daniel olguin

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Capturing Individual and Group Behavior with Wearable Sensors

We show how to obtain high level descriptions of human behavior in terms of physical activity, sp... more We show how to obtain high level descriptions of human behavior in terms of physical activity, speech activity, face-to-face interaction (f2f), physical proximity, and social network attributes from sensor data. We present experimental results that show that it is possible to identify individual personality traits as well as subjective and objective group performance metrics from low level data collected using wearable sensors.

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Assessing Group Performance from Collective Behavior

The Human Dynamics research group at the MIT Media Laboratory has demonstrated that wearable tech... more The Human Dynamics research group at the MIT Media Laboratory has demonstrated that wearable technology can be used to characterize face-to-face interactions, measure individual and collective patterns of human behavior, and automatically map out a company's de facto organizational chart . This capability can be an extraordinary resource for studying group behavior, group performance and team formation processes.

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Sensible organizations: Technology and methodology for automatically measuring organizational behavior

We present the design, implementation, and deployment of a wearable computing platform for measur... more We present the design, implementation, and deployment of a wearable computing platform for measuring and analyzing human behavior in organizational settings. We propose the use of wearable electronic badges capable of automatically measuring the amount of face-to-face interaction, conversational time, physical proximity to other people, and physical activity levels in order to capture individual and collective patterns of behavior. Our goal is to be able to understand how patterns of behavior shape individuals and organizations. By using on-body sensors in large groups of people for extended periods of time in naturalistic settings, we have been able to identify, measure, and quantify social interactions, group behavior, and organizational dynamics. We deployed this wearable computing platform in a group of 22 employees working in a real organization over a period of one month. Using these automatic measurements, we were able to predict employees' self-assessments of job satisfaction and their own perceptions of group interaction quality by combining data collected with our platform and e-mail communication data. In particular, the total amount of communication was predictive of both of these assessments, and betweenness in the social network exhibited a high negative correlation with group interaction satisfaction. We also found that physical proximity and e-mail exchange had a negative correlation of r = −0.55 (p < 0.01), which has far-reaching implications for past and future research on social networks.

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Sensible Organizations: A Sensor-Based System for Organizational Design and Engineering

We propose a sensor-based organizational design system capable of measuring social interactions i... more We propose a sensor-based organizational design system capable of measuring social interactions in the workplace. By combining behavioral sensor data with other sources of information such as text-mined documents, surveys, and performance data we can re-engineer organizations and make better informed decisions. The proposed system combines sensor measurements, pattern recognition algorithms, simulation and optimization techniques, social network analysis, and feedback mechanisms that aim at continuously monitoring and improving individual and group performance. We describe the system's general specifications and discuss preliminary studies that we have conducted in several organizations using an experimental sensing platform.

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Sensor-based organizational engineering

Proceedings of the Icmi Mlmi 09 Workshop, Nov 6, 2009

We propose the use of wearable and environmental sensors to capture and model social interactions... more We propose the use of wearable and environmental sensors to capture and model social interactions in the workplace, combined with data mining techniques and social network analysis for organizational engineering applications. By combining behavioral sensor data with other sources of information such as text-mined documents, surveys, and performance data, it is possible to optimize organizations.

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Social Sensing And Behavior Analysis System

Adaptive digital filtering algorithms for the elimination of power line interference in electroencephalographic signals

... 3, Adaptive IIR filtering: Current results and open issues - Jr - 1984. 2, Eriksen “Non-Disto... more

Teaching and research laboratory simulator of electric power systems

FIE'99 Frontiers in Education. 29th Annual Frontiers in Education Conference. Designing the Future of Science and Engineering Education. Conference Proceedings (IEEE Cat. No.99CH37011, 1999

A teaching and research laboratory simulator (TRLS) has been developed as a tool to validate digi... more A teaching and research laboratory simulator (TRLS) has been developed as a tool to validate digital models of electric power systems. The simulator includes synchronous machines, transformers, transmission system and dynamic and static loads. This paper describes the simulator and presents some recorded transients of a synchronous machine. Some variables of the system, registered during the starting of an induction

A method for initializing induction motors modeling during power system transient stability studies

IEEE International Electric Machines and Drives Conference. IEMDC'99. Proceedings (Cat. No.99EX272), 1999

This paper describes a steady state method for power flow programs and is one solution to the pro... more This paper describes a steady state method for power flow programs and is one solution to the problem of initializing the dynamic models of the induction motor for transient stability studies. In the method the steady state induction motor model is included in the initial Newton Raphson power flow study, so the values of slip and reactive power of the

Social Sensors for Automatic Data Collection

We propose a social network data collection method that uses wearable social sensors to automatic... more We propose a social network data collection method that uses wearable social sensors to automatically detect social interactions. This method offers clear advantages over traditional methods since data is automatically collected by electronic sensors rather than humans. We present the design, implementation and deployment of a wearable social sensing platform that can measure and analyze human behavior in a variety

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Sensor-Based Feedback Systems in Organizational Computing

2009 International Conference on Computational Science and Engineering, 2009

Radical change is needed in today's organizations. While e-mail, instant messaging, wikis, predic... more Radical change is needed in today's organizations. While e-mail, instant messaging, wikis, prediction markets, and the like have proliferated across myriad sectors, the fundamental practice of management has failed to keep pace. Sensors can automatically measure social behavior occurring in physical space as well as the virtual world. Moreover sensor-based feedback is poised to help create the change necessary to improve performance and satisfaction of workers. In this paper we summarize previous work on sensor-based feedback systems and propose new systems at the individual, group, and organizational level. Our goal is to help direct future research towards these promising avenues.

