Smartphone Interruptions: Are Yours Relentless and Annoying?

Rutgers study reveals that personality traits influence and help predict receptiveness to smartphone notifications

Does your smartphone spew a relentless stream of text messages, push alerts, social media messages and other noisy notifications?

Well, Rutgers experts have developed a novel model that can predict your receptiveness to smartphone interruptions. It incorporates personality traits and could lead to better ways to manage a blizzard of notifications and limit interruptions – if smartphone manufacturers get on board.

“Ideally, a smartphone notification management system should be like an excellent human secretary who knows when you want to be interrupted or left alone,” said Janne Lindqvist, an assistant professor in the Department of Electrical and Computer Engineering in Rutgers’ School of Engineering. “We know that people struggle with time management all the time, so a smartphone, instead of being a nuisance, could actually help with things.”

Currently, smartphone users can limit interruptions by turning off their ringers, but no system figures out when you want to receive notifications. “Preferably, your smartphone would recognize your patterns of use and behavior and schedule notifications to minimize interruptions,” said Lindqvist, who leads a research group focusing on human-computer interaction and security engineering.

Studies have shown that inappropriate or untimely smartphone interruptions annoy users, decrease productivity and affect emotions, he said. So it’s important to choose the right time to interrupt people.

Lindqvist began thinking about how to reduce smartphone distractions several years ago, so he and his doctoral students, Fengpeng Yuan and Xianyi Gao, conducted a peer-reviewed study: “How Busy Are You? Predicting the Interruptibility Intensity of Mobile Users.” The pioneering study will be formally published in May at the ACM CHI Conference on Human Factors in Computing Systems in Denver, Colorado. It’s the premier international conference on human-computer interaction.

For their study, the researchers developed and evaluated a two-stage model to predict the degree to which people are interruptible by smartphones. The first stage is aimed at predicting whether a user is available at all or unavailable. The second stage gauges whether people are not interruptible, highly not interruptible, highly interruptible, interruptible or neutral toward interruptions, according to Lindqvist.

They collected more than 5,000 smartphone records from 22 participants at Rutgers University over four weeks, and they were able to predict how busy people were. That’s important because people can respond to different kinds of interruptions based on their level of busyness.

In a first, the researchers used major personality traits to help predict how interruptible people were. Study participants took a standard test to see how their personalities aligned with the “Big Five” personality traits in psychological theory – extroversion, agreeableness, conscientiousness, neuroticism and openness.

In addition to building a model for interruptibility, the researchers studied the situations when participants’ interruptibility varied. When participants were in a pleasant mood, they were likely to be more interruptible than if they were in an unpleasant mood, the study showed. The study also found that participants’ willingness to be interrupted varied based on their location. A few participants were highly interruptible at locations such as health care and medical facilities, possibly because they were waiting to see doctors. But participants were reluctant to be interrupted when they were studying and, compared with other activities, were less interruptible when exercising.

Lindqvist and his team are working on next steps that could lead to smarter smartphone notifications.

“We could, for example, optimize our model to allow smartphone customization to match different preferences, such as always allowing someone to interrupt you,” he said. “This would be something an excellent human secretary would know. A call from your kids or their daycare should always pass through, no matter the situation, while some people might want to ignore their relatives, for example.”

“Ideally, smartphones would learn automatically,” he said. “As it is today, the notification management system is not smart or only depends on a user’s setting, such as turning on or off certain notifications.  Our model is different because it collects users’ activity data and preferences. This allows the system to learn automatically like a ‘human secretary,’ so it enables smart prediction.”

Story by Rutgers science communicator Todd B. Bates at or 848-932-0550.

