Investigating attentional processes in depressive-like domestic horses (Equus caballus).

Some captive/domestic animals respond to confinement by becoming inactive and unresponsive to external stimuli. Human inactivity is one of the behavioural markers of clinical depression, a mental disorder diagnosed by the co-occurrence of symptoms including deficit in selective attention. Some riding horses display 'withdrawn' states of inactivity and low responsiveness to stimuli that resemble the reduced engagement with their environment of some depressed patients. We hypothesized that 'withdrawn' horses experience a depressive-like state and evaluated their level of attention by confronting them with auditory stimuli. Five novel auditory stimuli were broadcasted to 27 horses, including 12 'withdrawn' horses, for 5 days. The horses' reactions and durations of attention were recorded. Non-withdrawn horses reacted more and their attention lasted longer than that of withdrawn horses on the first day, but their durations of attention decreased over days, but those of withdrawn horses remained stable. These results suggest that the withdrawn horses' selective attention is altered, adding to already evidenced common features between this horses' state and human depression

#Scanners: exploring the control of adaptive films using brain-computer interaction

This paper explores the design space of bio-responsive entertainment, in this case using a film that responds to the brain and blink data of users. A film was created with four parallel channels of footage, where blinking and levels of attention and meditation, as recorded by a commercially available EEG device, affected which footage participants saw. As a performance-led piece of research in the wild, this experience, named #Scanners, was presented at a week long national exhibition in the UK. We examined the experiences of 35 viewers, and found that these forms of partially-involuntary control created engaging and enjoyable, but sometimes distracting, experiences. We translate our findings into a two-dimensional design space between the extent of voluntary control that a physiological measure can provide against the level of conscious awareness that the user has of that control. This highlights that novel design opportunities exist when deviating from these two-dimensions - when giving up conscious control and when abstracting the affect of control. Reflection on of how viewers negotiated this space during an experience reveals novel design tactics

#Scanners: exploring the control of adaptive films using brain-computer interaction

This paper explores the design space of bio-responsive entertainment, in this case using a film that responds to the brain and blink data of users. A film was created with four parallel channels of footage, where blinking and levels of attention and meditation, as recorded by a commercially available EEG device, affected which footage participants saw. As a performance-led piece of research in the wild, this experience, named #Scanners, was presented at a week long national exhibition in the UK. We examined the experiences of 35 viewers, and found that these forms of partially-involuntary control created engaging and enjoyable, but sometimes distracting, experiences. We translate our findings into a two-dimensional design space between the extent of voluntary control that a physiological measure can provide against the level of conscious awareness that the user has of that control. This highlights that novel design opportunities exist when deviating from these two-dimensions - when giving up conscious control and when abstracting the affect of control. Reflection on of how viewers negotiated this space during an experience reveals novel design tactics

INTERACTIVE LIGHTING TO MAINTAIN CONCENTRATION: SALMAN AL FARISI BANDUNG FULL-DAY SCHOOL

Nowadays, the times affect the development of the education system for children. Full-time employment parents and the problem of leaving their children unattended and without essential activities are reasons full-day schools are in great demand. The learning conditions for a relatively long time and the various activities implemented in this full-day school affect the need for unique facilities compared to other schools, especially in maintaining children’s concentration in learning. This research uses a literature review, field surveys, and interviews with case studies of Salman Al Farisi Elementary School, a pioneer of full-day school in Bandung with an integrated Islamic education concept. Lighting is an interior architecture element that mainly affects student concentration in the classroom. Due to the existing problems, an interactive lighting system must be implemented in Salman Al Farisi Elementary School classrooms to support activities and maintain student concentration in learning. Arduino devices as artificial intelligence tools have the potential to be used in Salman Al Farisi Elementary School classrooms to create an interactive lighting system. The interactive lighting system required is the adjustable room light to maintain student concentration according to the ongoing activity

Logging Stress and Anxiety Using a Gamified Mobile-based EMA Application, and Emotion Recognition Using a Personalized Machine Learning Approach

