Detection of psychological stress using a hyperspectral imaging technique

The detection of stress at early stages is beneficial to both individuals and communities. However, traditional stress detection methods that use physiological signals are contact-based and require sensors to be in contact with test subjects for measurement. In this paper, we present a method to detect psychological stress in a non-contact manner using a human physiological response. In particular, we utilize a hyperspectral imaging (HSI) technique to extract the tissue oxygen saturation (StO2) value as a physiological feature for stress detection. Our experimental results indicate that this new feature may be independent from perspiration and ambient temperature. Trier Social Stress Tests (TSSTs) on 21 volunteers demonstrated a significant difference p\< 0.005 and a large practical discrimination (d 1/4 1.37) between normalized baseline and stress StO2 levels. The accuracy for stress recognition from baseline using a binary classifier was 76.19 and 88.1 percent for the automatic and manual selections of the classifier threshold, respectively. These results suggest that the StO2 level could serve as a new modality to recognize stress at standoff distances

A Comparative Evaluation of Heart Rate Estimation Methods using Face Videos

This paper presents a comparative evaluation of methods for remote heart rate estimation using face videos, i.e., given a video sequence of the face as input, methods to process it to obtain a robust estimation of the subjects heart rate at each moment. Four alternatives from the literature are tested, three based in hand crafted approaches and one based on deep learning. The methods are compared using RGB videos from the COHFACE database. Experiments show that the learning-based method achieves much better accuracy than the hand crafted ones. The low error rate achieved by the learning based model makes possible its application in real scenarios, e.g. in medical or sports environments.Comment: Accepted in "IEEE International Workshop on Medical Computing (MediComp) 2020

TensiStrength: Stress and relaxation magnitude detection for social media texts

Computer systems need to be able to react to stress in order to perform optimally on some tasks. This article describes TensiStrength, a system to detect the strength of stress and relaxation expressed in social media text messages. TensiStrength uses a lexical approach and a set of rules to detect direct and indirect expressions of stress or relaxation, particularly in the context of transportation. It is slightly more effective than a comparable sentiment analysis program, although their similar performances occur despite differences on almost half of the tweets gathered. The effectiveness of TensiStrength depends on the nature of the tweets classified, with tweets that are rich in stress-related terms being particularly problematic. Although generic machine learning methods can give better performance than TensiStrength overall, they exploit topic-related terms in a way that may be undesirable in practical applications and that may not work as well in more focused contexts. In conclusion, TensiStrength and generic machine learning approaches work well enough to be practical choices for intelligent applications that need to take advantage of stress information, and the decision about which to use depends on the nature of the texts analysed and the purpose of the task

Stress, indici psicofisiologici e applicazioni in ambito lavorativo

Lo stress è una condizione intrinseca alla vita dell'uomo, se permane comporta delle conseguenze alla salute. La ricerca oggi utilizza la psicofisiologia per la misurazione oggettiva dello stress e studia i suoi metodi di rilevazione in ambito lavorativo. A questo proposito le ultime evidenze valorizzano l'efficienza dell'utilizzo di dispositivi indossabili sul lavoro come metodo efficace di valutazione dello stress lavoro correlato

Analysis and design of individual information systems to support health behavior change

