Cloud Server and Internet of Things Assisted System for Stress Monitoring

Currently, the Internet of Things (IoT) has gained attention for its capability for real-time monitoring. The advancement in sensor and wireless communication technology has led to the widespread adoption of IoT technology in distinct applications. The cloud server, in conjunction with the IoT, enables the visualization and analysis of real-time sensor data. The literature concludes that there is a lack of remote stress-monitoring devices available to assist doctors in observing the real-time stress status of patients in the hospital and in rehabilitation centers. To overcome this problem, we have proposed the use of the IoT and cloud-enabled stress devices to detect stress in a real-time environment. The IoT-enabled stress device establishes piconet communication with the master node to allow visualization of the sensory data on the cloud server. The threshold value (volt) for real-time stress detection by the stress device is identified by experimental analysis using MATLAB based on the results obtained from the performance of three different physical-stress generating tasks. In addition, the stress device is interfaced with the cloud server, and the sensor data are recorded on the cloud server. The sensor data logged into the cloud server can be utilized for future analysis.

Fatigue Life Assessment of Tower Crane Based on Neural Network to Obtain Stress Spectrum

In order to reduce the probability of crane safety accidents, a method based on radial basis neural network is proposed to quickly obtain the stress spectrum and calculate the remaining life of the crane. Firstly, taking an in-service tower crane as an example, an ANSYS finite element model is established based on actual parameters, and the finite element model is statically analyzed to obtain the location of the dangerous point. Secondly, the typical operating conditions of the crane are simulated. The position of the trolley and the lifting load are used as the input layer while the equivalent stress value at any point is used as the output layer to train the radial basis neural network model. Using the trained radial basis neural network model can obtain time-stress curve at any point quickly. Finally the remaining life is assessed based on the fracture mechanics method. The results show that this method that using the radial basis function neural network model to obtain the time-stress curve at any point can greatly save the cumbersome process and a lot of investment in the field measurement of the crane, and also provides a reliable basis for the long-term safe use and later maintenance of the crane.

Animal welfare during transport and slaughter of beef cattle

Objective: To review how transport and stunning of cattle affect animal welfare. Approach: During the transport of beef cattle to slaughter plants, several factors affect animal welfare, such as travel time, stress, and load density. Additionally, the correct stunning of cattle helps comply with the animal welfare guidelines established by different protocols such as Welfare Quality®. Study limitations/Implications: Meat quality is affected by several factors, being of utmost importance the way animals are transported to the slaughterhouse, and they are stunned. Therefore, it is critical to perform these stages properly to obtain good quality meat; besides, it is a welfare issue. Conclusions: It is critical to comply with transport and slaughter procedures that guarantee good beef meat quality and ensure animal welfare to avoid stress in cattle as possible.

Single-item measures of stress during work- and private time in healthcare workers

BACKGROUND: While the psychosocial work environment within the hospital sector is a topic of great debate, surveys assessing stress often do not differentiate between stress related to work- and private life. Identifying risk factors associated with these domains of daily life would help improve policies as well as target relevant treatment options. Therefore, the aim of this study was to evaluate associations between stress during to work- and private time with Cohen’s Perceived Stress Scale (CPSS). METHODS: Perceived stress was assessed by the full version of CPSS (scores 0–40) as well as by two single-item questions related to stress related to work- and private life, respectively. Associations between these single-items and CPSS were modelled using general linear models controlling for lifestyle factors. RESULTS: Overall, stress due to both work- and private time was strongly associated with CPSS scores. In the full population (n = 3,600), “never experiencing stress” during both work- and private time was associated with low stress scores (6.0, 95%CI 5.1–6.9). “Never experiencing” work-related stress but experiencing private time stress “very often” was associated with high stress scores (22.4, CI 19.8–25.1). Likewise, experiencing work-related stress “very often” but “never experiencing” private time stress was also associated with high stress scores (22.2, CI 20.3–24.2). Lastly, Spearman’s r between the full CPSS and the two single-item questions about work- and private time stress were 0.62 (p < 0.0001) and 0.52 (p < 0.0001), respectively, while the two items were only weakly correlated (r = 0.32). CONCLUSION: The present study shows that perceived stress due to both work and private time is strongly associated with Cohen’s Perceived Stress Scale scores. The results illustrate the feasibility of using single-item questions related to work- and private time in identifying domain-specific risk factors for psychosocial stress.

Study of Effective Corridor Design to Improve Wayfinding in Underground Malls

In retail space, wayfinding difficulties can cause problems, such as loss of time, stress, or discomfort, negatively affecting the shopping experience of consumers and even their patronage intentions. Although studies have reported that space configuration may facilitate navigation, there has been a lack of detailed discussion, particularly in underground malls, where people often encounter wayfinding issues. In this study, a series of exit-finding tasks in virtual malls were simulated to determine if it was practical to encourage turn taking by changing the corridor width, length, height, or angle. The results showed that people have a right-turn preference during exit finding. Moreover, exit-finders mostly prefer taking the upward pathway via stairs followed by corridors with broader widths or curved corners, exhibiting visible and similar navigation effects. Shorter corridors have a visible but relatively small affinity. This study provides some empirical evidence of how the corridor configuration influences the turn taking of people and provides a theoretical reference for adding a guiding function to the spatial arrangement in underground malls.

Decision-Making and Multisensory Combination Under Time Stress

Using a video game platform, we examined how vision-based decision making was affected by a concurrent, potentially conflicting auditory stimulus. Electroencephalographic responses showed that by 150 milliseconds of stimulus onset, the brain had detected the conflict between visual and auditory stimuli. Systematically reducing the intertrial interval (ITI), which subjects described as stressful, undermined decision making. Subjects’ arterial pulse variance decreased along with ITI, signaling increased parasympathetic influence on the heart. When successive trials required a shift in processing mode, short ITIs significantly boosted one trial’s influence on the next, suggesting that stress reduces cognitive flexibility. Finally, our study demonstrates the heart’s and the brain’s important influence on decision making.