Fatigue as a key human factor in complex sociotechnical systems: Vessel Traffic Services.

Background: Vessel Traffic Services (VTS) are considered a subsystem of people, whose mission is to improve the effectiveness and efficiency of maritime transport within the maritime system. VTS operate as a control system where Vessel Traffic Services Operators (VTSOs) must cope with a complex environment to make up for safe and efficient maritime transport, so it is essential to understand how these operators maintain control through adapting to the uncertain and dynamic environment of maritime traffic. This multidisciplinary study explores how human factors within this complex sociotechnical system, means VTS, play a role in maritime safety, specifically focusing on fatigue, which is considered a key variable for VTSOs' performance. In this context, the research has focused on the assessment of fatigue with psychological and operational instruments to highlight the importance of the human element in CSSs. Objective: To study the intra and inter-individual differences in fatigue ratings and their relationships with other personal and environmental variables: mental workload, work shifts, reaction time, and hours of usual sleep. Methods: The study was conducted in two of the 19 Spanish Maritime Rescue Coordination Centers (MRCCs) with a sample of 23 active VTSOs (82.14% of the staff). Both objective and standardized subjective measures were used to assess fatigue and associated sleepiness (Borg RPE, Nasa-TLX, Stanford Sleepiness Scale, and Self-Assessment Manikin Scale). Results: A significant positive correlation between fatigue and mental workload was found, being more prevalent in the night shift, which shows a bigger variation in these variables. A significant difference was found in the increase in fatigue experienced throughout the shift depending on the hours of usual sleep, being smaller in the group of subjects reporting to sleep more. Conclusion: The human element is key to maritime safety related to Vessel Traffic Services, so it is of paramount importance to consider certain measures to counteract the negative effects of fatigue. A proper organization of duties on/off periods, assessment of work and rest schedules, and the implementation of fatigue management programs based on sleep education are recommended.

A Multirobot System in an Assisted Home Environment to Support the Elderly in Their Daily Lives.

The increasing isolation of the elderly both in their own homes and in care homes has made the problem of caring for elderly people who live alone an urgent priority. This article presents a proposed design for a heterogeneous multirobot system consisting of (i) a small mobile robot to monitor the well-being of elderly people who live alone and suggest activities to keep them positive and active and (ii) a domestic mobile manipulating robot that helps to perform household tasks. The entire system is integrated in an automated home environment (AAL), which also includes a set of low-cost automation sensors, a medical monitoring bracelet and an Android application to propose emotional coaching activities to the person who lives alone. The heterogeneous system uses ROS, IoT technologies, such as Node-RED, and the Home Assistant Platform. Both platforms with the home automation system have been tested over a long period of time and integrated in a real test environment, with good results. The semantic segmentation of the navigation and planning environment in the mobile manipulator for navigation and movement in the manipulation area facilitated the tasks of the later planners. Results about the interactions of users with the applications are presented and the use of artificial intelligence to predict mood is discussed. The experiments support the conclusion that the assistance robot correctly proposes activities, such as calling a relative, exercising, etc., during the day, according to the user's detected emotional state, making this is an innovative proposal aimed at empowering the elderly so that they can be autonomous in their homes and have a good quality of life.

Validity and reliability of a computer-assisted system method to measure axial vertebral rotation.

Background: Axial vertebral rotation and Cobb's angle are essential parameters for analysing adolescent idiopathic scoliosis. This study's scope evaluates the validity and absolute reliability of application software based on a new mathematical equation to determine the axial vertebral rotation in digital X-rays according to Raimondi's method in evaluators with different degrees of experience. Methods: Twelve independent evaluators with different experience levels measured 33 scoliotic curves in 21 X-rays with the software on three separate occasions, separated one month. Using the same methodology, the observers re-measured the same radiographic studies three months later but on X-ray films and in a conventional way. Results: Both methods show good validity and reliability, and the intraclass correlation coefficients are almost perfect. According to our results, the software increases 1.7 times the validity and 1.9 times the absolute reliability of axial vertebral rotation on digital X-rays according to Raimondi's method, compared to the conventional manual measurement. Conclusions: The intra-group and inter-group agreement of the measurements with the software shows equal or minor variations than with the manual method, among the different measurement sessions and in the three experience groups. There is almost perfect agreement between the two measurement methods, so the equation and the software may be helpful to increase the accuracy in the axial vertebral rotation assessment.

Developing of a Mathematical Model to Perform Measurements of Axial Vertebral Rotation on Computer-Aided and Automated Diagnosis Systems, Using Raimondi's Method.

