Some of the recently released smartwatch products feature a single-lead electrocardiogram (ECG) recording capability. The reliability of obtaining 3-lead ECG with smartwatches is yet to be confirmed in a large study. This study aimed to assess the feasibility and reliability of smartwatch to obtain 3-lead ECG recordings, the classical Einthoven ECG leads I-III compared to standard ECG. To record lead I, the watch was worn on the left wrist and the right index finger was placed on the digital crown for 30 s. For lead II, the watch was placed on the lower abdomen and the right index finger was placed on the digital crown for 30 s. For lead III, the same process was repeated with the left index finger. Spearman correlation and Bland-Altman tests were used for data analysis. A total of 300 smartwatch ECG tracings were successfully obtained. ECG waves’ characteristics of all three leads obtained from the smartwatch had a similar duration, amplitude, and polarity compared to standard ECG. The results of this study suggested that the examined smartwatch (Apple Watch Series 4) could obtain 3-lead ECG tracings, including Einthoven leads I, II, and III by placing the smartwatch on the described positions.

This master's thesis presents a research-through-design process that explores how can affective, context-aware systems support mental health and minimize stress in young adults during exam periods. This is achieved by designing an interactive system for stress recognition and relief. Biosensors embedded into existing wearable smart devices are used to infer stress-related mental states from a multimodal set of sensory data. The information is used to increase emotional awareness, provide recommendations for stress management, and enhance the users’ home environment. Two main challenges are addressed within this paper - detecting stress using easily available unobtrusive sensors and the output modalities supporting the human-computer interaction. Zenth has been developed through an iterative process, based on relevant literature and works in the field of affective computing, technology, and stress detection and recognition.

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A sedentary life leads to numerous health problems, thus the need of constant motivation for a more active lifestyle. This paper presents a design process for a smartwatch app in its early stages while exploring and involving users in engaging activities. Potential users have been involved throughout the design process, in design experiments in order to co-create engaging physical activities. The key element “engaging” refers to physical activities as being fun, captivating, attractive. After an online questionnaire about physical activity and reasons for not being active, followed by an autoethnography on fitness apps, like Let’s Muv, Zombie, Run!, Coach5K, 7 min workout and Fitnet, three experiments were conducted. The experiments - interview, bodystorming, brainstorming - were performed with the focus on exploring engaging physical activities in a work environment, and therefore understand the effective features a smartwatch could have to motivate people to a more active lifestyle.

Studien undersöker och sammanfattar vad det finns för risker i samband med användandet av aktivitetsmätare, så som aktivitetsarmband och smartwatches.Det finns många studier som visar på hur enkelt det är att komma åt den personliga data i flertalet olika aktivitetsarmband, av flera olika tillverkare. Därför har denna studien valt att fokusera på användarna genom att göra en enkätundersökning. Enkätundersökningen undersöker hur medvetna och hur mycket aktiva val användarna gör för att skydda sin personliga integritet online. En litteraturstudie har genomförts vilket omfattar vad det finns för risker, eventuella konsekvenser och vad det finns för tekniker som kan skydda den personliga integriteten i aktivitetsmätare.Riskerna som identifierats är bland annat dataintrång, att tredje part kan komma åt data vilket kan kartlägga användarnas vanor och livsstil. Konsekvenserna kan vara identitetsstöld, utpressning eller att den personliga integriteten kränks.Undersökningen visar att det finns en medvetenhet kring den digitala integriteten, men de är få som aktivt försöker skydda eller begränsa mängden data som samlas in. Enligt undersökningen är de flesta ovetande om hur deras data används. Slutsatsen är att de flesta aktivitetsarmband och smartwatches har säkerhetsbrister vilket innebär att den personliga integriteten kan äventyras. Brister i säkerheten finns när data ska överföras och lagras. Men för vissa användare är fördelarna med att bära aktivitetsband större än nackdelarna, det är upp till användaren att bestämma om den är villig att dela datan som samlas in. / This study investigates the risks associated with using fitness trackers, such as fitnesstrackers and smartwatches. In the recent years the interest in collecting and measuring personal data has increased, therefore it is important to investigate privacy risks. If privacy could be compromised through using fitness trackers and what are the security issues. It also includes suggestions for minimize the issues, which could work as guidelines or standards in the future. Previous studies demonstrate how easy it is to access the data from fitness trackers. Therefore, this study will focus more on the users instead of detailed issues of products from varied brands. The survey examines if users are aware of data collection and if they trying to protect their privacy online. The information to identified possible risks and consequences are based on previous research in the area.The risks identified include data breach and third-party access etc. It is important to protect the data fitness trackers generates. If the data leaks, the consequences can be identity theft, blackmailing or violation of privacy.The result shows that users are aware of privacy online, but few are trying to protect or limit the amount of data collected. The conclusion is that most activity tracker as braces and smartwatches have security issue, which means that privacy can be compromised. It is up to the user to decide if the benefits are greater than the disadvantages for using a fitnesstracker, if they are willing to share the data that are collected

