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We see a major hurdle, as well as a window of opportunity, in wearable system design - making the system soft and bendable for skin surface sensing. In this position statement, we present our design of an FPCB (flexible printed circuit board) based wearable system for muscle fatigue sensing, referred to as the Smart KT Tape.

This paper describes a case study of adapting a phone-based support system (CopeDiary) to help drug-dependent patients obtain, maintain, and practice coping skills for dealing with high-risk situations, thereby preventing drug relapse. We designed and implemented CopeDiary and conducted real-world user testing on three recovering drug-dependent patients receiving outpatient abstinence treatment at a hospital. CopeDiary was designed to be an assistive tool for therapists to educate drug-dependent patients about coping skills. Follow-up interviews revealed design-related challenges regarding how to engage drug-dependent patients and therapists about learning and teaching coping strategies for daily life.

This paper improves a remarkable background estimation algorithm, namely Neighbor-based Intensity Correction (NIC) which is used in the background subtraction technique for foreground detection. The algorithm has an efficient intensity correction scheme to update the current background based on calculating the standard deviation of two windows captured from the background and the input frame in which the windows are constructed by a squared-structure binary mask. Although the NIC algorithm achieved the comparative results with existing approaches on the foreground detection accuracy and processing speed, its performance in the multi-modal background including high-speed motion and camera jitter should be improved. In the original algorithm, we recognize that the shape of a binary mask further affects the updating performance besides the window size which was already analyzed. Various shapes are therefore recommended for the multi-modal background adaptation. Moreover, an adaptive threshold identified by referring several previous Otsu thresholds to cope with the high-speed motion challenge is proposed. Experimental results on some standard datasets such CAVIAR 2004, AVSS2007, PETS 2009, and CDNET 2014, demonstrate that the foreground detection accuracy is significantly boosted with 2.6--6.7% of the F-measure metric.

This paper describes the challenges and lessons learned in the design of a patient monitoring and early warning system for patients in acute psychiatric centers. We began by conducting contextual inquiries and a focus group to identify the challenges and opportunities for the application of new technologies. The resulting themes were then used in the development of wearable sensing and environment monitoring devices that can be configured for individual patients and the specifics of the facility.

Ketamine is an addictive drug that has been shown to inflict considerable physical and mental damage on users. Due in part to its low cost, ketamine has become one of the most popular club drugs among young adults and teenagers in Southeast Asia. This paper proposes a phone-based support system (KeDiary) with Bluetooth-enabled device for the screening of saliva, as a means of assisting ketamine-dependent patients to self-monitor their ketamine use following acute withdrawal treatment. We also conducted a practical experiment to evaluate the feasibility of the proposed system, wherein three ketamine-dependent patients self-administered tests at least once per day over a period of three weeks. Follow-up interviews with the same users helped in the further refinement of the proposed self-monitoring system.

In this paper, we proposed an Adaptive Return-to-Home Sensing (ARS) algorithm for a drone sensing system deployed in an open area with missions to conduct periodic environmental sensing. ARS scheme is able to conduct as many rounds of environmental sensing without drastic oscillation between consecutive sensing attempts while reserve sufficient energy for the drone to fly back home. We evaluate the ARS scheme under environmental difficulties. The results demonstrate the proposed scheme can conduct as many rounds of environmental sensing as possible without drastic oscillation while preserve enough energy for the done to return home.

Alcohol dependence is a chronic disorder associated with severe harm in multiple areas, and relapsing is easy, despite treatment. This study proposes SoberDiary, a phone-based support system that enables alcohol-dependent patients to self-monitor and -manage their own alcohol behavior, and remain sober in their daily lives. We tested SoberDiary in a real-life 12-week user study involving 27 clinical patients. The quantitative and qualitative results revealed that SoberDiary helped patients self-monitor and -manage their alcohol-use behavior, and reduced their total alcohol consumption as well as the number of heavy drinking days. Compared with patients who received standard treatment alone, this study demonstrated SoberDiary successfully complemented current alcohol treatment in reducing patients' alcoholic cravings and dropout rate over 3-month study period. Follow-up interviews further revealed the sophisticated use practices and value of SoberDiary.

