HCI Bibliography Home | HCI Conferences | Pervasive Archive | Detailed Records | RefWorks | EndNote | Hide Abstracts
Pervasive Tables of Contents: 02040506070809101112

Proceedings of Pervasive 2010: International Conference on Pervasive Computing

Fullname:Pervasive 2010: Pervasive Computing, 8th International Conference
Editors:Patrik Floréen; Antonio Krüger; Mirjana Spasojevic
Location:Helsinki, Finland
Dates:2010-May-17 to 2010-May-17
Publisher:Springer-Verlag
Series:Lecture Notes in Computer Science 6030 Springer 2010
Standard No:ISBN 978-3-642-12653-6; hcibib: Pervasive10
Papers:25
Pages:444
Links:Online Proceedings
  1. Positioning
  2. Navigation and Tracking
  3. Applications
  4. Tools, Modelling
  5. Studies
  6. Activity Recognition
  7. Sensing
  8. Resource Awareness
  9. Interaction

Positioning

Virtual Compass: Relative Positioning to Sense Mobile Social Interactions BIBAFull-Text 1-21
  Nilanjan Banerjee; Sharad Agarwal; Paramvir Bahl; Ranveer Chandra; Alec Wolman; Mark D. Corner
There are endless possibilities for the next generation of mobile social applications that automatically determine your social context. A key element of such applications is ubiquitous and precise sensing of the people you interact with. Existing techniques that rely on deployed infrastructure to determine proximity are limited in availability and accuracy. Virtual Compass is a peer-based relative positioning system that relies solely on the hardware and operating system support available on commodity mobile handhelds. It uses multiple radios to detect nearby mobile devices and places them in a two-dimensional plane. It uses adaptive scanning and out-of-band coordination to explore trade-offs between energy consumption and the latency in detecting movement. We have implemented Virtual Compass on mobile phones and laptops, and we evaluate it using a sample application that senses social interactions between Facebook friends.
The Geography of Taste: Analyzing Cell-Phone Mobility and Social Events BIBAFull-Text 22-37
  Francesco Calabrese; Francisco C. Pereira; Giusy Di Lorenzo; Liu Liang; Carlo Ratti
This paper deals with the analysis of crowd mobility during special events. We analyze nearly 1 million cell-phone traces and associate their destinations with social events. We show that the origins of people attending an event are strongly correlated to the type of event, with implications in city management, since the knowledge of additive flows can be a critical information on which to take decisions about events management and congestion mitigation.
Indoor Positioning Using GPS Revisited BIBAFull-Text 38-56
  Mikkel Baun Kjærgaard; Henrik Blunck; Torben Godsk; Thomas Toftkjær; Dan Lund Christensen; Kaj Grønbæk
It has been considered a fact that GPS performs too poorly inside buildings to provide usable indoor positioning. We analyze results of a measurement campaign to improve on the understanding of indoor GPS reception characteristics. The results show that using state-of-the-art receivers GPS availability is good in many buildings with standard material walls and roofs. The measured root mean squared 2D positioning error was below five meters in wooden buildings and below ten meters in most of the investigated brick and concrete buildings. Lower accuracies, where observed, can be linked to either low signal-to-noise ratios, multipath phenomena or bad satellite constellation geometry. We have also measured the indoor performance of embedded GPS receivers in mobile phones which provided lower availability and accuracy than state-of-the-art ones. Finally, we consider how the GPS performance within a given building is dependent on local properties like close-by building elements and materials, number of walls, number of overlaying stories and surrounding buildings.

