Beyond mobile apps: a survey of technologies for mental well-being

Mental health problems are on the rise globally and strain national health systems worldwide. Mental disorders are closely associated with fear of stigma, structural barriers such as financial burden, and lack of available services and resources which often prohibit the delivery of frequent clinical advice and monitoring. Technologies for mental well-being exhibit a range of attractive properties, which facilitate the delivery of state-of-the-art clinical monitoring. This review article provides an overview of traditional techniques followed by their technological alternatives, sensing devices, behaviour changing tools, and feedback interfaces. The challenges presented by these technologies are then discussed with data collection, privacy, and battery life being some of the key issues which need to be carefully considered for the successful deployment of mental health toolkits. Finally, the opportunities this growing research area presents are discussed including the use of portable tangible interfaces combining sensing and feedback technologies. Capitalising on the data these ubiquitous devices can record, state of the art machine learning algorithms can lead to the development of robust clinical decision support tools towards diagnosis and improvement of mental well-being delivery in real-time

Tangible fidgeting interfaces for mental wellbeing recognition using deep learning applied to physiological sensor data

The momentary assessment of an individual's affective state is critical to the monitoring of mental wellbeing and the ability to instantly apply interventions. This thesis introduces the concept of tangible fidgeting interfaces for affective recognition from design and development through to evaluation. Tangible interfaces expand upon the affordance of familiar physical objects as the ability to touch and fidget may help to tap into individuals' psychological need to feel occupied and engaged. Embedding digital technologies within interfaces capitalises on motor and perceptual capabilities and allows for the direct manipulation of data, offering people the potential for new modes of interaction when experiencing mental wellbeing challenges. Tangible interfaces present an ideal opportunity to digitally enable physical fidgeting interactions along with physiological sensor monitoring to unobtrusively and comfortable measure non-visable changes in affective state. This opportunity initiated the investigation of factors that would bring about the designing of more effective intelligent solutions using participatory design techniques to engage people in designing solutions relevant to themselves. Adopting an artificial intelligence approach using physiological signals creates the possibility to quantify affect with high levels of accuracy. However, labelling is an indispensable stage of data pre-processing that is required before classification and can be extremely challenging with multi-model sensor data. New techniques are introduced for labelling at the point of collection coupled with a pilot study and a systematic performance comparison of five custom built labelling interfaces. When classifying labelled physiological sensor data, individual differences between people limit the generalisability of models. To address this challenge, a transfer learning approach has been developed that personalises affective models using few labelled samples. This approach to personalise models and improve cross-domain performance is completed on-device, automating the traditionally manual process, saving time and labour. Furthermore, monitoring trajectories over long periods of time inherits some critical limitations in relation to the size of the training dataset. This shortcoming may hinder the development of reliable and accurate machine learning models. A second framework has been developed to overcome the limitation of small training datasets using an image-encoding transfer learning approach. This research offers the first attempt at the development of tangible interfaces using artificial intelligence towards building a real-world continuous affect recognition system in addition to offering real-time feedback to perform as interventions. This exploration of affective interfaces has many potential applications to help improve quality of life for the wider population