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ECE Welcomes New Faculty

The Department of Electrical and Computer Engineering welcomes two new faculty members to the Rutgers engineering. These new instructors bring extensive experience to Rutgers, having performed research in several exciting fields. We look forward to their continued growth and innovation as part of the Rutgers Engineering faculty.
Assistant Professor
Electrical and Computer Engineering
PhD, Electrical and Computer Engineering, 2012
McGill University
Maryam Dehnavi recently worked as a postdoctoral researcher at the Massachusetts Institute of Technology, where she worked on machine learning and stencil computations. Her research included improving previous methods for finite-element method computations and other algorithms. Her goal is to create more efficient methods by which data-heavy or otherwise large-scale computations are performed by parallel systems. Previously she worked at Qualcomm Incorporated, where she developed and optimized code to improve applications. She has also been a visiting scholar at the University of California Berkeley and Irvine, where she likewise studied methods of improving software to work more effectively with hardware. She has been granted multiple scholarships and grants by the Natural Sciences and Engineering Research Council of Canada, and most recently earned a postdoctoral fellowship by the Quebec Research Fund.
Assistant Professor
Electrical and Computer Engineering
PhD, Electrical Engineering, 2010
University of Maryland

Vishal Patel’s key research interests are in machine learning, signal/image processing, computer vision processing, and security and privacy. He is a co-principal investigator on a Defense Advanced Research Projects Agency (DARPA) study analyzing fingerprints as a security feature for mobile devices. After earning his doctorate studying visual and atomic representations of signals, he worked and taught at the University of Maryland’s Center for Automation Research. Other research areas include approximation theory with wavelets, face recognition by computers, and biometrics. He is the principal investigator on a LADAR imaging study hosted by an Army Research Laboratory with General Dynamics. He was the recipient of a 2015 Computer Vision and Pattern Recognition Outstanding Reviewer Award.

ECE Faculty.jpg

Spring 2019 Career & Internship Mega Fair

Join us at one of the largest and most diverse recruiting opportunities in the nation. An anticipated group of nearly 300 employers (different employers each day) will be available to network with candidates to discuss full-time, part-time, and internship opportunities from a wide variety of fields. This event is only open to Rutgers University (New Brunswick, Camden, Newark, and RBHS) students and alumni from all academic disciplines.

Kristin Dana receives Grant from Lockheed Martin

Professor Kristin Dana has won a new grant from Lockheed Martin for the project "Multiscale Deep Learning For Temporal Patterns." This is a one year award for $120,183.

The objective of this project is to conduct graduate level research for modeling time-varying patterns using deep learning in the context of temporally varying signals. The goal of the current project is to explore state of the art machine learning methods of GANs (generative adversarial networks) and RL (reinforcement learning) in the specific context of multiscale implementations.

Congratulations Kristin!

Mehdi Javanmard Wins NSF CAREER Award

ECE Assistant Professor Mehdi Javanmard has won the NSF CAREER award for the project titled "CAREER: Reconfigurable Electro-Fluidic Prescriptions (REFRx): Data-Driven Biosensors for Detection and Treatment of Multidrug-Resistant Cancers." This is a five-year $500,000 award. These prestigious awards are in support of early-career faculty who have the potential to serve as academic role models in research and education and to lead advances in the mission of their department or organization. This most recent CAREER award makes it the 8th active CAREER Award in the ECE department, reflecting the phenomenal success of our young faculty members!  


Mehdi and his group will develop an instrument that can rapidly identify drug resistant cancer cells in tumors and prescribe a course of treatment for the patient that minimizes chance of cancer recurrence. Drug resistance is one of the greatest impediments to treating both cancer and infectious disease and has been identified as one of the greatest public health threats of the next several decades. The proposed miniaturized instrument can be utilized for rapidly screening cancer patients for drug resistance and identifying the key molecular players involved and selecting optimal cancer treatment drugs. In this work, a microfluidics/electronic/data-driven crosscut approach is proposed to enable a rapid technology that can identify drug resistant cells using machine learning and examine the key protein pathways resulting in resistance using a label-free sensing array. The proposed platform is adaptive and reconfigures itself to assay the relevant proteins on-demand and avoids a resource-hungry brute force approach. This interdisciplinary project will engage and train both graduate and undergraduate students in various areas and also K-12 students through outreach workshops, local industry through educational lectures, and the general public through development of an online course, resulting in broad dissemination of knowledge.


Congratulations on this outstanding achievement Mehdi!


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