Navigation and Tracking

Specification and Verification of Complex Location Events with Panoramic BIBAFull-Text 57-75
  Evan Welbourne; Magdalena Balazinska; Gaetano Borriello; James Fogarty
We present the design and evaluation of Panoramic, a tool that enables end-users to specify and verify an important family of complex location events. Our approach aims to reduce or eliminate critical barriers to deployment of emerging location-aware business activity monitoring applications in domains like hospitals and office buildings. Panoramic does not require users to write code, understand complex models, perform elaborate demonstrations, generate test location traces, or blindly trust deterministic events. Instead, it allows end-users to specify and edit complex events with a visual language that embodies natural concepts of space and time. It also takes a novel approach to verification, in which events are extracted from historical sensor data traces and then presented with intelligible, hierarchical visualizations that represent uncertainty with probabilities. We build on our existing software for specifying and detecting events while enhancing it in non-trivial ways to facilitate event specification and verification. Our design is guided by a formative study with 12 non-programmers. We also use location traces from a building-scale radio frequency identification (RFID) deployment in a qualitative evaluation of Panoramic with 10 non-programmers. The results show that end-users can both understand and verify the behavior of complex location event specifications using Panoramic.
Tactile Wayfinder: Comparison of Tactile Waypoint Navigation with Commercial Pedestrian Navigation Systems BIBAKFull-Text 76-93
  Martin Pielot; Susanne Boll
In this paper we report on a field study comparing a commercial pedestrian navigation system to a tactile navigation system called Tactile Wayfinder. Similar to previous approaches the Tactile Wayfinder uses a tactile torso display to present the directions of a route's waypoints to the user. It advances those approaches by conveying the location of the next two waypoints rather than the next one only, so the user already knows how the route continues when reaching a waypoint. Using a within-subjects design, fourteen participants navigated along two routes in a busy city centre with the Tactile Wayfinder and a commercial pedestrian navigation system. We measured the acquisition of spatial knowledge, the level of attention the participants had to devote to the navigation task, and the navigation performance. We found that the Tactile Wayfinder freed the participants' attention but could not keep up with the navigation system in terms of navigation performance. No significant difference was found in the acquisition of spatial knowledge. Instead, a good general sense of direction was highly correlated with good spatial knowledge acquisition and a good navigation performance.
Keywords: Tactile Displays; Pedestrian Navigation; Wayfinding; Tactons

Applications

Jog Falls: A Pervasive Healthcare Platform for Diabetes Management BIBAKFull-Text 94-111
  Lama Nachman; Amit Baxi; Sangeeta Bhattacharya; Vivek Darera; Piyush Deshpande; Nagaraju Kodalapura; Vincent Mageshkumar; Satish Rath; Junaith Shahabdeen; Raviraja Acharya
This paper presents Jog Falls, an end to end system to manage diabetes that blends activity and energy expenditure monitoring, diet-logging, and analysis of health data for patients and physicians. It describes the architectural details, sensing modalities, user interface and the physician's backend portal. We show that the body wearable sensors accurately estimate the energy expenditure across a varied set of active and sedentary states through the fusion of heart rate and accelerometer data. The GUI ensures continuous engagement with the patient by showing the activity goals, current and past activity states and dietary records along with its nutritional values. The system also provides a comprehensive and unbiased view of the patient's activity and food intake trends to the physician, hence increasing his/her effectiveness in coaching the patient. We conducted a user study using Jog Falls at Manipal University, a leading medical school in India. The study involved 15 participants, who used the system for 63 days. The results indicate a strong positive correlation between weight reduction and hours of use of the system.
Keywords: Personal Health Monitoring; Diabetes Management; Energy Expenditure Analysis; Activity monitoring
EyeCatcher: A Digital Camera for Capturing a Variety of Natural Looking Facial Expressions in Daily Snapshots BIBAFull-Text 112-129
  Koji Tsukada; Maho Oki
This paper proposes a novel interactive technique, the EyeCatcher, which helps photographers capture a variety of natural looking facial expressions of their subjects, by keeping the eyes of the subjects focused on the camera without the stress usually associated with being photographed. We develop a prototype system and verify the effectiveness through evaluation and discussion.
TreasurePhone: Context-Sensitive User Data Protection on Mobile Phones BIBAFull-Text 130-137
  Julian Seifert; Alexander De Luca; Bettina Conradi; Heinrich Hussmann
Due to increased input and output capabilities, mobile phones hold many different kinds of (mostly private) data. The need for finer grained profiles and integrated data security on mobile phones has already been documented extensively (e.g. [1]). However, there are no appropriate concepts and implementations yet to handle and limit access to data on mobile phones. TreasurePhone has been designed to address this specific problem. It protects the users' mobile phone data based on their current context. Privacy protection is realized by spheres, which represent the users' context-specific need for privacy. That is, users can define which data and services are accessible in which sphere. TreasurePhone exploits context information to support authentication and automatic activation of spheres by locations and actions. We conducted a user study with 20 participants to gain insights on how well users accept such a concept. One of the main goals was to find out whether such privacy features are appreciated by the users even though they make interaction slower and might hinder fast access to specific data. Additionally, we showed that integration of context information significantly increases ease-of-use of the system.