INTRODUCTION: Axial vertebral rotation (AVR) is a basic parameter in the study of idiopathic scoliosis and on physical two-dimensional images. Raimondi's tables are the most used method in the quantification of AVR. The development of computing technologies has enabled the creation of computer-aided or automated diagnosis systems (CADx) with which measurement on medical images can be carried out more quickly, simply, and with less intra and interobserver variabilities than manual methods. Although there are several publications dealing with the measurement of AVR in CADx systems, none of them provides information on the equation or algorithm used for the measurement applying Raimondi's method. Goal. The aim of this work is to perform a mathematical modelling of the data contained in Raimondi's tables that enable the Raimondi method to be used in digital medical images more precisely and in a more exact manner. METHODS: Data from Raimondi's tables were tabulated on a first step. After this, each column of Raimondi's tables containing values corresponding to vertebral body width (D) were adjusted to a curve determined by AVR = f (d). Third, representative values of each rotation divided by D were obtained through the equation of each column D. In a fourth step, a regression line was fitted to the data in each row, and from its equation, the mean value of the D/d distribution is calculated (value corresponding to the central column, D = 45). Finally, a curve was adjusted to the obtained data using the least squares method. Summary and Conclusion. Our mathematical equation allows the Raimondi method to be used in digital images of any format in a more accurate and simplified approach. This equation can be easily and freely implemented in any CADx system to quantify AVR, providing a more precise use of Raimondi's method, as well as being used in traditional manual measurement as it is performed with Raimondi tables.

Validation of Electroencephalographic Recordings Obtained with a Consumer-Grade, Single Dry Electrode, Low-Cost Device: A Comparative Study.

The functional validity of the signal obtained with low-cost electroencephalography (EEG) devices is still under debate. Here, we have conducted an in-depth comparison of the EEG-recordings obtained with a medical-grade golden-cup electrodes ambulatory device, the SOMNOwatch + EEG-6, vs those obtained with a consumer-grade, single dry electrode low-cost device, the NeuroSky MindWave, one of the most affordable devices currently available. We recorded EEG signals at Fp1 using the two different devices simultaneously on 21 participants who underwent two experimental phases: a 12-minute resting state task (alternating two cycles of closed/open eyes periods), followed by 60-minute virtual-driving task. We evaluated the EEG recording quality by comparing the similarity between the temporal data series, their spectra, their signal-to-noise ratio, the reliability of EEG measurements (comparing the closed eyes periods), as well as their blink detection rate. We found substantial agreement between signals: whereas, qualitatively, the NeuroSky MindWave presented higher levels of noise and a biphasic shape of blinks, the similarity metric indicated that signals from both recording devices were significantly correlated. While the NeuroSky MindWave was less reliable, both devices had a similar blink detection rate. Overall, the NeuroSky MindWave is noise-limited, but provides stable recordings even through long periods of time. Furthermore, its data would be of adequate quality compared to that of conventional wet electrode EEG devices, except for a potential calibration error and spectral differences at low frequencies.

Monitoring driver fatigue using a single-channel electroencephalographic device: A validation study by gaze-based, driving performance, and subjective data.

Driver fatigue can impair performance as much as alcohol does. It is the most important road safety concern, causing thousands of accidents and fatalities every year. Thanks to technological developments, wearable, single-channel EEG devices are now getting considerable attention as fatigue monitors, as they could help drivers to assess their own levels of fatigue and, therefore, prevent the deterioration of performance. However, the few studies that have used single-channel EEG devices to investigate the physiological effects of driver fatigue have had inconsistent results, and the question of whether we can monitor driver fatigue reliably with these EEG devices remains open. Here, we assessed the validity of a single-channel EEG device (TGAM-based chip) to monitor changes in mental state (from alertness to fatigue). Fifteen drivers performed a 2-h simulated driving task while we recorded, simultaneously, their prefrontal brain activity and saccadic velocity. We used saccadic velocity as the reference index of fatigue. We also collected subjective ratings of alertness and fatigue, as well as driving performance. We found that the power spectra of the delta EEG band showed an inverted U-shaped quadratic trend (EEG power spectra increased for the first hour and half, and decreased during the last thirty minutes), while the power spectra of the beta band linearly increased as the driving session progressed. Coherently, saccadic velocity linearly decreased and speeding time increased, suggesting a clear effect of fatigue. Subjective data corroborated these conclusions. Overall, our results suggest that the TGAM-based chip EEG device is able to detect changes in mental state while performing a complex and dynamic everyday task as driving.