As a wide-ranging socio-technical transformation, the digitalization has significantly influenced the world, bringing opportunities and challenges to our lives. Despite numerous benefits like the possibility to stay connected with people around the world, the increasing dispersion and use of digital technologies and media (DTM) pose risks to individuals’ well-being and health. Rising demands emerging from the digital world have been linked to digital stress, that is, stress directly or indirectly resulting from DTM (Ayyagari et al. 2011; Ragu-Nathan et al. 2008; Tarafdar et al. 2019; Weil and Rosen 1997), potentially intensifying individuals’ overall exposure to stress. Individuals experiencing this adverse consequence of digitalization are at elevated risk of developing severe mental health impairments (Alhassan et al. 2018; Haidt and Allen 2020; Scott et al. 2017), which is why various scholars emphasize that research should place a stronger focus on analyzing and shaping the role of the individual in a digital world, pursuing instrumental as well as humanistic objectives (Ameen et al. 2021; Baskerville 2011b). Information Systems (IS) research has long placed emphasis on the use of information and communication technology (ICT) in organizations, viewing an information system as the socio-technical system that emerges from individuals’ interaction with DTM in organizations. However, socio-technical information systems, as the essence of the IS discipline (Lee 2004; Sarker et al. 2019), are also present in different social contexts from private life. Acknowledging the increasing private use of DTM, such as smartphones and social networks, IS scholars have recently intensified their efforts to understand the human factor of IS (Avison and Fitzgerald 1991; Turel et al. 2021). A framework recently proposed by Matt et al. (2019) suggests three research angles: analyzing individuals’ behavior associated with their DTM use, analyzing what consequences arise from their DTM use behavior, and designing new technologies that promote positive or mitigate negative effects of individuals’ DTM use. Various recent studies suggest that individuals’ behavior seems to be an important lever influencing the outcomes of their DTM use (Salo et al. 2017; Salo et al. 2020; Weinstein et al. 2016). Therefore, this dissertation aims to contribute to IS research targeting the facilitation of a healthy DTM use behavior. It explores the use behavior, consequences, and design of DTM for individuals' use with the objective to deliver humanistic value by increasing individuals' health through supporting a behavior change related to their DTM use. The dissertation combines behavioral science and design science perspectives and applies pluralistic methodological approaches from qualitative (e.g., interviews, prototyping) and quantitative research (e.g., survey research, field studies), including mixed-methods approaches mixing both. Following the framework from Matt et al. (2019), the dissertation takes three perspectives therein: analyzing individuals’ behavior, analyzing individuals’ responses to consequences of DTM use, and designing information systems assisting DTM users. First, the dissertation presents new descriptive knowledge on individuals’ behavior related to their use of DTM. Specifically, it investigates how individuals behave when interacting with DTM, why they behave the way they do, and how their behavior can be influenced. Today, a variety of digital workplace technologies offer employees different ways of pursuing their goals or performing their tasks (Köffer 2015). As a result, individuals exhibit different behaviors when interacting with these technologies. The dissertation analyzes what interactional roles DTM users can take at the digital workplace and what may influence their behavior. It uses a mixed-methods approach and combines a quantitative study building on trace data from a popular digital workplace suite and qualitative interviews with users of this digital workplace suite. The empirical analysis yields eight user roles that advance the understanding of users’ behavior at the digital workplace and first insights into what factors may influence this behavior. A second study adds another perspective and investigates how habitual behavior can be changed by means of DTM design elements. Real-time feedback has been discussed as a promising way to do so (Schibuola et al. 2016; Weinmann et al. 2016). In a field experiment, employees working at the digital workplace are provided with an external display that presents real-time feedback on their office’s indoor environmental quality. The experiment examines if and to what extent the feedback influences their ventilation behavior to understand the effect of feedback as a means of influencing individuals’ behavior. The results suggest that real-time feedback can effectively alter individuals’ behavior, yet the feedback’s effectiveness reduces over time, possibly as a result of habituation to the feedback. Second, the dissertation presents new descriptive and prescriptive knowledge on individuals’ ways to mitigate adverse consequences arising from the digitalization of individuals. A frequently discussed consequence that digitalization has on individuals is digital stress. Although research efforts strive to determine what measures individuals can take to effectively cope with digital stress (Salo et al. 2017; Salo et al. 2020; Weinert 2018), further understanding of individuals’ coping behavior is needed (Weinert 2018). A group at high risk of suffering from the adverse effects of digital stress is adolescents because they grow up using DTM daily and are still developing their identity, acquiring mental strength, and adopting essential social skills. To facilitate a healthy DTM use, the dissertation explores what strategies adolescents use to cope with the demands of their DTM use. Combining a qualitative and a quantitative study, it presents 30 coping responses used by adolescents, develops five factors underlying adolescents’ activation of coping responses, and identifies gender- and age-related differences in their coping behavior. Third, the dissertation presents new prescriptive knowledge on the design of individual information systems supporting individuals in understanding and mitigating their perceived stress. Facilitated by the sensing capabilities of modern mobile devices, it explores the design and development of mobile systems that assess stress and support individuals in coping with stress by initiating a change of stress-related behavior. Since there is currently limited understanding of how to develop such systems, this dissertation explores various facets of their design and development. As a first step, it presents the development of a prototype aiming for life-integrated stress assessment, that is, the mobile sensor-based assessment of an individual’s stress without interfering with their daily routines. Data collected with the prototype yields a stress model relating sensor data to individuals’ perception of stress. To deliver a more generalized perspective on mobile stress assessment, the dissertation further presents a literature- and experience-based design theory comprising a design blueprint, design requirements, design principles, design features, and a discussion of potentially required trade-offs. Mobile stress assessment may be used for the development of mobile coping assistants. Aiming to assist individuals in effectively coping with stress and preventing future stress, a mobile coping assistant should recommend adequate coping strategies to the stressed individual in real-time or execute targeted actions within a defined scope of action automatically. While the implementation of a mobile coping assistant is yet up to future research, the dissertation presents an abstract design and algorithm for selecting appropriate coping strategies. To sum up, this dissertation contributes new knowledge on the digitalization of individuals to the IS knowledge bases, expanding both descriptive and prescriptive knowledge. Through the combination of diverse methodological approaches, it delivers knowledge on individuals’ behavior when using DTM, on the mitigation of consequences that may arise from individuals’ use of DTM, and on the design of individual information systems with the goal of facilitating a behavior change, specifically, regarding individuals’ coping with stress. Overall, the research contained in this dissertation may promote the development of digital assistants that support individuals’ in adopting a healthy DTM use behavior and thereby contribute to shaping a socio-technical environment that creates more benefit than harm for all individuals

