Jakob Eg Larsen

Measuring Large-Scale Social Networks with High Resolution

This paper describes the deployment of a large-scale study designed to measure human interactions across a variety of communication channels, with high temporal resolution and spanning multiple years—the Copenhagen Networks Study. Specifically, we collect data on face-to-face interactions, telecommunication, social networks, location, and background information (personality, demographics, health, politics) for a densely connected population of 1 000 individuals, using state-of-the-art smartphones as social sensors. Here we provide an overview of the related work and describe the motivation and research agenda driving the study. Additionally, the paper details the data-types measured, and the technical infrastructure in terms of both backend and phone software, as well as an outline of the deployment procedures. We document the participant privacy procedures and their underlying principles. The paper is concluded with early results from data analysis, illustrating the importance of multi-channel high-resolution approach to data collection.

The Smartphone Brain Scanner: A Portable Real-Time Neuroimaging System

Combining low-cost wireless EEG sensors with smartphones offers novel opportunities for mobile brain imaging in an everyday context. Here we present the technical details and validation of a framework for building multi-platform, portable EEG applications with real-time 3D source reconstruction. The system – Smartphone Brain Scanner – combines an off-the-shelf neuroheadset or EEG cap with a smartphone or tablet, and as such represents the first fully portable system for real-time 3D EEG imaging. We discuss the benefits and challenges, including technical limitations as well as details of real-time reconstruction of 3D images of brain activity. We present examples of brain activity captured in a simple experiment involving imagined finger tapping, which shows that the acquired signal in a relevant brain region is similar to that obtained with standard EEG lab equipment. Although the quality of the signal in a mobile solution using an off-the-shelf consumer neuroheadset is lower than the signal obtained using high-density standard EEG equipment, we propose mobile application development may offset the disadvantages and provide completely new opportunities for neuroimaging in natural settings.

Personal informatics in practice: improving quality of life through data

Personal informatics refers to a class of software and hardware systems that help individuals collect personal information to improve self-understanding. Improving self-understanding can foster self-insight and promote positive behaviors: healthy living, energy conservation, etc. The development of personal informatics applications poses new challenges for human-computer interaction and creates opportunities for applications in various domains related to quality of life, such as fitness, nutrition, wellness, mental health, and sustainability. This workshop will continue the conversations from the CHI 2010 and CHI 2011 workshops on personal informatics [6][7]. The focal themes for this workshop are: (1) practical lessons from previous research and development experiences that can guide interface design for systems that allow users to collect and reflect on personal data; (2) requirements for building robust personal informatics applications; and (3) design and development of infrastructures that make personal informatics applications easier to create and evaluate.

Smartphones get emotional: mind reading images and reconstructing the neural sources

Combining a wireless EEG headset with a smartphone offers new opportunities to capture brain imaging data reflecting our everyday social behavior in a mobile context. However processing the data on a portable device will require novel approaches to analyze and interpret significant patterns in order to make them available for runtime interaction. Applying a Bayesian approach to reconstruct the neural sources we demonstrate the ability to distinguish among emotional responses reflected in different scalp potentials when viewing pleasant and unpleasant pictures compared to neutral content. Rendering the activations in a 3D brain model on a smartphone may not only facilitate differentiation of emotional responses but also provide an intuitive interface for touch based interaction, allowing for both modeling the mental state of users as well as providing a basis for novel bio-feedback applications.

Estimating human predictability from mobile sensor data

Quantification of human behavior is of prime interest in many applications ranging from behavioral science to practical applications like GSM resource planning and context-aware services. As proxies for humans, we apply multiple mobile phone sensors all conveying information about human behavior. Using a recent, information theoretic approach it is demonstrated that the trajectories of individual sensors are highly predictable given complete knowledge of the infinite past. We suggest using a new approach to time scale selection which demonstrates that participants have even higher predictability of non-trivial behavior on smaller timer scale than previously considered.

Smartphones as pocketable labs: Visions for mobile brain imaging and neurofeedback

Mobile brain imaging solutions, such as the Smartphone Brain Scanner, which combines low cost wireless EEG sensors with open source software for real-time neuroimaging, may transform neuroscience experimental paradigms. Normally subject to the physical constraints in labs, neuroscience experimental paradigms can be transformed into dynamic environments allowing for the capturing of brain signals in everyday contexts. Using smartphones or tablets to access text or images may enable experimental design capable of tracing emotional responses when shopping or consuming media, incorporating sensorimotor responses reflecting our actions into brain machine interfaces, and facilitating neurofeedback training over extended periods. Even though the quality of consumer neuroheadsets is still lower than laboratory equipment and susceptible to environmental noise, we show that mobile neuroimaging solutions, like the Smartphone Brain Scanner, complemented by 3D reconstruction or source separation techniques may support a range of neuroimaging applications and thus become a valuable addition to high-end neuroimaging solutions.

Participatory bluetooth sensing: A method for acquiring spatio-temporal data about participant mobility and interactions at large scale events

Acquisition of data to capture human mobility and interactions during large-scale events is a challenging task. In this paper we discuss a mobile sensing method for mapping the mobility of crowds at large scale events using a participatory Bluetooth sensing approach. This non-invasive technique for collecting spatio-temporal data about participant mobility and social interactions uses the capabilities of Bluetooth capable smartphones carried by participants. As a proof-of-concept we present a field study with deployment of the method in a large music festival with 130000 participants where a small subset of participants installed Bluetooth sensing apps on their personal smartphones. Our software module uses location and Bluetooth scans to utilize smartphones as provisional scanners that are present with higher frequency in regions with high density of participants. We discuss the initial results obtained and outline opportunities and challenges introduced by this methodology along with opportunities for future pervasive systems and applications.

N-glycans are not the signal for apical sorting of corticosteroid binding globulin in MDCK cells

It has been suggested that N‐glycans act as a general sorting signal for secretory proteins in MDCK cells [Scheiffele et al. (1995) Nature 378, 96–98]. Human corticosteroid binding globulin contains six consensus sites for N‐glycosylation and is known to be secreted to the apical side of MDCK cells. Our results show that wild‐type corticosteroid binding globulin is N‐glycosylated when it is recombinantly expressed in MDCK cells. Six mutants, each lacking one of the N‐glycosylation sites, and a mutant lacking all six N‐glycosylation sites were also secreted to the apical side of MDCK cells in a polarized manner. Thus, the N‐glycans on corticosteroid binding globulin do not act as an apical sorting signal in MDCK cells.

A smartphone interface for a wireless EEG headset with real-time 3D reconstruction

We demonstrate a fully functional handheld brain scanner consisting of a low-cost 14-channel EEG headset with a wireless connection to a smartphone, enabling minimally invasive EEG monitoring in naturalistic settings. The smartphone provides a touch-based interface with real-time brain state decoding and 3D reconstruction.

Personal informatics in the wild: hacking habits for health & happiness

Personal informatics is a class of systems that help people collect personal information to improve self-knowledge. Improving self-knowledge can foster self-insight and promote positive behaviors, such as healthy living and energy conservation. The development of personal informatics applications poses new challenges in human-computer interaction and creates opportunities for applications in various domains related to quality of life, such as fitness, nutrition, wellness, mental health, and sustainability. This workshop will continue the conversations from the 3 previous CHI workshops through discussions on practical lessons from previous research and development experiences. In particular, this workshop will extend this ongoing work through a focus on rapid prototyping and deployment in the wild. Topics covered will include designing interfaces for collecting and reflecting on personal data, building robust applications, and infrastructures to make applications easier to create.