Smells, well-being and the built environment

In this Research Topic, we aimed to collect a range of contributions to understand the emotional and wellbeing responses resulting from smells in different public spaces (museums, highstreets, heritage buildings, food districts, neighborhoods, squares, etc.) to inform future spatial design and management. The articles in this Research Topic are presented according to three types of contributions: reviews and conceptual analyses, empirical research in fieldwork, in laboratory studies and technological applications. Reviews and Conceptual Analyses Xiao et al. reviewed smellscape research studies conducted in the past 10 years to identify the challenges and related areas of future research, namely smell archives and databases, social justice within odor control and management, and research into advanced building materials. Spence reviewed the changing role of smells in the built environment from negative associations with sanitation to meaningful personal and cultural associations with memories and experiences which led to an evaluation of different approaches in examining the impact of smells on people's mood or wellbeing and the challenges of researching smells in the multi-sensory environment. Moving from the sick building sydrome to sick transport sydrome, Spence further reviewed the smells in transport environments as aesthetic and functional, and suggests challenges for future transportation to produce a more tangible vision to integrate smells in the design process to achieve the right balance of olfactory stimulation. Looking backwards to scented past, Bembibre and Strlič make the case for the need of knowledge exchange and interdisciplinary interpretation of findings in the field of olfactory heritage, providing an overview of methodological and museal studies as well as challenges associated with historical scent reconstruction. Empirical Research - Fieldwork Pálsdóttir et al. carried out a field study with participants suffering from stress-related mental disorders and explored how they would describe their smellscape perception of a garden in the context of a nature-based rehabilitation intervention. In a different field study, de Groot investigated whether ambient scents could affect customers' subjective experience and spending behavior in an experiment with customers of a second-hand clothing store. The author concluded that for that to happen, the smellscape should have a meaningful link to the physical context. Masaoka et al. present the results of a study conducted to examine whether continuous odor stimuli associated with autobiographical memories could activate olfactory areas in the brain of older adults and assess whether this odor stimulation could have a protective effect against age-related cognitive decline. Empirical Research - Laboratory Studies and Technological Applications Masaoka et al. investigated the potential protective effect from age-related cognitive decline of continuous odor stimuli associated with autobiographical memories and whether those could activate the above olfactory areas in older adults. Jiang et al. used blood pressure, pulse rate, EEG, POMS, and SD data to examine the odor-visual effects of the Primula forbesii Franch compared with the non-fragrant Primula malacoides Franch on the physiological and psychological state of Chinese female college students in the indoor environment. Courrèges et al. examined the correlations between odor and texture in users' perceptions of cosmetic creams cross-culturally, in laboratory conditions, using questionnaires, minimizing the impacts of branded messages from the packing and retail spaces. Amores et al. discussed the design and technical implementation of Essence- a smartphone-controlled wearable device that monitors users' EEG and real-time sleep staging algorithm to release scents to interact with users- in home-based sleep environments. The articles included in this Research Topic represent a nice balance between the theoretical reviews, empirical studies and laboratory research, showing the vibrance and dynamic in this research field as well as new technological developments such as extended reality, emotional sensors (i.e. EEG, GSR) and odor monitoring devices. New insights are drawn into the theoretical frameworks to understand relationships between smells, wellbeing and emotions, behaviors and physiological aspects; methodological approaches to measure smell triggered emotions, experiences, and quality of life; practical explorations on the process and challenges of using smells to influence user experiences in the built environment

A Systematic Review and Meta-Analysis of the Incidence of Injury in Professional Female Soccer

The epidemiology of injury in male professional football is well documented and has been used as a basis to monitor injury trends and implement injury prevention strategies. There are no systematic reviews that have investigated injury incidence in women’s professional football. Therefore, the extent of injury burden in women’s professional football remains unknown. PURPOSE: The primary aim of this study was to calculate an overall incidence rate of injury in senior female professional soccer. The secondary aims were to provide an incidence rate for training and match play. METHODS: PubMed, Discover, EBSCO, Embase and ScienceDirect electronic databases were searched from inception to September 2018. Two reviewers independently assessed study quality using the Strengthening the Reporting of Observational Studies in Epidemiology statement using a 22-item STROBE checklist. Seven prospective studies (n=1137 professional players) were combined in a pooled analysis of injury incidence using a mixed effects model. Heterogeneity was evaluated using the Cochrane Q statistic and I2. RESULTS: The epidemiological incidence proportion over one season was 0.62 (95% CI 0.59 - 0.64). Mean total incidence of injury was 3.15 (95% CI 1.54 - 4.75) injuries per 1000 hours. The mean incidence of injury during match play was 10.72 (95% CI 9.11 - 12.33) and during training was 2.21 (95% CI 0.96 - 3.45). Data analysis found a significant level of heterogeneity (total Incidence, X2 = 16.57 P < 0.05; I2 = 63.8%) and during subsequent sub group analyses in those studies reviewed (match incidence, X2 = 76.4 (d.f. = 7), P <0.05; I2 = 90.8%, training incidence, X2 = 16.97 (d.f. = 7), P < 0.05; I2 = 58.8%). Appraisal of the study methodologies revealed inconsistency in the use of injury terminology, data collection procedures and calculation of exposure by researchers. Such inconsistencies likely contribute to the large variance in the incidence and prevalence of injury reported. CONCLUSIONS: The estimated risk of sustaining at least one injury over one football season is 62%. Continued reporting of heterogeneous results in population samples limits meaningful comparison of studies. Standardising the criteria used to attribute injury and activity coupled with more accurate methods of calculating exposure will overcome such limitations