 81 hours of pulse signals (with a sleep apnea annotated every 30 seconds and 9,720 segments in total) from the MIT-BIH Polysomnographic Database are used in the study, including 35 minutes of poor-sensor-contact noises and 25 minutes of spike noises. The proposed method was used to preprocess the pulse signals, in which 9,684 segments out of a total of 9,720 were correctly discriminated, and the accuracy of the method reached 99.63%. To quantitatively evaluate the noise removal effect, a simulation experiment is conducted to compare the Jaccard Similarity Coefficient (JSC) calculated before and after the noise removal, respectively, and the results show that the preprocessed signal obtains higher JSC, closer to the reference signal, which indicates that the proposed method can effectively improve the signal quality. In order to evaluate the method, three back-propagation (BP) sleep apnea detection models with the same network structure and parameters were established, respectively. Through comparing the recognition rate and the prediction rate of the models, higher rates were obtained by using the proposed method. To prove the efficiency, the comparison experiment between the proposed Chauvenet-based method and a Romanovsky-based method was conducted, and the execution time of the proposed method is much shorter than that of the Romanovsky method. The results suggest that the superiority in execution time of the Chauvenet-based method becomes more significant as the date size increases.
To solve the problem of real-time arrhythmia classification, this paper proposes a real-time arrhythmia classification algorithm using deep learning with low latency, high practicality, and high ...reliability, which can be easily applied to a real-time arrhythmia classification system. In the algorithm, a classifier detects the QRS complex position in real time for heartbeat segmentation. Then, the ECG_RRR feature is constructed according to the heartbeat segmentation result. Finally, another classifier classifies the arrhythmia in real time using the ECG_RRR feature. This article uses the MIT-BIH arrhythmia database and divides the 44 qualified records into two groups (DS1 and DS2) for training and evaluation, respectively. The result shows that the recall rate, precision rate, and overall accuracy of the algorithm’s interpatient QRS complex position prediction are 98.0%, 99.5%, and 97.6%, respectively. The overall accuracy for 5-class and 13-class interpatient arrhythmia classification is 91.5% and 75.6%, respectively. Furthermore, the real-time arrhythmia classification algorithm proposed in this paper has the advantages of practicability and low latency. It is easy to deploy the algorithm since the input is the original ECG signal with no feature processing required. And, the latency of the arrhythmia classification is only the duration of one heartbeat cycle.
The rating of perceived exertion (RPE) and surface electromyography (sEMG) describe exercise intensity subjectively and objectively, while there has been a lack of research on the relationship ...between them during dynamic contractions to predict exercise intensity, comprehensively. The purpose of this study was to establish a model of the relationship between sEMG and RPE during dynamic exercises. Therefore, 20 healthy male subjects were organized to perform an incremental load test on a cycle ergometer, and the subjects’ RPEs (Borg Scale 6–20) were collected every minute. Additionally, the sEMGs of the subjects’ eight lower limb muscles were collected. The sEMG features based on time domain, frequency domain and time–frequency domain methods were extracted, and the relationship model was established using Gaussian process regression (GPR). The results show that the sEMG and RPE of the selected lower limb muscles are significantly correlated (p < 0.05) but that they have different monotonic correlation degrees. The model that was established with all three domain features displayed optimal performance and when the RPE was 13, the prediction error was the smallest. The study is significant for lower limb muscle training strategy and quantification of training intensity from both subjective and objective aspects, and lays a foundation for sEMG further applications in rehabilitation medicine and sports training.
Problem-based learning (PBL), a pedagogical approach, is widely accepted in medical education. Manipulated by many factors, the internal motivation of learner is the most crucial determinant that ...affects the nature of the outcome, in which the influences of critical thinking (CT) remained elusive.
One hundred two third-year undergraduate medical students at Peking University were involved in this study. A Chinese version of the Critical Thinking Disposition Inventory (CTDI-CV) was used to assess the CT disposition, and the performance scores of students in PBL tutorials were compiled. A parametric bivariate correlation analysis was performed between the students' CT scores and their PBL average scores. The PBL scores were compared between the strong and weak CT disposition groups using independent t-test. The analysis of numerical data was conducted using SPSS 16.0.