Hyperspectral Imaging from Ground Based Mobile Platforms and Applications in Precision Agriculture

This thesis focuses on the use of line scanning hyperspectral sensors on mobile ground based platforms and applying them to agricultural applications. First this work deals with the geometric and radiometric calibration and correction of acquired hyperspectral data. When operating at low altitudes, changing lighting conditions are common and inevitable, complicating the retrieval of a surface's reflectance, which is solely a function of its physical structure and chemical composition. Therefore, this thesis contributes the evaluation of an approach to compensate for changes in illumination and obtain reflectance that is less labour intensive than traditional empirical methods. Convenient field protocols are produced that only require a representative set of illumination and reflectance spectral samples. In addition, a method for determining a line scanning camera's rigid 6 degree of freedom (DOF) offset and uncertainty with respect to a navigation system is developed, enabling accurate georegistration and sensor fusion. The thesis then applies the data captured from the platform to two different agricultural applications. The first is a self-supervised weed detection framework that allows training of a per-pixel classifier using hyperspectral data without manual labelling. The experiments support the effectiveness of the framework, rivalling classifiers trained on hand labelled training data. Then the thesis demonstrates the mapping of mango maturity using hyperspectral data on an orchard wide scale using efficient image scanning techniques, which is a world first result. A novel classification, regression and mapping pipeline is proposed to generate per tree mango maturity averages. The results confirm that maturity prediction in mango orchards is possible in natural daylight using a hyperspectral camera, despite complex micro-illumination-climates under the canopy

Socio-technical analysis and design of digital workplaces to foster employee health