This paper describes the design of a digital fork and a mobile interactive and persuasive game for a young child who is a picky eater and/or easily distracted during mealtime. The system employs Ubicomp technology to educate children on the importance of a balanced diet while motivating proper eating behavior. To sense a child's eating behavior, we have designed and prototyped a sensor-embedded digital fork, called the Sensing Fork. Furthermore, we have developed a story-book and persuasive game, called the Hungry Panda, on a smartphone. This capitalizes on the capabilities of the Sensing Fork to interact with and modify children's eating behavior during mealtime. We report the results of a real-life study that involves mother-child subjects and tested the effectiveness of the Sensing Fork and Hungry Panda game in addressing children's eating problems. Our findings exhibit positive effects for changing children's eating behavior.

To facilitate the collection of patient biosignals, designing extensible sensing devices in which sensor management is simplified is essential. This paper presents BioScope, an extensible sensing system that facilitates collecting data used in nursing assessments. We conducted experiments to demonstrate the potential of the system. The results obtained in this study can be applied in improving the design, thus enabling BioScope to facilitate data collection in numerous potential applications.

To deliver voice over the Internet in a cost-effective way, it is essential to quantify the quality of user experience (i.e., QoE) of a voice service at various provisioning levels. Conducting user studies is an inevitable step facilitating quantitative studies of QoE. The two experimental methods -- lab experiment vs. crowdsourcing via Amazon Mechanical Turk [1] -- are compared in this study. We find that, for the study of Skype call quality, the crowdsourcing approach stands out in terms of efficiency and user diversity, which in turn strengthens the robustness and the depth of the analysis.

This paper presents the design and implementation of a wearable oral sensory system that recognizes human oral activities, such as chewing, drinking, speaking, and coughing. We conducted an evaluation of this oral sensory system in a laboratory experiment involving 8 participants. The results show 93.8% oral activity recognition accuracy when using a person-dependent classifier and 59.8% accuracy when using a person-independent classifier.

We present a fork-type sensing device called the Sensing Fork that detects the eating behavior of children (food choice and eating actions), and a smartphone game to address children's eating problems based on their eating behavior. This paper describes the design and implementation of the Sensing Fork prototype and a play-based eating game called Hungry Panda 2, which works with the Sensing Fork. This game focuses on motivating children to eat all kinds of food on their table.

As Skype has become popular and a profitable business, the long-standing problem of how to deliver Skype calls deserves a serious revisit from an economic viewpoint. This study proposes a rate control mechanism for Skype calls that satisfies more users and satisfies users more than the greedy-naïve mechanism, as well as the mechanism implemented in Skype.

We propose a fork-type sensing device, Sensing Fork, which detects children's eating behavior (eating actions and chosen food) and a smartphone game to address children's eating problems. This paper describes the design and implementation of the Sensing Fork prototype and the play-based eating game called Hungry Panda.

This study explores the use of mobile phones as a normal life support system that connects alcohol addict patients to their addiction physiatrists after they leave a rehabilitation center. This paper presents the design and implementation of this phone-based support system that enables continuous patient monitoring and provides feedback support to the patients.

This paper proposes Listen-to-Nose, a phone-based system that detects and records when and where a person's nose-related symptoms, such as sneezing and runny nose, occur in everyday settings. It is hoped that this system can be used to collect reference data for doctors to diagnose the cause of these symptoms.

This paper proposes a blimp-based vehicular sensing system, called BlimpProbe, which travels above ground to perform environmental monitoring. We describe an application in atmosphere science that is suitable for this blimp-based sensing system.

