WearPut : Designing Dexterous Wearable Input based on the Characteristics of Human Finger Motions

Department of Biomedical Engineering (Human Factors Engineering)Powerful microchips for computing and networking allow a wide range of wearable devices to be miniaturized with high fidelity and availability. In particular, the commercially successful smartwatches placed on the wrist drive market growth by sharing the role of smartphones and health management. The emerging Head Mounted Displays (HMDs) for Augmented Reality (AR) and Virtual Reality (VR) also impact various application areas in video games, education, simulation, and productivity tools. However, these powerful wearables have challenges in interaction with the inevitably limited space for input and output due to the specialized form factors for fitting the body parts. To complement the constrained interaction experience, many wearable devices still rely on other large form factor devices (e.g., smartphones or hand-held controllers). Despite their usefulness, the additional devices for interaction can constrain the viability of wearable devices in many usage scenarios by tethering users' hands to the physical devices. This thesis argues that developing novel Human-Computer interaction techniques for the specialized wearable form factors is vital for wearables to be reliable standalone products. This thesis seeks to address the issue of constrained interaction experience with novel interaction techniques by exploring finger motions during input for the specialized form factors of wearable devices. The several characteristics of the finger input motions are promising to enable increases in the expressiveness of input on the physically limited input space of wearable devices. First, the input techniques with fingers are prevalent on many large form factor devices (e.g., touchscreen or physical keyboard) due to fast and accurate performance and high familiarity. Second, many commercial wearable products provide built-in sensors (e.g., touchscreen or hand tracking system) to detect finger motions. This enables the implementation of novel interaction systems without any additional sensors or devices. Third, the specialized form factors of wearable devices can create unique input contexts while the fingers approach their locations, shapes, and components. Finally, the dexterity of fingers with a distinctive appearance, high degrees of freedom, and high sensitivity of joint angle perception have the potential to widen the range of input available with various movement features on the surface and in the air. Accordingly, the general claim of this thesis is that understanding how users move their fingers during input will enable increases in the expressiveness of the interaction techniques we can create for resource-limited wearable devices. This thesis demonstrates the general claim by providing evidence in various wearable scenarios with smartwatches and HMDs. First, this thesis explored the comfort range of static and dynamic touch input with angles on the touchscreen of smartwatches. The results showed the specific comfort ranges on variations in fingers, finger regions, and poses due to the unique input context that the touching hand approaches a small and fixed touchscreen with a limited range of angles. Then, finger region-aware systems that recognize the flat and side of the finger were constructed based on the contact areas on the touchscreen to enhance the expressiveness of angle-based touch input. In the second scenario, this thesis revealed distinctive touch profiles of different fingers caused by the unique input context for the touchscreen of smartwatches. The results led to the implementation of finger identification systems for distinguishing two or three fingers. Two virtual keyboards with 12 and 16 keys showed the feasibility of touch-based finger identification that enables increases in the expressiveness of touch input techniques. In addition, this thesis supports the general claim with a range of wearable scenarios by exploring the finger input motions in the air. In the third scenario, this thesis investigated the motions of in-air finger stroking during unconstrained in-air typing for HMDs. The results of the observation study revealed details of in-air finger motions during fast sequential input, such as strategies, kinematics, correlated movements, inter-fingerstroke relationship, and individual in-air keys. The in-depth analysis led to a practical guideline for developing robust in-air typing systems with finger stroking. Lastly, this thesis examined the viable locations of in-air thumb touch input to the virtual targets above the palm. It was confirmed that fast and accurate sequential thumb touch can be achieved at a total of 8 key locations with the built-in hand tracking system in a commercial HMD. Final typing studies with a novel in-air thumb typing system verified increases in the expressiveness of virtual target selection on HMDs. This thesis argues that the objective and subjective results and novel interaction techniques in various wearable scenarios support the general claim that understanding how users move their fingers during input will enable increases in the expressiveness of the interaction techniques we can create for resource-limited wearable devices. Finally, this thesis concludes with thesis contributions, design considerations, and the scope of future research works, for future researchers and developers to implement robust finger-based interaction systems on various types of wearable devices.ope

Isolated Double-Chambered Right Ventricle in a Young Adult

Double-chambered right ventricle (DCRV) is a rare congenital heart disorder in which the right ventricle is divided by an anomalous muscle bundle into a high pressure inlet portion and a low pressure outlet portion. We report a case of isolated DCRV without symptoms in adulthood, diagnosed through echocardiography, cardiac catheterization and cardiac magnetic resonance imaging

Isolated Double-Chambered Right Ventricle in a Young Adult

Double-chambered right ventricle (DCRV) is a rare congenital heart disorder in which the right ventricle is divided by an anomalous muscle bundle into a high pressure inlet portion and a low pressure outlet portion. We report a case of isolated DCRV without symptoms in adulthood, diagnosed through echocardiography, cardiac catheterization and cardiac magnetic resonance imaging

Fingers and Angles: Exploring the Comfort of Touch Input on Smartwatches.

