Electroencephalography (EEG) is a non-invasive technique used to record the brain’s evoked and induced electrical activity from the scalp. Artificial intelligence, particularly machine learning (ML) and deep learning (DL) algorithms, are increasingly being applied to EEG data for pattern analysis, group membership classification, and brain-computer interface purposes. This study aimed to systematically review recent advances in ML and DL supervised models for decoding and classifying EEG signals. Moreover, this article provides a comprehensive review of the state-of-the-art techniques used for EEG signal preprocessing and feature extraction. To this end, several academic databases were searched to explore relevant studies from the year 2000 to the present. Our results showed that the application of ML and DL in both mental workload and motor imagery tasks has received substantial attention in recent years. A total of 75% of DL studies applied convolutional neural networks with various learning algorithms, and 36% of ML studies achieved competitive accuracy by using a support vector machine algorithm. Wavelet transform was found to be the most common feature extraction method used for all types of tasks. We further examined the specific feature extraction methods and end classifier recommendations discovered in this systematic review.

The COVID-19 pandemic and the social distancing implemented shortly after influence physical activity levels (PALs). The purpose of this investigation was to evaluate the changes in PAL and factors associated with PALs among Croatian adolescents while considering the impact of community (urban vs. rural living environment). The sample included 823 adolescents (mean age: 16.5 ± 2.1 years) who were tested on baseline (from October 2019 to March 2020; before COVID-19 pandemic in Croatia) and follow-up (in April 2020; during the COVID-19 pandemic and imposed rules of social distancing). Baseline testing included anthropometrics, physical fitness status, and evaluation of PALs, while follow-up included only PALs (evaluated by a standardized questionnaire through an internet application). The results showed a significant influence of the living environment on the decrease of PAL, with a larger decrease in urban adolescents. Logistic regression showed a higher likelihood for normal PALs at baseline in adolescents who had better fitness status, with no strong confounding effect of the urban/rural environment. The fitness status of urban adolescents predicted their PALs at follow-up. The differences between urban and rural adolescents with regard to the established changes in PALs and relationships between the predictors and PALs are explained by the characteristics of the living communities (lack of organized sports in rural areas), and the level of social distancing in the studied period and region/country.

In recent years, there has been significant interest in developing system dynamics simulation models to analyze complex healthcare problems. However, there is a lack of studies seeking to summarize the available papers in healthcare and present evidence on the effectiveness of system dynamics simulation in this area. The present paper draws on a systematic selection of published literature from 2000 to 2019, in order to form a comprehensive view of current applications of system dynamics methodology that address complex healthcare issues. The results indicate that the application of system dynamics has attracted significant attention from healthcare researchers since 2013. To date, articles on system dynamics have focused on a variety of healthcare topics. The most popular research areas among the reviewed papers included the topics of patient flow, obesity, workforce demand, and HIV/AIDS. Finally, the quality of the included papers was assessed based on a proposed ranking system, and ways to improve the system dynamics models’ quality were discussed.

Whole-body vibration (WBV) is an exercise modality or treatment/prophylaxis method in which subjects (humans, animals, or cells) are exposed to mechanical vibrations through a vibrating platform or device. The vibrations are defined by their direction, frequency, magnitude, duration, and the number of daily bouts. Subjects can be exposed while performing exercises, hold postures, sitting, or lying down. Worldwide, WBV has attracted significant attention, and the number of studies is rising. To interpret, compare, and aggregate studies, the correct, complete, and consistent reporting of WBV-specific data (WBV parameters) is critical. Specific reporting guidelines aid in accomplishing this goal. There was a need to expand existing guidelines because of continuous developments in the field of WBV research, including but not limited to new outcome measures regarding brain function and cognition, modified designs of WBV platforms and attachments (e.g., mounting a chair on a platform), and comparisons of animal and cell culture studies with human studies. Based on Delphi studies among experts and using EQUATOR recommendations, we have developed extended reporting guidelines with checklists for human and animal/cell culture research, including information on devices, vibrations, administration, general protocol, and subjects. In addition, we provide explanations and examples of how to report. These new reporting guidelines are specific to WBV variables and do not target research designs in general. Researchers are encouraged to use the new WBV guidelines in addition to general design-specific guidelines.

The validity of an accelerometric system (Myotest©) for assessing vertical jump height, vertical force and power, leg stiffness and reactivity index was examined. 20 healthy males performed 3×"5 hops in place", 3×"1 squat jump" and 3× "1 countermovement jump" during 2 test-retest sessions. The variables were simultaneously assessed using an accelerometer and a force platform at a frequency of 0.5 and 1 kHz, respectively. Both reliability and validity of the accelerometric system were studied. No significant differences between test and retest data were found (p < 0.05), showing a high level of reliability. Besides, moderate to high intraclass correlation coefficients (ICCs) (from 0.74 to 0.96) were obtained for all variables whereas weak to moderate ICCs (from 0.29 to 0.79) were obtained for force and power during the countermovement jump. With regards to validity, the difference between the two devices was not significant for 5 hops in place height (1.8 cm), force during squat (-1.4 N · kg(-1)) and countermovement (0.1 N · kg(-1)) jumps, leg stiffness (7.8 kN · m(-1)) and reactivity index (0.4). So, the measurements of these variables with this accelerometer are valid, which is not the case for the other variables. The main causes of non-validity for velocity, power and contact time assessment are temporal biases of the takeoff and touchdown moments detection.

Beneficial effects are associated with whole-body vibration exercises (WBVEs). Increases in muscular strength/power, flexibility, and gait speed; improvements in bone mineral density, balance, and the quality of life; and decreased pain and risk of falls are reported. The aim is to present a review about the importance of WBVE for elderly individuals, considering clinical studies and meta-analyses, on bone and muscle strength/power. There is evidence supporting beneficial effect of WBVE in postmenopausal women (PW); however, effects in PW with osteoporosis are unclear. Age-related decrease in muscle mass and function contribute to undesirable health conditions, including death risk. The WBVEs improve muscle strength/power, functional independence measure, balance, and various fall risk factors, and mobility, measured by Timed Up and Go test, increased significantly after WBVE. An explanation for the absence of positive effects in some outcomes could be related to discrepancies in WBVE protocols as well as the populations tested. It is concluded that WBVE is effective for counteracting the loss of muscle strength associated with sarcopenia in elderly individuals. Balance and leg and plantar flexor strength improvements due to WBV indicate benefit to reduce risk and incidence of falls, frailty, and fracture risks. However, long-term feasibility of WBVE for musculoskeletal and bone health in elderly individuals needs further investigation.