This study presents TriopusNet, a mobile wireless sensor network system for autonomous sensor deployment in pipeline monitoring. TriopusNet works by automatically releasing sensor nodes from a centralized repository located at the source of the water pipeline. During automated deployment, TriopusNet runs a sensor deployment algorithm to determine node placement. While a node is flowing inside the pipeline, it performs placement by extending its mechanical arms to latch itself onto the pipe's inner surface. By continuously releasing nodes into pipes, the TriopusNet system builds a wireless network of interconnected sensor nodes. When a node runs at a low battery level or experiences a fault, the TriopusNet system releases a fresh node from the repository and performs a node replacement algorithm to replace the failed node with the fresh one. We have evaluated the TriopusNet system by creating and collecting real data from an experimental pipeline testbed. Comparing with the nonautomated static deployment, TriopusNet is able to use less sensor nodes to cover a sensing area in the pipes while maintaining network connectivity among nodes with high data collection rate. Experimental results also show that TriopusNet can recover from the network disconnection caused by a battery-depleted node and successfully replace the battery-depleted node with a fresh node.

To promote energy-saving behavior, disaggregating electricity usage is critical for increasing consumer awareness of energy usage behavior. This study proposes HeatProbe, a thermal-based power meter system that uses thermal imaging to track disaggregated appliance usage. We have designed, prototyped, and tested the HeatProbe system. Results show that HeatProbe successfully senses individual appliance operating durations with an average error of 125.03 seconds, achieving 80.2% appliance power accounting accuracy in different appliance usage scenarios.

This paper presents PipeProbe, a mobile sensor system for determining the spatial topology of hidden water pipelines behind walls. PipeProbe works by dropping a tiny wireless sensor capsule into the source of the water pipelines. As the PipeProbe capsule traverses the pipelines, it gathers and transmits pressure and angular velocity readings. Through spatio-temporal analysis on the sensor readings, our algorithm locates all turning points in the pipelines and maps their 3D spatial topology. We evaluated the PipeProbe system by developing a prototype and using data collected in our experimental testbed. Results show that the PipeProbe system successfully located and estimated 90% of all pipe tube lengths within 8-cm accuracy on average tube lengths of 76 cm. PipeProbe also successfully located 90% of all turning points within 15-cm accuracy on average length paths of 335cm.

This paper proposes Convenience Probe, a participatory sensing tool to collect large-scale consumer flow behaviors from everyday mobile phones. We hope to use Convenience Probe to collect real consumer flow data that will help convenience store chains in store location assessment.

Saving DTNs' battery power to prolong the system life time has been an important research topic which scientists try to optimize. Most researches fall into two categories - Time Division Multiple Access based ones, and Low Power Listening ones by turning the listener's radio on/off intermittenly with long sending preambles. In this paper we propose solving the problem from a whole new angle - by using the motes' physical behavior, which is detectable by relatively energy-cheap accelerometer, as the judgment for turning the radio on/off. This scheme can be used in combination with any energy efficient DTN MAC protocols. We evaluate the protocol by running simulations with real hikers' traces and the result is shown in the evaluation section.

MemoIcon increases productivity with a new interaction method based on pattern recognition and multi-touch techniques. It easily binds virtual information to everyday real objects and transforms them into physical icons that embody virtual tasks as tangible items. Virtual information becomes tangible and physically present.

This study of mobile persuasion system explores the use of a mobile phone, when attached to an everyday object used by an everyday behavior, becomes a tool to sense and influence that behavior. This mobile persuasion system, called Playful Bottle system, makes use of a mobile phone attached to an everyday drinking mug and motivates office workers to drink healthy quantities of water. A camera and accelerometer sensors in the phone are used to build a vision/motion-based water intake tracker to detect the amount and regularity of water consumed by the user. Additionally, the phone includes hydration games in which natural drinking actions are used as game input. Two hydration games are developed: a single-user TreeGame with automated computer reminders and a multi-user ForestGame with computer-mediated social reminders from members of the group playing the game. Results from 7-week user study with 16 test subjects suggest that both hydration games are effective for encouraging adequate and regular water intake by users. Additionally, results of this study suggest that adding social reminders to the hydration game is more effective than system reminders alone.

