Learning an Orchestra Conductor's Technique Using a Wearable Sensor Platform

Our study focuses on finding new input devices for a system allowing users with any skill to configure and conduct a virtual orchestra in real-time. As a first step, we conducted a user study to learn more about the interaction between a conductor's gestures and the orchestra 's reaction. During an orchestra rehearsal session, we observed a conductor's timing and gestures using the eWatch, a wrist-worn wearable computer and sensor platform. The gestures are analyzed and compared to the music of the orchestra

dWatch: a Personal Wrist Watch for Smart Environments

Intelligent environments, such as smart homes or domotic systems, have the potential to support people in many of their ordinary activities, by allowing complex control strategies for managing various capabilities of a house or a building: lights, doors, temperature, power and energy, music, etc. Such environments, typically, provide these control strategies by means of computers, touch screen panels, mobile phones, tablets, or In-House Displays. An unobtrusive and typically wearable device, like a bracelet or a wrist watch, that lets users perform various operations in their homes and to receive notifications from the environment, could strenghten the interaction with such systems, in particular for those people not accustomed to computer systems (e.g., elderly) or in contexts where they are not in front of a screen. Moreover, such wearable devices reduce the technological gap introduced in the environment by home automation systems, thus permitting a higher level of acceptance in the daily activities and improving the interaction between the environment and its inhabitants. In this paper, we introduce the dWatch, an off-the-shelf personal wearable notification and control device, integrated in an intelligent platform for domotic systems, designed to optimize the way people use the environment, and built as a wrist watch so that it is easily accessible, worn by people on a regular basis and unobtrusiv

Environmental Sensing by Wearable Device for Indoor Activity and Location Estimation

We present results from a set of experiments in this pilot study to investigate the causal influence of user activity on various environmental parameters monitored by occupant carried multi-purpose sensors. Hypotheses with respect to each type of measurements are verified, including temperature, humidity, and light level collected during eight typical activities: sitting in lab / cubicle, indoor walking / running, resting after physical activity, climbing stairs, taking elevators, and outdoor walking. Our main contribution is the development of features for activity and location recognition based on environmental measurements, which exploit location- and activity-specific characteristics and capture the trends resulted from the underlying physiological process. The features are statistically shown to have good separability and are also information-rich. Fusing environmental sensing together with acceleration is shown to achieve classification accuracy as high as 99.13%. For building applications, this study motivates a sensor fusion paradigm for learning individualized activity, location, and environmental preferences for energy management and user comfort.Comment: submitted to the 40th Annual Conference of the IEEE Industrial Electronics Society (IECON

Analysis of Subscription Demand for Pay-TV

In this paper, we will conduct an analysis from an empirical perspective concerning broadcasting demand behavior and characteristics. More concretely, we will assume three options (subscription patterns), namely, nonsubscription, cable TV subscription, and subscription to broadcasting services via communications satellites (CS), and we will conduct an analysis of broadcasting service demand behavior using a discrete choice model. According to our result, price elasticity is low for cable TV and CS subscribers, which is a contrast to the United States, where price elasticity for paid broadcasting is high. It shows that factors other than price continue to have a strong influence on demand behavior (subscription choices) in the Japanese market for regular and paid broadcasting (the multichannel market) and that the market has not yet entered the phase of price competition between cable TV and CS broadcasting. With regard to channel number elasticity, the figures are high for basic channel service and low for special channel services. This indicates that basic services are an important concern for viewers. This suggests that, in line with reports that the spread of cable TV in the United States was promoted by difficulty in receiving terrestrial broadcasts, basic channel services may be more important than special channels as keys to the spread of paid broadcasting in Japan.Subscription demand, Broadcasting service, Pay-TV, Discrete choice model, Price/Channel elasticity

Anti-Employer Blogging: Employee Breach of the Duty of Loyalty and the Procedure for Allowing Discovery of a Blogger’s Identity Before Service of Process Is Effected

The rapid rise in anonymous anti-employer internet blogs by disgruntled employees has created a tension between the liberty interests of employees in free speech and privacy and employers\u27 rights to be free from defamation, disparagement and disclosure of confidential information by an employee. This iBrief argues that the anonymity of anti-employer bloggers should not shield employees from breach of the duty of loyalty claims under tort and contract law, and that Congress should enact rules to govern the disclosure of blogger identity

Centinela: A human activity recognition system based on acceleration and vital sign data