A stressful society with a deficiency of attention has led to a growing demand for meditation techniques. One meditation technique is mindfulness, which is a tool used to reduce stress, intensify body awareness and to help us be more present. However, as mindfulness requires extensive training and dedication, many beginners may decide to quit practicing in the initial phase and may risk not ever experiencing the benefits of body awareness. Previous studies indicate that technology is often blamed for the deficiency of attention. Therefore, this study addresses the possibilities to design technology for sustained attention. More precisely, the study aims to investigate what potential possibilities wearable haptic technology has in enabling body awareness in body scan meditation in mindfulness. It also aims to explore how beginners in mindfulness experience the use of wearable haptic technology in body scan meditation. The study explores these problems by combining research through design and action research, with three phases of iteration, resulting in the design, implementation and evaluation of the wearable prototype HeatCue with haptic thermal feedback. The study implies that HeatCue provides an intimate, subtle and skin-close interaction, suitable for the context of body scan mediation. The results indicate that wearable haptic technology with thermal feedback holds the possibility to enable body awareness in body scan meditation through acting as a reminder for the body part where the feedback is applied, a reference for the rest of the body as well as encouragement. Furthermore, the study shows that wearable haptic technology is beneficial in evoking emotions and interest. The study also indicates some key aspects when designing for body awareness, namely; subtlety and interplay of the feedback, a secluded environment and an understanding that each individual is different. The study contributes to a deeper understanding of designing for body awareness and to new knowledge in the field of wearable haptic technology with thermal feedback and techno-spirituality in human-computer interaction

Intresset för den personliga hälsan ökar inom samtliga sociala grupper. Människor vill få utökad kontroll över hur sin hälsosituation och de tar till allt fler hjälpmedel för att kunna få bättre svar. Med det digitala samhället nära till hands dyker det upp allt fler tjänster och produkter som agerar hjälpmedel för att produktens användare ska kunna få en större och bättre kontroll över sin hälsa. Produkter och tjänster som gör detta ingår i området Internet of Sports. I samband med att fler användare ansluter sig till dessa tjänster och produkter ökar därmed också datamängden de samlar in. Skyddas denna data i överföringen mellan användaren och företagen och skyddar de som samlar in datan användarens personliga integritet? Uppsatsens syfte är att undersöka detta genom att granska utvalda företag som verkar inom Internet of Sports och se om det går att komma över användarnas personliga data genom man in the middle-attacker. / The interest for personal health is growing in all demographic groups. People want better control regarding their personal health and they are using more aids to get better answers. With the digital society close to hand new products and services are appearing to aid users to get a better knowledge and control of their personal health. The products and services that aim to do this are categorized as Internet of Sports. As more users are signing up for and using these products and services the gathering of data is growing. Is the data that these companies gather safely transfered from the user to the companies and are the companies protecting the user’s privacy? The thesis’ purpose is to examine chosen companies within Internet of Sports and to see if it is possible to access the user’s personal data through man in the middle attacks.

The aim of this thesis is to compare two different interface approaches for pervasive gameswith a focus on immersion. We designed and created two small pervasive games and implemented bothon two different platforms; smartphone and wearable device. We created four pervasive gameprototypes which we tested with a group of fourteen testers. We subsequently conducted interviewsusing the Repertory Grid Technique. The findings suggest that our testers appreciated wearable devicesmore than smartphones in the context of immersion, while they identified characteristics theyassociated with each platform; Smartphones were considered familiar, inconspicuous, casual but notvery exciting. Wearables were considered a new experience and fun but also strange and attention-drawing.