We present a new mobile interaction model, called double-side multi-touch, based on a mobile device that receives simultaneous multi-touch input from both the front and the back of the device. This new double-sided multi-touch mobile interaction model enables intuitive finger gestures for manipulating 3D objects and user interfaces on a 2D screen.

In this paper we propose a new video interaction model called adaptive fast-forwarding to help people quickly browse videos with predefined semantic rules. This model is designed around the metaphor of scenic car driving, in which the driver slows down near areas of interest and speeds through unexciting areas. Results from a preliminary user study of our video player suggest the following: (1) the player should adaptively adjust the current playback speed based on the complexity of the present scene and predefined semantic events; (2) the player should learn user preferences about predefined event types as well as a suitable playback speed; (3) the player should fast-forward the video continuously with a playback rate acceptable to the user to avoid missing any undefined events or areas of interest. Furthermore, our user study results suggest that for certain types of video, our SmartPlayer yields better user experiences in browsing and fast-forwarding videos than existing video players' interaction models.

This work proposes the novel use of spinning beacons for precise indoor localization. The proposed "SpinLoc" (Spinning Indoor Localization) system uses "spinning" (i.e., rotating) beacons to create and detect predictable and highly distinguishable Doppler signals for sub-meter localization accuracy. The system analyzes Doppler frequency shifts of signals from spinning beacons, which are then used to calculate orientation angles to a target. By obtaining orientation angles from two or more beacons, SpinLoc can precisely locate stationary or slow-moving targets. After designing and implementing the system using MICA2 motes, its performance was tested in an indoor garage environment. The experimental results revealed a median error of 40~50 centimeters and a 90% error of 70~90 centimeters.

To infer correctly application semantics, sensor network applications often need accurate times on observations that are reported from distributed sensor nodes. Since the nodes' local clocks can go out-of-sync due to clock drifts, a networked time synchronization protocol is needed to synchronize their clocks to a reference clock. This paper provides performance modeling and comparison between two time synchronization protocols: TPSN clock synchronization (clock-sync) and TSS event synchronization (event-sync). Their main difference is that the TPSN clock-sync synchronizes all nodes' local clocks to a global reference clock, whereas TSS event-sync synchronizes events' generation times from different local nodes to their sink nodes' clocks. Although these two time synchronization protocols have their respective limitations in application scenarios, they are comparable in that they also share a large domain with none of these limitations. This paper evaluates these two protocols by considering different ad-hoc network sizes, node mobility levels, and traffic volumes. In order to fully understand the tradeoffs between these two time synchronization protocols, we have derived analytical models on their performances and conducted simulations to measure the impact of these variables. Both the simulation results and analytical models show that (1) event-sync provides much better accuracy than clock-sync, (2) under very high node mobility level, clock-sync may achieve better accuracy than event-sync, and (3) under increasing traffic volume clock-sync scales better.

This case study in UbiComp technology and design presents a "Playful Toothbrush" system for assisting parents and teachers to motivate kindergarten children to learn proper and thorough brushing skills. The system includes a vision-based motion tracker that recognizes different tooth brushing strokes and a tooth brushing game in which the child cleans a virtual, mirror picture of his/her dirty teeth by physically brushing his/her own teeth. The user study results suggest that Playful Toothbrush enhances the effectiveness of kindergarten children in brushing their teeth, as measured by number of brushing strokes, duration of brushing and thoroughness of teeth cleaning.

This study presents the "ChroMirror" system, a digital mirror imaging system which helps users select appropriate clothing color combinations. By digitally rendering a mirror image of the user wearing clothing in different color-harmonic combinations, this system enables users to easily and playfully explore a wide variety of chromatic and color-harmonic clothing combinations (i.e., without having to physically change clothing). A long-term goal of the ChroMirror system is to encourage users to experiment with colorful and color-harmonic clothes.