This paper presents Centinela, a system that combines acceleration data with vital signs to achieve highly accurate activity recognition. Centinela recognizes five activities: walking, running, sitting, ascending, and descending. The system includes a portable and unobtrusive real-time data collection platform, which only requires a single sensing device and a mobile phone. To extract features, both statistical and structural detectors are applied, and two new features are proposed to discriminate among activities during periods of vital sign stabilization. After evaluating eight different classifiers and three different time window sizes, our results show that Centinela achieves up to 95.7% overall accuracy, which is higher than current approaches under similar conditions. Our results also indicate that vital signs are useful to discriminate between certain activities. Indeed, Centinela achieves 100% accuracy for activities such as running and sitting, and slightly improves the classification accuracy for ascending compared to the cases that utilize acceleration data only

Characterizing Natural User Interface with Wearable Smart Watches

Background - The emergence of new interaction paradigms makes the use of technology inrealizing the users??? natural ways of exploring the real world the ultimate goal of designers today.Research on interactive and immersive technologies for user interface design is still a challenging chore for engineers and scientists when it comes to designing natural interaction for wearable smart devices. To address the challenge, our study aims to develop guidelines for design practitioners in designing wearable smart watches that could offer natural user experiences. Methods - To better understand natural user experiences with smart watches, an extensive literature review was conducted. A quantitative survey with 80 participants was conducted, of which the focus was on the expected functions of smart watches. Based on the survey results, we selected eight participants in terms of technology familiarity. To achieve the objectives of our research, three studies were conducted: a design workshop (Study 1), a cultural probe (Study 2), and a focus group interview (Study 3). The design workshop was created to figure out the needs and wishes people have forsmart watches. In the cultural probe, the focus was on figuring out natural interactions with smart watches. Finally, the focus group interview aimed to gain more insights from the results of the cultural probe in terms of natural user interaction with particular functions. Results - To address the needs and wishes of the users toward wearable smartwatches, we made a subdivision into three categories, such as functions, input measures, and notification (feedback) methods. According to the results, participants wanted weather notification, health monitoring, and identification as expected functions. Regarding the methodof input, voice command and touch screen were preferred. In order to get feedback, most of the participantswanted vibrations, particularly as a reaction tocompleting the commands or inputs. There was also a suggestion to customize their smart watch. For example, users can select the functions and build their own command system, and even choose the notificationmethods. Considering natural user interface with respect to functions (weather, answering a call, navigation, health monitoring, taking a picture and messaging), specific natural user interfaces were mentioned for particular functions. Conclusions - Throughout the study, people???s needs and wishes and their perceptions about natural interaction were identified and the characteristics of natural user interfacesweredetermined. Based on the results, tenperceptions were specifically defined to provide a better understanding of smart watches in terms of natural interaction: user affinity of form, awareness by familiarity, reality correspondence, behavioral extension, purpose orientation, easiness of performance, timeliness, routine acceptance, generality, and rule of thumb. In addition to that, natural user interfaces were categorized into five groups: user familiarity, realistic interaction, accomplishment assistance, contextual appropriateness, and social awareness. In this study,we tried to identify what constitutes anatural interaction and how it should be created. The limitations and further study are discussed at the end.ope

ActivityAware: an App for Real-Time Daily Activity Level Monitoring on the Amulet Wrist-Worn Device

Physical activity helps reduce the risk of cardiovascular disease, hypertension and obesity. The ability to monitor a person\u27s daily activity level can inform self-management of physical activity and related interventions. For older adults with obesity, the importance of regular, physical activity is critical to reduce the risk of long-term disability. In this work, we present ActivityAware, an application on the Amulet wrist-worn device that measures daily activity levels (sedentary, moderate and vigorous) of individuals, continuously and in real-time. The app implements an activity-level detection model, continuously collects acceleration data on the Amulet, classifies the current activity level, updates the day\u27s accumulated time spent at that activity level, logs the data for later analysis, and displays the results on the screen. We developed an activity-level detection model using a Support Vector Machine (SVM). We trained our classifiers using data from a user study, where subjects performed the following physical activities: sit, stand, lay down, walk and run. With 10-fold cross validation and leave-one-subject-out (LOSO) cross validation, we obtained preliminary results that suggest accuracies up to 98%, for n=14 subjects. Testing the ActivityAware app revealed a projected battery life of up to 4 weeks before needing to recharge. The results are promising, indicating that the app may be used for activity-level monitoring, and eventually for the development of interventions that could improve the health of individuals

Activity recognition and monitoring using multiple sensors on different body positions.

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