Edward Jay Wang

Skin Drag Displays: Dragging a Physical Tactor across the User's Skin Produces a Stronger Tactile Stimulus than Vibrotactile

We propose a new type of tactile displays that drag a physical tactor across the skin in 2D. We call this skin drag. We demonstrate how this allows us to communicate geometric shapes or characters to users. The main benefit of our approach is that it simultaneously produces two types of stimuli, i.e., (1) it moves a tactile stimulus across skin locations and (2) it stretches the users skin. Skin drag thereby combines the essential stimuli produced by vibrotactile and skin stretch. In our study, skin drag allowed participants to recognize tactile shapes significantly better than a vibrotactile array of comparable size. We present two arm-worn prototype devices that implement our concept.

Demo of MagnifiSense: inferring device interaction using wrist-worn passive magneto-inductive sensors

The different electronic devices we use on a daily basis produce distinct electromagnetic radiation due to differences in their underlying electrical components. We present MagnifiSense, a low-power wearable system that uses three passive magneto-inductive sensors and a minimal ADC setup to identify the device a person is operating. MagnifiSense achieves this by analyzing near-field electromagnetic radiation from common components such as the motors, rectifiers, and modulators. We conducted a staged, in-the-wild evaluation where an instrumented participant used a set of devices in a variety of settings in the home such as cooking and outdoors such as commuting in a vehicle. MagnifiSense achieves a classification accuracy of 82.6% using a model-agnostic classifier and 94.0% using a model-specific classifier. In a 24-hour naturalistic deployment, MagnifiSense correctly identified 25 of the total 29 events, while achieving a low false positive rate of 0.65% during 20.5 hours of non-activity.

HemaApp: noninvasive blood screening of hemoglobin using smartphone cameras

We present HemaApp, a smartphone application that noninvasively monitors blood hemoglobin concentration using the smartphones camera and various lighting sources. Hemoglobin measurement is a standard clinical tool commonly used for screening anemia and assessing a patients response to iron supplement treatments. Given a light source shining through a patients finger, we perform a chromatic analysis, analyzing the color of their blood to estimate hemoglobin level. We evaluate HemaApp on 31 patients ranging from 6 -- 77 years of age, yielding a 0.82 rank order correlation with the gold standard blood test. In screening for anemia, HemaApp achieve a sensitivity and precision of 85.7% and 76.5%. Both the regression and classification performance compares favorably with our control, an FDA-approved noninvasive hemoglobin measurement device. We also evaluate and discuss the effect of using different kinds of lighting sources.

Glabella: Continuously Sensing Blood Pressure Behavior using an Unobtrusive Wearable Device

We propose Glabella, a wearable device that continuously and unobtrusively monitors heart rates at three sites on the wearer’s head. Our glasses prototype incorporates optical sensors, processing, storage, and communication components, all integrated into the frame to passively collect physiological data about the user without the need for any interaction. Glabella continuously records the stream of reflected light intensities from blood flow as well as inertial measurements of the user’s head. From the temporal differences in pulse events across the sensors, our prototype derives the wearer’s pulse transit time on a beat-to-beat basis. Numerous efforts have found a significant correlation between a person’s pulse transit time and their systolic blood pressure. In this paper, we leverage this insight to continuously observe pulse transit time as a proxy for the behavior of systolic blood pressure levels—at a substantially higher level of convenience and higher rate than traditional blood pressure monitors, such as cuff-based oscillometric devices. This enables our prototype to model the beat-to-beat fluctuations in the user’s blood pressure over the course of the day and record its short-term responses to events, such as postural changes, exercise, eating and drinking, resting, medication intake, location changes, or time of day. During our in-the-wild evaluation, four participants wore a custom-fit Glabella prototype device over the course of five days throughout their daytime job and regular activities. Participants additionally measured their radial blood pressure three times an hour using a commercial oscillometric cuff. Our analysis shows a high correlation between the pulse transit times computed on our devices with participants’ heart rates (mean r = 0.92, SE = 0.03, angular artery) and systolic blood pressure values measured using the oscillometric cuffs (mean r = 0.79, SE = 0.15, angular-superficial temporal artery, considering participants’ self-administered cuff-based measurements as ground truth). Our results indicate that Glabella has the potential to serve as a socially-acceptable capture device, requiring no user input or behavior changes during regular activities, and whose continuous measurements may prove informative to physicians as well as users’ self-tracking activities.

HCI in Business: A Collaboration with Academia in IoT Privacy

The Internet of Things (IoT) integrates communication capabilities into physical objects to create a ubiquitous and multi-modal network of information and computing resources. The promise and pervasiveness of IoT ecosystems has lured many companies, including Intel, to devote resources and engineers to participate in the future of IoT. This paper describes a joint effort from Intel and two collaborators from academia to address the problem of IoT privacy.

What can i do here? IoT service discovery in smart cities

The vision of smart cities and IoT is an environment blanketed with interconnected, software-enabled devices. Unlike software installed on personal devices, however, people may not know about services in the environment, or may not even be the intended users. People lack a unified way to discover software services in a smart city infrastructure, and the current device-centric approach to IoT is inconsistent with the growing network and software services associated with these devices. In this paper we outline changes needed in the current IoT framework to shift to a service model for IoT. We describe how, similar to users of a personal computing device, users can define their preferences, install services, and manage the data that is generated and consumed by services. In this framework, service preferences provide a basis for proper service discovery. As an illustration of the proposed model, we provide modifications to the well established Auto-ID Object Name Service and Physical Markup Language architecture to demonstrate how a practical system can support the concept of IoT services and discovery.

Carpacio: Repurposing Capacitive Sensors to Distinguish Driver and Passenger Touches on In-Vehicle Screens

Standard vehicle infotainment systems often include touch screens that allow the driver to control their mobile phone, navigation, audio, and vehicle configurations. For the drivers safety, these interfaces are often disabled or simplified while the car is in motion. Although this reduced functionality aids in reducing distraction for the driver, it also disrupts the usability of infotainment systems for passengers. Current infotainment systems are unaware of the seating position of their user and hence, cannot adapt. We present Carpacio, a system that takes advantage of the capacitive coupling created between the touchscreen and the electrode present in the seat when the user touches the capacitive screen. Using this capacitive coupling phenomenon, a car infotainment system can intelligently distinguish who is interacting with the screen seamlessly, and adjust its user interface accordingly. Manufacturers can easily incorporate Carpacio into vehicles since the included seat occupancy detection sensor or seat heating coils can be used as the seat electrode. We evaluated Carpacio in eight different cars and five mobile devices and found that it correctly detected over 2600 touches with an accuracy of 99.4%.

Seismo: Blood Pressure Monitoring using Built-in Smartphone Accelerometer and Camera

Although cost-effective at-home blood pressure monitors are available, a complementary mobile solution can ease the burden of measuring BP at critical points throughout the day. In this work, we developed and evaluated a smartphone-based BP monitoring application called textitSeismo. The technique relies on measuring the time between the opening of the aortic valve and the pulse later reaching a periphery arterial site. It uses the smartphones accelerometer to measure the vibration caused by the heart valve movements and the smartphones camera to measure the pulse at the fingertip. The system was evaluated in a nine participant longitudinal BP perturbation study. Each participant participated in four sessions that involved stationary biking at multiple intensities. The Pearson correlation coefficient of the blood pressure estimation across participants is 0.20-0.77 (

A smartphone-based system for assessing intraocular pressure

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CASPER: capacitive serendipitous power transfer for through-body charging of multiple wearable devices

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