Bodo Urban

Activity Recognition for Everyday Life on Mobile Phones

Mobile applications for activity monitoring are regarded as a high potential field for efficient improvement of health care solutions. The measurement of physical activity within every-day conditions should be as easy as using an automatic weighing machine. Up to now physical activity monitoring required special sensor devices and are not suitable for an every day usage. Movement pattern recognition based on acceleration data enables the usage of standard mobile phones for measurement of physical activity. Now, just by carrying a standard phone in a pocket, the device provides information about the type, intensity and duration of the performed activity. Within the project DiaTrace, we developed the method and algorithm to detect activities like walking, jumping, running, cycling or car driving. Based on activity measurement, this application also calculates the consumed calories over the day, shares activity progress with friends or family and might deliver details about different kinds of transportation during a business trip. The DiaTrace application can easily used today by standard phones which are already equipped with the required sensors.

Ambient interaction by smart watches

The availability of new hardware allows new interaction and visualization metaphors for work environment and private life. Smart watches with integrated acceleration sensors and vibration feedback enable a new kind of interaction. In complement with a matrix display and connectivity to the Internet, smart watches provide assistance in ambient surroundings. This work presents challenges and opportunities of smart watches and introduces a concept of non-obtrusive interaction with smart watches by using physical activity recognition. Hereby the paper presents a prototype application of maintenance assistance and shows possible applications for ambient assistant living environments. In combination of information visualization, permanent sensing and notification, the smart watch becomes the next technology step in the row of smart devices for home-consumer and industrial users.

Screen Coverage: A Pen-Interaction Problem for PDA's and Touch Screen Computers

Touch screens at electronic kiosk systems, pen based PDAs or smart phones, have become more popular over the recent years. The direct interaction on the display by fingers, hands or pens implies the problem of covering the screen. The coverage depends on the interface organization and the use of the interaction elements. This paper describes a basic approach of measuring the coverage of the interface, as well as determination and definitions of basic parameters concerning the ratio between visualization and interaction areas. The metric determination of the coverage leads to analytic testimonies and provides new predictions for resent and future usability tests.

Exploring vibrotactile feedback on the body and foot for the purpose of pedestrian navigation

In this paper, we present an evaluation of vibrotactile onbody feedback for the purpose of pedestrian navigation. For this specific task, many researchers already provide different approaches such as vibrating belts, wristbands or shoes. Still, there are issues left that have to be considered, such as which body position is most suitable, what kind of vibration patterns are easy to interpret, and how applicable are vibrotactile feedback systems in real scenarios. To find answers, we reconstructed prototypes commonly found in literature and continued to further evaluate different foot-related designs. On the one hand, we learned that vibrotactile feedback at the foot reduces visual attention and thus also potentially reduces stress. However, on the other hand, we found that urban space can be very diverse, and ambiguous and therefore a vibrotactile system cannot completely replace common path finding systems for pedestrians. Rather, we envision such a system to be applied complementary as an assistive technology.

Mobile physical activity recognition of stand-up and sit-down transitions for user behavior analysis

Sufficient physical activity is required for everybody, especially for elderly people. Monitoring of physical activity is possible in daily life by using mobile sensors such as acceleration sensors. The recognition of periodic activity types like walking, cycling, car driving etc. is easy to perform. However, the identification of transitions between physical activities is difficult, because those events are nonrecurring and unique. The estimation about the share of standing or sitting during work is interesting for the design of the modern workplace. Human ergonomics demand for a limitation of standing work; this may even be enforced by the legal protection of working mothers to improve the working condition. The recognition of standing and sitting is furthermore useful within the home living area design. Hereby a detection of staying, sitting and walking supports the assessment of the activities of daily life. This paper addresses the methodology of mobile physical activity recognition of transitions between sitting and standing by using only one three-dimensional acceleration sensor. The recognition is performed by using a synthetic kernel signal and a correlation of the measurement signal. For the evaluation, a detection application has been developed which uses the build-in sensors of a standard mobile phone. The evaluation included 12 subjects and the result shows that mobile recognition of activity transitions is possible.