Tools, Modelling

Recruitment Framework for Participatory Sensing Data Collections BIBAKFull-Text 138-155
  Sasank Reddy; Deborah Estrin; Mani B. Srivastava
Mobile phones have evolved from devices that are just used for voice and text communication to platforms that are able to capture and transmit a range of data types (image, audio, and location). The adoption of these increasingly capable devices by society has enabled a potentially pervasive sensing paradigm -- participatory sensing. A coordinated participatory sensing system engages individuals carrying mobile phones to explore phenomena of interest using in situ data collection. For participatory sensing to succeed, several technical challenges need to be solved. In this paper, we discuss one particular issue: developing a recruitment framework to enable organizers to identify well-suited participants for data collections based on geographic and temporal availability as well as participation habits. This recruitment system is evaluated through a series of pilot data collections where volunteers explored sustainable processes on a university campus.
Keywords: Mobile Computing; Participatory Sensing; Urban Sensing
Out of the Lab and into the Fray: Towards Modeling Emotion in Everyday Life BIBAKFull-Text 156-173
  Jennifer Healey; Lama Nachman; Sushmita Subramanian; Junaith Shahabdeen; Margaret E. Morris
We conducted a 19 participant study using a system comprised of wireless galvanic skin response (GSR), heart rate (HR), activity sensors and a mobile phone for aggregating sensor data and enabling affect logging by the user. Each participant wore the sensors daily for five days, generating approximately 900 hours of continuous data. We found that analysis of emotional events was highly dependent on correct windowing and report results on synthesized windows around annotated events. Where raters agreed on the timing and quality of the emotion we were able to recognize 85% of the high and low energy emotions and 70% of the positive and negative emotions. We also gained many insights regarding participant's perception of their emotional state and the complexity of emotion in real life.
Keywords: Affective computing; emotional sensing; mood detection
The Secret Life of Machines -- Boundary Objects in Maintenance, Repair and Overhaul BIBAKFull-Text 174-191
  Matthias Betz
The increasing level of automation in tight just-in-time subcontracting relationships in the automotive industry makes the complex, weak structured, knowledge intense and highly cooperative practice of Reactive Maintenance (RM) in Maintenance Repair and Overhaul (MRO) in this branch a demanding and stressful job. In this paper two typical breakdown situations are presented which occurred in a participative observation to gain insights to this field. Based on the analysis of the observations and the existing MRO related IT infrastructure we refer to the theoretical concept of 'boundary objects' to understand the practice in this field. Finally, implications for design for a MRO supporting pervasive computing environment are derived from this conceptualization. We highlight the potentials of attaching relevant information to physical objects in place to support and motivate documentation by bridging the physical world of machines with the virtual information space and to enhance the discovering of relevant information in breakdowns situations.
Keywords: maintenance; repair; overhaul; collaboration; boundary-objects; histories; practice; observation; UbiComp; autoID; physical; sensor-networks

Studies

Automatic Assessment of Cognitive Impairment through Electronic Observation of Object Usage BIBAFull-Text 192-209
  Mark R. Hodges; Ned Kirsch; Mark W. Newman; Martha E. Pollack
Indications of cognitive impairments such as dementia and traumatic brain injury (TBI) are often subtle and may be frequently missed by primary care physicians. We describe an experiment where we unobtrusively collected sensor data as individuals with TBI performed a routine daily task (making coffee). We computed a series of four features of the sensor data that were increasingly representative of the task, and that we hypothesized might correlate with severity of cognitive impairment. Our main result is a significant correlation between the most representational feature and an apparent indicator of general neuropsychological integrity, namely, the first principal component of a standard suite of neuropsychological assessments. We also found suggestive but preliminary evidence of correlations between the computed features and a number of the individual tests in the assessment suite; this evidence can be used as the basis of larger-scale studies to validate significance.
Further into the Wild: Running Worldwide Trials of Mobile Systems BIBAKFull-Text 210-227
  Donald McMillan; Alistair Morrison; Owain Brown; Malcolm Hall; Matthew Chalmers
Many studies of ubiquitous computing systems involve deploying a system to a group of users who will be studied through direct observation, interviews and the gathering of system log data. However, such studies are often limited in the number of participants and duration of the trial, particularly if the researchers are providing the participants with hardware. Apple's App Store and similar application repositories have become popular with smartphone users, yet few ubiquitous computing studies have yet utilised these distribution mechanisms. We describe our experiences of running a very large scale trial where such a distribution model is used to recruit thousands of users for a mobile system trial that can be run continuously with no constrained end date. We explain how we conducted such a trial, covering issues such as data logging and interviewing users based in several different continents. Benefits and potential shortcomings of running a trial in this way are discussed and we offer guidance on ways to help manage a large and disparate user-base using in-application feedback measures and web-based social networking applications. We describe how, through these methods, we were able to further the development of a piece of ubiquitous computing software through user-informed design on a mass scale.
Keywords: Evaluation Techniques; Large Scale Deployment; Trial Methods
Studying the Use and Utility of an Indoor Location Tracking System for Non-experts BIBAKFull-Text 228-245
  Shwetak N. Patel; Julie A. Kientz; Sidhant Gupta
Indoor location tracking systems have been a major focus of ubiquitous computing research, and they have much promise to help in collecting objective, real time data for applications and supporting studies. However, due to their typically difficult and time consuming installation process, few have explored the extent to which they can be used by non-experts. In this research, we studied how one location tracking system, PowerLine Positioning, could be used by non-technology expert rehabilitation researchers to study the mobility patterns of wheelchair users in their homes. We determined that indoor location tracking systems are not only usable by non-experts, but they can also be useful in allowing them to achieve their own research goals of obtaining objective mobility data. Based on the results, we provide areas for future exploration and implications for designers of location-based and other types of sensing systems which aim to be end-user deployable.
Keywords: Location; indoor location sensing; end-user deployable; accessibility; wheelchair users; PowerLine Positioning; user study