A spacewalk, or extravehicular activity (EVA), is one of the most mission critical and physically and cognitively challenging tasks that crewmembers complete. With next-generation missions to the Moon and Mars, exploration EVA will challenge crewmembers in partial gravity environments with increased frequency, duration, and autonomy of operations. Given the distance from Earth, associated communication delays, and durations of exploration missions, there is a monumental shift in responsibility and authority taking place in spaceflight; moving from Earth-dependent to crew self-reliant. For the safety, efficacy, and efficiency of future surface EVAs, there is a need to better understand crew health and performance. With this knowledge, technology and operations can be designed to better support future crew autonomy. The focus of this dissertation is to develop and evaluate a psychophysiological monitoring tool to classify cognitive workload during an operationally relevant EVA task. This was completed by compiling a sensor suite of commercial wearable devices to record physiological signals in two human research studies, one at Virginia Tech and one at NASA Johnson Space Center. The approach employs supervised machine learning to recognize patterns in psychophysiological features across different psychological states. This relies on the ability to simulate, or induce, cognitive workload in order to label data for training the model. A virtual reality (VR) Translation Task was developed to control and quantify cognitive demands during an immersive, ambulatory EVA scenario. Participants walked on a passive treadmill while wearing a VR headset to move along a virtual lunar surface. They walked with constraints on time and resources, while simultaneously identifying and recalling waypoints in the scene. Psychophysiological features were extracted and labeled according to the task demands, i.e. high or low cognitive workload, for the novel Translation Task, as well as for the benchmark Multi-Attribute Task Battery (MATB). Predictive models were created using the K Nearest Neighbor (KNN) algorithm. The contributions of this dissertation span the simulation, characterization, and modeling of cognitive state. Ultimately, this work tests the limits of extending laboratory psychophysiological monitoring to more realistic environments using wearable devices, and of generalizing predictive models across participants, times, and tasks. This work paves the way for future field studies and real-time implementation to close the loop between human and automation. / Doctor of Philosophy / A spacewalk is one of the most important and physically and mentally challenging tasks that astronauts complete. With next-generation missions to the Moon and Mars, exploration spacewalks will challenge astronauts in reduced-weight environments (1/6 and 1/3 Earth's gravity) with longer, more frequent spacewalks and with less help from mission control. To keep astronauts safe while exploring there is a need to better understand astronaut health and performance (physical and mental) during spacewalks. With knowledge of how astronauts will respond to high workload and stressful events, we can plan missions and design tools that can best assist them during spacewalks on the Moon and Mars when help from Earth mission control is limited. Traditional tools of quantifying mental state are not suitable for real-time assessment during spacewalks. Current methods, including subjective surveys and performance-based computer tests, require time and attention to complete and cannot assess real-time operations. The focus of this dissertation is to create a psychophysiological monitoring tool to measure mental workload during a virtual reality (VR) spacewalk. Psychophysiological monitoring uses physiological measures, like heart rate and breathing rate, to predict psychological state, like high workload or stress. Physiological signals were recorded using commercial wearable devices in two human research studies, one at Virginia Tech and one at NASA Johnson Space Center. With machine learning, computer models can be trained to recognize patterns in physiological measures for different psychological states. Once a model is trained, it can be tested on new data to predict mental workload. To train and test the models, participants in the studies completed high and low workload versions of the VR task. The VR task was specifically designed for this study to simulate and measure performance during a mentally-challenging spacewalk scenario. The participants walked at their own pace on a treadmill while wearing a VR headset to move along a virtual lunar surface, while balancing their time and resources. They were also responsible for identifying and recalling flags along their virtual path. Ultimately, this work tests the limits of extending laboratory psychophysiological monitoring to more realistic environments using wearable devices, and of generalizing predictive models across participants, times, and tasks. This work paves the way for future field studies and real-time implementation to close the loop between human and automation.

Acquiring joint kinematics, joint moments, and ground reaction forces (GRFs) during walking is essential for assessing disease progression and health monitoring during rehabilitation. However, spatial and temporal constraints, expert processing, and high costs limit the current gold standard methods, such as optical motion capture systems and floor-embedded force plates. Experts have suggested wearables with machine learning methods to address this issue, but their large sensor count renders them impractical for daily use, and the use of generic algorithms limits their accuracy. As a result, learning kinematics and kinetics in everyday life outside of laboratory settings is challenging. Thus, there is a need for an inexpensive, near-real-time system and an accurate method for estimating kinematics, joint moments, and GRFs. This dissertation proposes using shoe-mounted IMU sensors and deep learning to estimate these parameters across various locomotion modes, reflecting everyday walking conditions. Four different approaches are explored. The first approach uses shoe-embedded IMU sensors with novel deep learning models, DeepBBWAE-Net, Kinetics-FM-DLR-Ensemble-Net, and DL-Kinetics-FM-Net, which outperform state-of-the-art models but are computationally expensive. The second approach introduces Kinematics-Net and Kinetics-MMF-Net, which are lightweight yet maintain similar performance. Sparse IMU sensors on the feet may miss critical walking dynamics, so the third approach proposes a sensor distillation technique, transferring knowledge from a teacher model (trained with full sensors) to a student model (trained with sparse IMUs), enhancing estimation accuracy. Although our models are trained on a substantial number of subjects, deep learning models tend to perform better with larger datasets. Collecting extensive subject data is resource-intensive and time-consuming. Additionally, public datasets often differ in sensor types, locations, and protocols. Our fourth approach addresses this by proposing a domain adaptation technique that transfers knowledge from source datasets to the target dataset, improving performance in the target domain.