Recent socio-technical developments caused by ongoing digitalization (e.g., robotic process automation, artificial intelligence, anthropomorphic systems) or the COVID-19 pandemic (e.g., an increasing number of remote working employees and hence, increasing number of virtual collaboration) change the work environment and culture. Digital and smart workplace technol-ogies facilitate business processes and provide tools for efficient communication and (virtual) collaboration, “increasing the productivity of the workforce in the information age” (Attaran et al. 2019, p. 1). Especially in times of the COVID-19 pandemic, digital technologies play a crucial role in keeping us socially close, connected, and collaborative while increasing the phys-ical distance between humans. However, this development affects the health of employees (Tarafdar et al. 2013). In research, for example, it has long been known that the increased usage of digital technologies and media (DTM) may cause stress, leading to potentially harmful reac-tions in individuals. Research has noted this specific form of stress as technostress (Ayyagari et al. 2011; Tarafdar et al. 2007; Tarafdar et al. 2011; Tarafdar et al. 2019), which is an umbrella term for causes, negative organizational outcomes, and negative humanistic outcomes resulting from the use of DTM at work. The simultaneous consideration of humanistic (e.g., well-being, equality) and organizational outcomes (e.g., efficiency, productivity) is an integral part of a socio-technical system (Beath et al. 2013; Mumford 2006), which is at the core of the IS discipline (Bostrom et al. 2009; Chiasson and Davidson 2005). However, a review from Sarker et al. (2019) regarding published research articles in one of the top journals within the IS community revealed that most reviewed studies (91%) had focused exclusively on instrumental goals. They conclude that “many IS researchers have forgotten or ignored the premise that technologies need to benefit humankind overall (Majchrzak et al. 2016), not just their economic condition” (Sarker et al. 2019, p. 705). Especially as humanistic outcomes can lead to even more positive instrumental outcomes. Hence, Sarker et al. (2019) call for focusing on the connection between humanistic and instru-mental outcomes, enabling a positive synergy resulting from this interplay. For this reason, this dissertation adopts a socio-technical perspective. It aims to conduct re-search that links instrumental outcomes with humanistic objectives to ultimately achieve a healthier use of DTMs at the digital workplace. It is important to note that the socio-technical perspective considers both the technical component and the social component privileging nei-ther one of them and sees outcomes resulting from the reciprocal interaction between those two.Therefore, the dissertation focuses on the interaction while applying pluralistic methodological approaches from qualitative (e.g., semi-structured interviews, focus group discussions) and quantitative research (e.g., collection from a field study or survey research). It provides a theo-retical contribution applying both behavioral research (i.e., analysis of cause-and-effect rela-tionships) and design-oriented research (i.e., instructions for designing socio-technical information systems). Overall, this work addresses four different areas within the reciprocal interaction between the social and technical components: the role of the technical component, the role of the social component, DTMs fostering a fit between the technical and social compo-nents, and the imminent misfit between these two due to ongoing digitalization. First, to contribute to an understanding of the technical component’s role, this thesis presents new knowledge on the characteristics and features of DTM and their influence on employee health and productivity. Research on the design of digital workplaces examined different design approaches, in which information exchange and sharing documents or project support were regarded (Williams and Schubert 2018). However, the characteristics of DTM also play an es-sential role in the emergence of technostress (Dardas and Ahmad 2015). This thesis presents ten characteristics of DTM that affect technostress at an individual’s workplace, including a measurement scale and analysis on how these characteristics affect technostress. Besides, also, the provision of functional features by DTMs can affect instrumental outcomes or humanistic objectives. For example, affording users with certain kinds of autonomy regarding the config-uration of DTM while they work towards their goals could have a tremendous effect on pursu-ing goals and well-being (Patall et al. 2008; Ryan and Deci 2000). Therefore, this thesis presents knowledge regarding the design of DTM on the benefits of affording users with autonomy. Furthermore, it shows that merely affording more autonomy can have positive effects above and beyond the positive effects of the actualization of affordance. Second, to contribute to an understanding of the social component’s role, this thesis presents new knowledge on contextual and individual factors of social circumstances and their influence on employee health and productivity. In this context, the influence of the COVID-19 pandemic on the intensity of technostress among employees is considered, as work became more digital almost overnight. Therefore, this thesis provides empirical insights into digital work and its context in times of the COVID-19 pandemic and its effect on employees’ well-being, health, and productivity. Furthermore, measures to steer the identified effects if the situation in the course of the COVID-19 pandemic persists or comparable disruptive situations should re-occur are discussed. On the other hand, this research takes a closer look at the effect of an individual preference regarding coping styles in dealing with upcoming technostress. A distinction is made between the effects of two different coping styles, namely active-functional and dysfunctional, on strain as a humanistic outcome and productivity as an instrumental outcome. In the course of this, evidence is provided that coping moderates the relationship between the misfit within the socio-technical system and strain as proposed by the psychological theory of job demands-resources model (Demerouti et al. 2001). Third, to contribute to a successful fit between the technical and social components, this thesis presents frameworks and guidelines on the design of DTM, which understand the social com-ponent (here the user and her/his environment) and adjust accordingly to the needs of their users. Therefore, the thesis provides knowledge on the design of DTMs that support users in applying stress management techniques and build the foundation for stress-sensitive systems (i.e., systems that aim to mitigate stress by applying intervention measures on the social and technical component (Adam et al. 2017)). As a matter of fact, a framework for collecting and storing data (e.g., on the user and her/his environment) is developed and experiences with im-plementing a prototype for life-integrated stress assessment are reported. The experiences from this and the existing knowledge in the literature will finally be aggregated to a mid-range design theory for mobile stress assessment. To contribute to the fourth and last aspect, the imminent misfit within the socio-technical sys-tem due to ongoing digitalization, this thesis presents new knowledge regarding digital work demands that potentially affect both employees’ health and instrumental outcomes. The current version of technostress’s theoretical foundation was introduced more than ten years ago by Tarafdar et al. (2007). However, the interaction with and use of DTM has considerably changed along with the societal and individual expectations. Therefore, this thesis puts the current con-cept of technostress to test. As a result, a new theory of digital stress, as an extension of the concept of technostress, is proposed with twelve dimensions – instead of five dimensions within the concept of Tarafdar et al. (2007) – that could be hierarchically structured in four higher-order factors. This theory holistically addresses the current challenges that employees have to deal with digitalization. To sum up, this dissertation contributes to the IS community’s knowledge base by providing knowledge regarding the interaction between employees and their digital workplace to foster the achievement of humanistic and instrumental outcomes. It provides both behavioral research and design-oriented research while using pluralistic methodological approaches. For this pur-pose, this thesis presents knowledge about the different components within the socio-technical system, design knowledge on DTMs fostering the fit between these components, and an under-standing of an upcoming misfit due to the ongoing digitalization. Overall, this research aims to support the successful change towards a healthy digital workplace in the face of digitalization