Activity Recognition

Object-Based Activity Recognition with Heterogeneous Sensors on Wrist BIBAKFull-Text 246-264
  Takuya Maekawa; Yutaka Yanagisawa; Yasue Kishino; Katsuhiko Ishiguro; Koji Kamei; Yasushi Sakurai; Takeshi Okadome
This paper describes how we recognize activities of daily living (ADLs) with our designed sensor device, which is equipped with heterogeneous sensors such as a camera, a microphone, and an accelerometer and attached to a user's wrist. Specifically, capturing a space around the user's hand by employing the camera on the wrist mounted device enables us to recognize ADLs that involve the manual use of objects such as making tea or coffee and watering plant. Existing wearable sensor devices equipped only with a microphone and an accelerometer cannot recognize these ADLs without object embedded sensors. We also propose an ADL recognition method that takes privacy issues into account because the camera and microphone can capture aspects of a user's private life. We confirmed experimentally that the incorporation of a camera could significantly improve the accuracy of ADL recognition.
Keywords: Wearable sensors; Recognizing daily activities; Experiment
GasSense: Appliance-Level, Single-Point Sensing of Gas Activity in the Home BIBAKFull-Text 265-282
  Gabe Cohn; Sidhant Gupta; Jon Froehlich; Eric C. Larson; Shwetak N. Patel
This paper presents GasSense, a low-cost, single-point sensing solution for automatically identifying gas use down to its source (e.g., water heater, furnace, fireplace). This work adds a complementary sensing solution to the growing body of work in infrastructure-mediated sensing. GasSense analyzes the acoustic response of a home's government mandated gas regulator, which provides the unique capability of sensing both the individual appliance at which gas is currently being consumed as well as an estimate of the amount of gas flow. Our approach provides a number of appealing features including the ability to be easily and safely installed without the need of a professional. We deployed our solution in nine different homes and initial results show that GasSense has an average accuracy of 95.2% in identifying individual appliance usage.
Keywords: Ubiquitous Computing; Sustainability; Sensing; Gas
Transferring Knowledge of Activity Recognition across Sensor Networks BIBAFull-Text 283-300
  Tim van Kasteren; Gwenn Englebienne; Ben J. A. Kröse
A problem in performing activity recognition on a large scale (i.e. in many homes) is that a labelled data set needs to be recorded for each house activity recognition is performed in. This is because most models for activity recognition require labelled data to learn their parameters. In this paper we introduce a transfer learning method for activity recognition which allows the use of existing labelled data sets of various homes to learn the parameters of a model applied in a new home. We evaluate our method using three large real world data sets and show our approach achieves good classification performance in a home for which little or no labelled data is available.