According to American Psychological Association (APA) more than 9 in 10 (94 percent) adults believe that stress can contribute to the development of major health problems, such as heart disease, depression, and obesity. Due to the subjective nature of stress, and anxiety, it has been demanding to measure these psychological issues accurately by only relying on objective means. In recent years, researchers have increasingly utilized computer vision techniques and machine learning algorithms to develop scalable and accessible solutions for remote mental health monitoring via web and mobile applications. To further enhance accuracy in the field of digital health and precision diagnostics, there is a need for personalized machine-learning approaches that focus on recognizing mental states based on individual characteristics, rather than relying solely on general-purpose solutions. This thesis focuses on conducting experiments aimed at recognizing and assessing levels of stress and anxiety in participants. In the initial phase of the study, a mobile application with broad applicability (compatible with both Android and iPhone platforms) is introduced (we called it STAND). This application serves the purpose of Ecological Momentary Assessment (EMA). Participants receive daily notifications through this smartphone-based app, which redirects them to a screen consisting of three components. These components include a question that prompts participants to indicate their current levels of stress and anxiety, a rating scale ranging from 1 to 10 for quantifying their response, and the ability to capture a selfie. The responses to the stress and anxiety questions, along with the corresponding selfie photographs, are then analyzed on an individual basis. This analysis focuses on exploring the relationships between self-reported stress and anxiety levels and potential facial expressions indicative of stress and anxiety, eye features such as pupil size variation and eye closure, and specific action units (AUs) observed in the frames over time. In addition to its primary functions, the mobile app also gathers sensor data, including accelerometer and gyroscope readings, on a daily basis. This data holds potential for further analysis related to stress and anxiety. Furthermore, apart from capturing selfie photographs, participants have the option to upload video recordings of themselves while engaging in two neuropsychological games. These recorded videos are then subjected to analysis in order to extract pertinent features that can be utilized for binary classification of stress and anxiety (i.e., stress and anxiety recognition). The participants that will be selected for this phase are students aged between 18 and 38, who have received recent clinical diagnoses indicating specific stress and anxiety levels. In order to enhance user engagement in the intervention, gamified elements - an emerging trend to influence user behavior and lifestyle - has been utilized. Incorporating gamified elements into non-game contexts (e.g., health-related) has gained overwhelming popularity during the last few years which has made the interventions more delightful, engaging, and motivating. In the subsequent phase of this research, we conducted an AI experiment employing a personalized machine learning approach to perform emotion recognition on an established dataset called Emognition. This experiment served as a simulation of the future analysis that will be conducted as part of a more comprehensive study focusing on stress and anxiety recognition. The outcomes of the emotion recognition experiment in this study highlight the effectiveness of personalized machine learning techniques and bear significance for the development of future diagnostic endeavors. For training purposes, we selected three models, namely KNN, Random Forest, and MLP. The preliminary performance accuracy results for the experiment were 93%, 95%, and 87% respectively for these models

Astigmatism and Pseudoaccommodation in Pseudophakic Eyes

noAdvanced IOLs with circumferential zones of different power provide pseudoaccommodation. We investigated the potential for power variation with meridian, namely astigmatism, to provide pseudo-accommodation. With appropriate power and axis orientations, acceptable pseudo-accommodation can be achieved

Human–Machine Interface in Transport Systems: An Industrial Overview for More Extended Rail Applications

This paper provides an overview of Human Machine Interface (HMI) design and command systems in commercial or experimental operation across transport modes. It presents and comments on different HMIs from the perspective of vehicle automation equipment and simulators of different application domains. Considering the fields of cognition and automation, this investigation highlights human factors and the experiences of different industries according to industrial and literature reviews. Moreover, to better focus the objectives and extend the investigated industrial panorama, the analysis covers the most effective simulators in operation across various transport modes for the training of operators as well as research in the fields of safety and ergonomics. Special focus is given to new technologies that are potentially applicable in future train cabins, e.g., visual displays and haptic-shared controls. Finally, a synthesis of human factors and their limits regarding support for monitoring or driving assistance is propose