Smartwatches present a unique touch input context: small, fixed to one wrist and approachable from a limited range of angles by the touching hand. Techniques to expand their input expressivity often involve variations in how a watch must be touched, such as with different fingers, poses or from specific angles. While objective performance with such systems is commonly reported, subjective qualities such as comfort remain overlooked. We argue that techniques that involve uncomfortable input will be of limited value and contribute the first data on the comfort of input on smartwatches via two studies that combine subjective ratings of comfort with objective performance data. We examine both static and dynamic touches and three finger poses. Based on the study results, we contribute a set of design recommendations for comfortable, effective smartwatch input. We close by instantiating the recommendations in interface prototypes that we evaluate in a final qualitative study

TriTap: Identifying Finger Touches on Smartwatches

The small screens of smartwatches provide limited space for input tasks. Finger identification is a promising technique to address this problem by associating different functions with different fingers. However, current technologies for finger identification are unavailable or unsuitable for smartwatches. To address this problem, this paper observes that normal smartwatch use takes places with a relatively static pose between the two hands. In this situation, we argue that the touch and angle profiles generated by different fingers on a standard smartwatch touch screen will differ sufficiently to support reliable identification. The viability of this idea is explored in two studies that capture touches in natural and exaggerated poses during tapping and swiping tasks. Machine learning models report accuracies of up to 93% and 98% respectively, figures that are sufficient for many common interaction tasks. Furthermore, the exaggerated poses show modest costs (in terms of time/errors) compared to the natural touches. We conclude by presenting examples and discussing how interaction designs using finger identification can be adapted to the smartwatch form factor

Whiskers: Exploring the Use of Ultrasonic Haptic Cues on the Face

Haptic cues are a valuable feedback mechanism for smart glasses. Prior work has shown how they can support navigation, deliver notifications and cue targets. However, a focus on actuation technologies such as mechanical tactors or fans has restricted the scope of research to a small number of cues presented at fixed locations. To move beyond this limitation, we explore perception of in-air ultrasonic haptic cues on the face. We present two studies examining the fundamental properties of localization, duration and movement perception on three facial sites suitable for use with glasses: the cheek, the center of the forehead, and above the eyebrow. The center of the forehead led to optimal performance with a localization error of 3.77mm and accurate duration (80%) and movement perception (87%). We apply these findings in a study delivering eight different ultrasonic notifications and report mean recognition rates of up to 92.4% (peak: 98.6%). We close with design recommendations for ultrasonic haptic cues on the face

The effect of peripheral cues on motion sickness mitigation when using a VR HMD in a car

Virtual Reality (VR) is a promising candidate for an in-vehicle personal viewing system. However, motion sickness caused by VR in vehicles is a major obstacle to its use. In this study, we propose mitigating motion sickness by presenting peripheral cues that are integral to a VR scene. The cues react to the vehicle???s rotation with a three-dimensional opposing rotation. An on-road experiment was conducted to evaluate whether the peripheral cues mitigate motion sickness. Outcomes were assessed by both subjective motion sickness ratings and physiological responses. There are two conditions: watching a video with the cues and without the cues. Results indicate that motion sickness gradually increased with exposure time, and the mean levels of motion sickness were lower when the cues were presented. We discuss how these results are related to the cue design and suggest directions for future work

Mid- and Late-Life Migraine Is Associated with an Increased Risk of All-Cause Dementia and Alzheimer’s Disease, but Not Vascular Dementia: A Nationwide Retrospective Cohort Study

We used a nationwide cohort sample of data from 2002 to 2013, representing approximately 1 million patients to investigate the prospective association between migraine and dementia. The migraine group (n = 1472) included patients diagnosed between 2002 and 2004, aged over 55 years; the comparison group was selected using propensity score matching (n = 5888). Cox proportional hazards regression analyses was used to calculate the hazard ratios (HRs). The incidence of dementia was 13.5 per 1000 person-years in the migraine group. Following adjustment for sociodemographic and comorbidities variables, patients with migraine developed dementia more frequently than those in the comparison group (adjusted HR = 1.37, 95% confidence interval [CI], 1.16–1.61). In the subgroup analysis, we found a higher HR of dementia events in male, the presence of comorbidities, and older age (≥65) patients with migraine, compared to those without migraine. Moreover, patients with migraine had a significantly higher incidence of Alzheimer’s disease (adjusted HR = 1.31, 95% CI, 1.08–1.58), but not vascular dementia, than those without migraine. Therefore, our findings suggest that mid- and late-life migraines may be associated with an increased incidence of all-cause dementia and Alzheimer’s disease, but not vascular dementia