Sensing

Common Sense Community: Scaffolding Mobile Sensing and Analysis for Novice Users BIBAKFull-Text 301-318
  Wesley Willett; Paul M. Aoki; Neil Kumar; Sushmita Subramanian; Allison Woodruff
As sensing technologies become increasingly distributed and democratized, citizens and novice users are becoming responsible for the kinds of data collection and analysis that have traditionally been the purview of professional scientists and analysts. Leveraging this citizen engagement effectively, however, requires not only tools for sensing and data collection but also mechanisms for understanding and utilizing input from both novice and expert stakeholders. When successful, this process can result in actionable findings that leverage and engage community members and build on their experiences and observations. We explored this process of knowledge production through several dozen interviews with novice community members, scientists, and regulators as part of the design of a mobile air quality monitoring system. From these interviews, we derived design principles and a framework for describing data collection and knowledge generation in citizen science settings, culminating in the user-centered design of a system for community analysis of air quality data. Unlike prior systems, ours breaks analysis tasks into discrete mini-applications designed to facilitate and scaffold novice contributions. An evaluation we conducted with community members in an area with air quality concerns indicates that these mini-applications help participants identify relevant phenomena and generate local knowledge contributions.
Keywords: Air quality monitoring; citizen science; environmental science; mobile sensing; participatory sensing; qualitative studies
Active Capacitive Sensing: Exploring a New Wearable Sensing Modality for Activity Recognition BIBAFull-Text 319-336
  Jingyuan Cheng; Oliver Amft; Paul Lukowicz
The paper describes the concept, implementation, and evaluation of a new on-body capacitive sensing approach to derive activity related information. Using conductive textile based electrodes that are easy to integrate in garments, we measure changes in capacitance inside the human body. Such changes are related to motions and shape changes of muscle, skin, and other tissue, which can in turn be related to a broad range of activities and physiological parameters. We describe the physical principle, the analog hardware needed to acquire and pre-process the signal, and example signals from different body locations and actions. We perform quantitative evaluations of the recognition accuracy, focused on the specific example of collar-integrated electrodes and actions, such as chewing, swallowing, speaking, sighing (taking a deep breath), as well as different head motions and positions.
Using Height Sensors for Biometric Identification in Multi-resident Homes BIBAFull-Text 337-354
  Vijay Srinivasan; John A. Stankovic; Kamin Whitehouse
In this study, we evaluate the use of height for biometric identification of residents, by mounting ultrasonic distance sensors above the doorways in a home. Height sensors are cheap, are convenient for the residents, are simple to install in an existing home, and are perceived to be less invasive than cameras or microphones. Height is typically only a weak biometric, but we show that it is well suited for identifying among a few residents in the home, and can potentially be improved by using the history of height measurements at multiple doorways in a tracking approach. We evaluate this approach using 20 people in a controlled laboratory environment and by installing in 3 natural, home environments. We combine these results with public anthropometric data sets that contain the heights of residents in 2077 elderly multi-resident homes to conclude that height sensors could potentially achieve at least 95% identification accuracy in 95% of elderly homes in the US.

Resource Awareness

Supporting Energy-Efficient Uploading Strategies for Continuous Sensing Applications on Mobile Phones BIBAFull-Text 355-372
  Mirco Musolesi; Mattia Piraccini; Kristof Fodor; Antonio Corradi; Andrew T. Campbell
Continuous sensing applications (e.g., mobile social networking applications) are appearing on new sensor-enabled mobile phones such as the Apple iPhone, Nokia and Android phones. These applications present significant challenges to the phone's operations given the phone's limited computational and energy resources and the need for applications to share real-time continuous sensed data with back-end servers. System designers have to deal with a trade-off between data accuracy (i.e., application fidelity) and energy constraints in the design of uploading strategies between phones and back-end servers. In this paper, we present the design, implementation and evaluation of several techniques to optimize the information uploading process for continuous sensing on mobile phones. We analyze the cases of continuous and intermittent connectivity imposed by low-duty cycle design considerations or poor wireless network coverage in order to drive down energy consumption and extend the lifetime of the phone. We also show how location prediction can be integrated into this forecasting framework. We present the implementation and the experimental evaluation of these uploading techniques based on measurements from the deployment of a continuous sensing application on 20 Nokia N95 phones used by 20 people for a period of 2 weeks. Our results show that we can make significant energy savings while limiting the impact on the application fidelity, making continuous sensing a viable application for mobile phones. For example, we show that it is possible to achieve an accuracy of 80% with respect to ground-truth data while saving 60% of the traffic sent over-the-air.
Efficient Resource-Aware Hybrid Configuration of Distributed Pervasive Applications BIBAFull-Text 373-390
  Stephan Schuhmann; Klaus Herrmann; Kurt Rothermel
As the size and complexity of Pervasive Computing environments increases, configuration and adaptation of distributed applications gains importance. These tasks require automated system support, since users must not be distracted by the (re-)composition of applications. In homogeneous ad hoc scenarios, relying on decentralized configuration schemes is obviously mandatory, while centralized approaches may help to reduce latencies in weakly heterogeneous infrastructure-based environments. However, in case of strongly heterogeneous pervasive environments including several resource-rich and resource-weak devices, both approaches may lead to suboptimal results concerning configuration latencies: While the resource-weak devices represent bottlenecks for decentralized configuration, the centralized approach faces the problem of not utilizing parallelism. Instead, a hybrid approach that involves only the subset of resource-rich devices is capable of rendering configuration and adaptation processes more efficiently. In this paper, we present such a resource-aware hybrid scheme that effectively reduces the time required for configuration processes. This is accomplished by a balanced-load clustering scheme that exploits the computational power of resource-rich devices, while avoiding bottlenecks in (re-)configurations. We present real-world evaluations which confirm that our approach reduces configuration latencies in heterogeneous environments by more than 30% compared to totally centralized and totally decentralized approaches. This is an important step towards seamless application configuration.