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Sensor-based organisational design and engineering

International Journal of Organisational Design and Engineering, 2010

Towards “Honest Signals” of Creativity – Identifying Personality Characteristics Through Microscopic Social Network Analysis

Procedia - Social and Behavioral Sciences, 2011

This paper presents preliminary results on predicting individual creativity based on interpersona... more This paper presents preliminary results on predicting individual creativity based on interpersonal interaction patterns. We combine insights from analyzing communication in an E-mail student network of a distributed course with measurements of interaction by sociometric badges for 23 programmers in Northern Europe. In the first case study we measure communication patterns of 23 software developers in a Nordic country through sociometric badges over a period of 4 weeks, associating it with creativity and productivity collected by a daily questionnaire. At the same time we collected individual trust through another questionnaire. We found that the more central people are in the network, the more trusting they are, and the less they oscillate between low and high states of energy, the more trusting they are. The second case study is based on a sample of 17 students from a German university participating in a multinational course. We show that e-mail behavior is associated with personality type as measured by the FFI personality test. We found that the larger degree and betweenness centrality of students in the e-mail course network is, the more agreeable and less neurotic they are. The faster students respond to e-mail, the more open and agreeable they are. The smaller the contribution index of students is, i.e. the less e-mails they send relative to other team members, the more neurotic they are. We speculate that there might be two different types of creativity, "lonely genius" -feeling most creative when on his/her own with lower trust in others, and "swarm creative" -most creative when in the midst of other people, and with higher trust.

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Analyzing the Flow of Knowledge with Sociometric Badges

Procedia - Social and Behavioral Sciences, 2010

This paper presents a collection of “best practices” for the use of “Sociometric Badges” that sup... more This paper presents a collection of “best practices” for the use of “Sociometric Badges” that support automatic collection of face-to-face interaction between workers within an organization. The practices presented aim to improve data quality over legacy methods allowing insights into the processes and structures of an enterprise&amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;#x27;s de-facto communication networks. Our approach uses dynamic Social Network Analysis (dSNA) to make it easier for executives to analyze and manage communications networks. The ...

Sensible Organizations: Changing Our Businesses and Work Styles through Sensor Data

Journal of Information Processing, 2008

We introduce the concept of sensor-based applications for the daily business settings of organiza... more We introduce the concept of sensor-based applications for the daily business settings of organizations and their individual workers. Wearable sensor devices were developed and deployed in a real organization, a bank, for a month in order to study the effectiveness and potential of using sensors at the organizational level. It was found that patterns of physical interaction changed dynamically while e-mail is more stable from day to day. Different patterns of behavior between people in different rooms and teams (p < 0.01), as well as correlations between communication and a worker's subjective productivity, were also identified. By analyzing a fluctuation of network parameters, i.e., "betweenness centrality," it was also found that communication patterns of people are different: some people tend to communicate with the same people in regular frequency (which is hypothesized as a typical pattern of throughput-oriented jobs) while some others drastically changed their communication day by day (which is hypothesized as a pattern of creative jobs). Based on these hypotheses, a reorganization, such that people having similar characteristics work together, was proposed and implemented.

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Mobile Sensing Technologies and Computational Methods for Collective Intelligence

Studies in Computational Intelligence, 2011

This book chapter is a review of mobile sensing technologies and computational methods for collec... more This book chapter is a review of mobile sensing technologies and computational methods for collective intelligence. We discuss the application of mobile sensing to understand collective mechanisms and phenomena in face-to-face networks at three different scales: organizations, communities and societies. We present an overview of the state-of-the art in individual behavior recognition from sensor data. We discuss related work on

Mapping Organizational Dynamics with Body Sensor Networks

2012 Ninth International Conference on Wearable and Implantable Body Sensor Networks, 2012

This paper demonstrates a novel approach that combines generative models of organizational dynami... more This paper demonstrates a novel approach that combines generative models of organizational dynamics and sensor network data with a stochastic method. Generative models specify how organizational performance is related to who interacts with whom and who performs what. Sensor network data track who interacts with whom and who performs what within an organization, and the stochastic methodology fits multi-agent models

Wearable sensors for pervasive healthcare management

Proceedings of the 3d International ICST Conference on Pervasive Computing Technologies for Healthcare, 2009

We show that it is possible to identify individual personality traits and measure group performan... more We show that it is possible to identify individual personality traits and measure group performance in a Postanesthesia Care Unit (PACU) using wearable sensors. We instrumented a group of 67 nurses working in the PACU of a Boston area hospital with sociometric badges capable of measuring physical activity, speech activity, face-to-face interaction, and physical proximity. Using the data collected with these sensors we were able to estimate the daily average length of stay (LOS) and number of delays.

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Studying Microscopic Peer-to-Peer Communication Patterns

SSRN Electronic Journal, 2000

This paper describes first results of an ongoing research effort using real time data collected b... more This paper describes first results of an ongoing research effort using real time data collected by social badges to correlate temporal changes in social interaction patterns with performance of individual actors and groups. Towards that goal we analyzed social interaction among a team of employees at a bank in Germany, and developed a set of interventions for more efficient collaboration. In particular, we were able to identify typical meeting patterns, and to distinguish between creative and high-executing knowledge work based on the interaction pattern. management practices lead to greater productivity, a large number of important organizational communications are face-toface, so studies based on mining electronic interactions are missing a great part of the picture.

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Sociometric Badges: A New Tool for I.S. Research

SSRN Electronic Journal, 2000

Abstract: Researchers have recently been able to understand organizations at an unprecedented lev... more Abstract: Researchers have recently been able to understand organizations at an unprecedented level of detail using new digital records and electronic communication data. However, while digital communication is important in the modern workplace, face-to-face interaction still represents a large and important share of organizational communication, information exchange, socialization and informal coordination. Unfortunately, few techniques exist to collect face-to-face communication data at the same level of granularity ...

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