We present a smart kitchen that can enhance the traditional meal preparation and cooking process by raising awareness of the nutrition facts in food ingredients that go into a meal. The goal is to promote healthy cooking. Our smart kitchen is augmented with sensors to detect cooking activities and provides digital feedbacks to users about nutritional information on the used food ingredients. We have created a preliminary prototype for evaluation, and the result is promising.

With wireless networking technologies extending into the fabrics of our working and operating environments, proper handling of intermittent wireless connectivity and network disruptions is of significance. As the sheer number of potential opportunistic application continues to surge (i.e. wireless sensor networks, underwater sensor networks, pocket switched networks, transportation networks, and etc.), the design for an effective routing scheme that considers and accommodates the various intricate behaviors observed in an opportunistic network is of interest and remained desirable. While previous solutions use either replication or coding techniques to address the challenges in opportunistic networks, the tradeoff of these two techniques only make them ideal under certain network scenarios. In this paper, we propose a hybrid scheme, named H-EC, to deal with a wide variety of opportunistic network cases. H-EC is designed to fully combine the robustness of erasure coding based routing techniques, while preserving the performance advantages of replication techniques. We evaluate H-EC against other similar strategies in terms of delivery ratio and latency, and find that H-EC offers robustness in worst-case delay performance cases while achieving good performance in small delay performance cases. We also discuss the traffic overhead issues associated with H-EC as compared to other schemes, and present several strategies that can potentially alleviate the traffic overhead of H-EC schemes.

Wi-Fi based indoor location systems have been shown to be both cost-effective and accurate, since they can attain meter-level positioning accuracy by using existing Wi-Fi infrastructure in the environment. However, two major technical challenges persist for current Wi-Fi based location systems, instability in positioning accuracy due to changing environmental dynamics, and the need for manual offline calibration during site survey. To address these two challenges, three environmental factors (people, doors, and humidity) that can interfere with radio signals and cause positioning inaccuracy are identified. Then, we have proposed a sensor-assisted adaptation method that employs RFID sensors and environment sensors to adapt the location systems automatically to the changing environmental dynamics. The proposed adaptation method performs online calibration to build multiple context-aware radio maps under various environmental conditions. Experiments were performed on the sensor-assisted adaptation method. The experimental results show that the proposed adaptive method can avoid adverse reduction in positioning accuracy under changing environmental dynamics.

Personal experience computing is about computing support for recording, storing, retrieving, editing, analyzing, and sharing of personal experiences. In this paper, we present our design, implementation and evaluation of a mobile authoring tool called mProducer. mProducer enables a user to generate personal experience content using a mobile device anytime, anywhere. To address challenges in both limited system resources and user interface constraints on a mobile device, mProducer provides several innovative system techniques and UI designs. (1) The Storage Constrained Uploading (SCU) algorithm uploads large multimedia data to remote servers, in order to alleviate the problem of limited storage on a mobile device. (2) Sensor-Assisted Automated Editing utilizes a tilt sensor on the mobile device to automate the detection and removal of blurry frames resulting from excessive amount of camera shaking. This sensor-based solution requires small processing overhead, and it is considered a good alternative to computational-expensive image processing techniques for detecting shaking artifacts. (3) Map-based content management interface incorporates a GPS receiver on a mobile device to record location meta-data for each recording captured by a user, and enables easy, intuitive content navigation on a small screen. (4) Keyframe-based editing enables a user to edit content using only keyframes. We have conducted user studies to evaluate overall editing experience, user satisfaction in the editing quality, task performance time, ease-of-use, and learnability. The results of user studies have shown that keyframe-based editing works best with a storyboard interface. In general, users have found mProducer to be both fun and easy to use on a mobile device.