Interaction

12Pixels: Exploring Social Drawing on Mobile Phones BIBAKFull-Text 391-408
  Karl D. D. Willis; Ivan Poupyrev
In this paper we present the design and development of 12Pixels, a novel interface, application, and social web service that allows people to create and share drawings directly from a regular mobile phone. We detail the release of 12Pixels as a service in Japan and analyze trends that emerged from user data collected. Our analysis and insights provide useful ground-level experiences with social drawing and mobile content creation.
Keywords: 12Pixels; twelve pixels; drawing; mobile phone; cellphone; art; design; creativity; creativity support tools; content creation; user generated content; social web; web applications
No-Look Notes: Accessible Eyes-Free Multi-touch Text Entry BIBAKFull-Text 409-426
  Matthew N. Bonner; Jeremy T. Brudvik; Gregory D. Abowd; W. Keith Edwards
Mobile devices with multi-touch capabilities are becoming increasingly common, largely due to the success of the Apple iPhone and iPod Touch. While there have been some advances in touchscreen accessibility for blind people, touchscreens remain inaccessible in many ways. Recent research has demonstrated that there is great potential in leveraging multi-touch capabilities to increase the accessibility of touchscreen applications for blind people. We have created No-Look Notes, an eyes-free text entry system that uses multi-touch input and audio output. No-Look Notes was implemented on Apple's iPhone platform. We have performed a within-subjects (n=10) user study of both No-Look Notes and the text entry component of Apple's VoiceOver, the recently released official accessibility component on the iPhone. No-Look Notes significantly outperformed VoiceOver in terms of speed, accuracy and user preference.
Keywords: accessibility; mobile device; multi-touch; touchscreen; text entry; eyes-free
On the Use of Brain Decoded Signals for Online User Adaptive Gesture Recognition Systems BIBAFull-Text 427-444
  Kilian Förster; Andrea Biasiucci; Ricardo Chavarriaga; José del R. Millán; Daniel Roggen; Gerhard Tröster
Activity and context recognition in pervasive and wearable computing ought to continuously adapt to changes typical of open-ended scenarios, such as changing users, sensor characteristics, user expectations, or user motor patterns due to learning or aging. System performance inherently relates to the user's perception of the system behavior. Thus, the user should be guiding the adaptation process. This should be automatic, transparent, and unconscious.
   We capitalize on advances in electroencephalography (EEG) signal processing that allow for error related potentials (ErrP) recognition. ErrP are emitted when a human observes an unexpected behavior in a system. We propose and evaluate a hand gesture recognition system from wearable motion sensors that adapts online by taking advantage of ErrP. Thus the gesture recognition system becomes self-aware of its performance, and can self-improve through re-occurring detection of ErrP signals.
   Results show that our adaptation technique can improve the accuracy of a user independent gesture recognition system by 13.9% when ErrP recognition is perfect. When ErrP recognition errors are factored in, recognition accuracy increases by 4.9%. We characterize the boundary conditions of ErrP recognition guaranteeing beneficial adaptation. The adaptive algorithms are applicable to other forms of activity recognition, and can also use explicit user feedback rather than ErrP.