A study on measuring heart- and respiration-rate via wrist-worn accelerometer-based seismocardiography (SCG) in comparison to commonly applied technologies

Since the human body is a living organism, it emits various life signs which can be traced with an action potential sensitive electromyography, but also with motion sensitive sensors such as typical inertial sensors. In this paper, we present a possibility to recognize the heart rate (HR), respiration rate (RR), and the muscular microvibrations (MV) by an accelerometer worn on the wrist. We compare our seismocardiography (SCG) / ballistocardiography (BCG) approach to commonly used measuring methods. In conclusion, our study confirmed that SCG/BCD with a wrist-worn accelerometer also provides accurate vital parameters. While the recognized RR deviated slightly from the ground truth (SD=16.61%), the detection of HR is non-significantly different (SD=1.63%) to the gold standard.

The hearing trousers pocket: activity recognition by alternative sensors

In daily life, mobile phones accompany the user permanently and are worn often in the front pocket of the trousers. The sensors included in todays mobile phones can hence be used for ubiquitous assistance. For instance, the acceleration sensor could be used for analysis of the persons bodily activity, or the microphone can be used to analyze the environmental noise levels. A possible sensor fusion provides additional and assured environmental and context information. This work presents new methods of activity recognition by acceleration and sound sensors by means of sensors included in commercially available smart phones during everyday life. We could identify that sounds provide valuable additional information on a users situation that allow to better asses a persons current context.

Botential: Localizing On-Body Gestures by Measuring Electrical Signatures on the Human Skin

We present Botential, an on-body interaction method for a wearable input device that can identify the location of on-body tapping gestures, using the entire human body as an interactive surface to expand the usually limited interaction space in the context of mobility. When the sensor is being touched, Botential identifies a body parts unique electric signature, which depends on its physiological and anatomical compositions. This input method exhibits a number of advantages over previous approaches, which include: 1) utilizing the existing signal the human body already emits, to accomplish input with various body parts, 2) the ability to also sense soft and long touches, 3) an increased sensing range that covers the whole body, and 4) the ability to detect taps and hovering through clothes.

SeismoTracker: Upgrade any Smart Wearable to enable a Sensing of Heart Rate, Respiration Rate, and Microvibrations

In this paper we present a method to enable any smart Wearable to sense vital data in resting states. These resting states (e.g. sleeping, sitting calmly, etc.) imply the presence of low-amplitude body-motions. Our approach relies on seismocardiography (SCG), which only requires a built-in accelerometer. Compared to commonly applied technologies, such as photoplethysmography (PPG), our approach is not only tracking heart rate (HR), but also respiration rate (RR), and microvibrations (MV) of the muscles, while being also computational inexpensive. In addition, we can calculate several other parameters, such as HR variability and RR variability. Our extracted vital parameters match with the vital data gathered from clinical state-of-the art technology. These data allow us to gain an impression on the users activity, quality of sleep, arousal and stress level over the whole day, week, month, or year. Moreover, we can detect whether a device is actually worn or doffed, which is crucial when connecting such data with health services. We implemented our method on two current smartwatches: a Simvalley AW420 RX as well as on a LG G Watch R and recorded user data for several months. A web platform enables to keep track of ones data.

Situation aware interaction with multi-modal business applications in smart environments

A consistent user experience in combination with proactive assistance may improve the user performance while interacting with heterogeneous data sources as e.g., occurring in business decision making. We describe our approach which is based on inferring the user intentions from sensory inputs, providing a situation aware information assistance, and controlling the environment proactively by anticipating future goals. Our system has been realized within a smart meeting room and has in parts been evaluated. In this paper, we describe the core ideas underlying our approach and report on first findings from the evaluation.