CT disposition of third-year undergraduate medical students at Peking University was at a positive level, with an average score of 297.72. The total CT scores had a positive correlation with the scores of the PBL performance and its five dimensions significantly. In the majority, students with Strong-CT disposition obtained higher scores in PBL tutorials compared with students with Weak-CT disposition. The performance of these two groups was significantly different in the Late-Half but not in the Early-Half PBL tutorials. Furthermore, a significant improvement was observed in the students with strong CT but not weak CT dispositions.
CT disposition positively correlates to a students' PBL performance. Students with stronger CT dispositions perform better in the PBL process and obtain higher scores. Our work suggested that the open-mindedness of the CT disposition is the primary factor that determines the improvement of the preparation dimensions in the PBL process.
Ultra high frequency radio frequency identification (UHF RFID)-based indoor localization technology has been a competitive candidate for context-awareness services. Previous works mainly utilize a ...simplified Friis transmission equation for simulating/rectifying received signal strength indicator (RSSI) values, in which the directional radiation of tag antenna and reader antenna was not fully considered, leading to unfavorable performance degradation. Moreover, a k-nearest neighbor (kNN) algorithm is widely used in existing systems, whereas the selection of an appropriate k value remains a critical issue. To solve such problems, this paper presents an improved kNN-based indoor localization algorithm for a directional radiation scenario, IKULDAS. Based on the gain features of dipole antenna and patch antenna, a novel RSSI estimation model is first established. By introducing the inclination angle and rotation angle to characterize the antenna postures, the gains of tag antenna and reader antenna referring to direct path and reflection paths are re-expressed. Then, three strategies are proposed and embedded into typical kNN for improving the localization performance. In IKULDAS, the optimal single fixed rotation angle is introduced for filtering a superior measurement and an NJW-based algorithm is advised for extracting nearest-neighbor reference tags. Furthermore, a dynamic mapping mechanism is proposed to accelerate the tracking process. Simulation results show that IKULDAS achieves a higher positioning accuracy and lower time consumption compared to other typical algorithms.
The particle penetration factor is an important parameter to determine the concentration of indoor particles. In this paper, a mathematical model for calculating this parameter was established by ...combining with the decay of the indoor PM
2.5
and CO
2
concentrations measured in a bedroom with an air cleaner. The convergence of the penetration factors was analyzed under different working conditions. The results show that the particle penetration factors converge to stable values within the range of 0.69 to 0.84 close to the value from the empirical formula when the indoor PM
2.5
concentration decays to stable values. When the role of particle deposition is ignored, the penetration factors at the low and middle airflow modes are 0.78 and 0.69, respectively. The particle penetration factors are mainly determined by the clean air delivery rate (CADR) of the air cleaner, clearance airflow, and I/O ratio during the balanced phase when the roles of indoor particle deposition and exfiltration can be ignored. This work can provide a convenient method for the calculation of the particle penetration factor.
Vulvar metastasis of colorectal cancer (CRC) and acquired resistance to cetuximab is a very rare phenomenon. To our knowledge, few cases have been reported in the English literatures.
A 55-year-old ...woman was diagnosed as adenocarcinoma of the rectum and the primary tumor was detected to be Kirsten-RAS (KRAS) wild type.
The patient was diagnosed with rectal adenocarcinoma by colonoscopy. Positron emission tomography/computed tomography (PET-CT) revealed multiple lymph node and bone metastases.
The patient received a first-line course of palliative chemotherapy with FOLFOX combined with cetuximab.
After an initial response, acquired resistance to cetuximab occurred and vulvar metastasis was established by a second biopsy. Further molecular analysis showed that the KRAS mutation was detected in plasma samples and tumor tissues.
Vulvar metastasis from CRC is relatively rare and indicates a poor prognosis. Routine physical examinations of cutaneous and subcutaneous may facilitate early detection of metastases and timely intervention of medical technology. Moreover, combining serial tumor biopsy, liquid biopsy, and radiologic imaging could help to define mechanisms of drug resistance and to guide selection of therapeutic strategies.
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