Nabil Alshurafa

Northwestern University | NU · Department of Preventive Medicine

Smoking is the leading cause of preventable death worldwide. Cigarette smoke includes thousands of chemicals that are harmful and cause tobacco-related diseases. To date, the causality between human exposure to specific compounds and the harmful effects is unknown. A first step in closing the gap in knowledge has been measuring smoking topography,...

Researchers increasingly use passive sensing data and frequent self-report to implement personalized mobile health (mHealth) interventions. Yet, we know that certain populations may find these technical protocols burdensome and intervention uptake as well as treatment efficacy may be affected as a result. In the present study, we predicted feasibil...

Screen time is associated with several health risk behaviors including mindless eating, sedentary behavior, and decreased academic performance. Screen time behavior is traditionally assessed with self-report measures, which are known to be burdensome, inaccurate, and imprecise. Recent methods to automatically detect screen time are geared more towa...

Automated detection and validation of fine-grained human activities from egocentric vision has gained increased attention in recent years due to the rich information afforded by RGB images. However, it is not easy to discern how much rich information is necessary to detect the activity of interest reliably. Localization of hands and objects in the...

Wearable cameras provide an informative view of wearer activities, context, and interactions. Video obtained from wearable cameras is useful for life-logging, human activity recognition, visual confirmation, and other tasks widely utilized in mobile computing today. Extracting foreground information related to the wearer and separating irrelevant b...

Mobile and wearable devices have enabled numerous applications, including activity tracking, wellness monitoring, and human–computer interaction, that measure and improve our daily lives. Many of these applications are made possible by leveraging the rich collection of low-power sensors found in many mobile and wearable devices to perform human act...

The COVID-19 pandemic has dramatically increased the use of face masks across the world. Aside from physical distancing, they are among the most effective protection for healthcare workers and the general population. Face masks are passive devices, however, and cannot alert the user in case of improper fit or mask degradation. Additionally, face ma...

Persistent coughs are a major symptom of respiratory-related diseases. Increasing research attention has been paid to detecting coughs using wearables, especially during the COVID-19 pandemic. Among all types of sensors utilized, microphone is most widely used to detect coughs. However, the intense power consumption needed to process audio signals...

Mobile and wearable devices have enabled numerous applications, including activity tracking, wellness monitoring, and human-computer interaction, that measure and improve our daily lives. Many of these applications are made possible by leveraging the rich collection of low-power sensors found in many mobile and wearable devices to perform human act...

Background Commercial nutrition apps are increasingly used to evaluate diet. Evaluating the comparative validity of nutrient data from commercial nutrition app databases is important to determine the merits of using these apps for dietary assessment. Objective Nutrient data from four commercial nutrition apps were compared with a research-based fo...

Background: Cognitive behavioral therapy-based interventions are effective in reducing prenatal stress, which can have severe adverse health effects on mothers and newborns if unaddressed. Predicting next-day physiological or perceived stress can help to inform and enable pre-emptive interventions for a likely physiologically and perceptibly stres...

Personalized weight management strategies are gaining interest. However, knowledge is limited regarding eating habits and association with energy intake, and current technologies limit assessment in free-living situations. We assessed associations between eating behavior and time of day with energy intake using a wearable camera under free-living c...

Introduction: Short message service (SMS) is a widely accepted telecommunications approach used to support health informatics, including behavioral interventions, data collection, and patient-provider communication. However, SMS delivery platforms are not standardized and platforms are typically commercial "off-the-shelf" or developed "in-house."...

Objective: We applied the ORBIT model to digitally define dynamic treatment pathways whereby intervention improves multiple risk behaviors. We hypothesized that effective intervention improves the frequency and consistency of targeted health behaviors and that both correlate with automaticity (habit) and self-efficacy (self-regulation). Method:...

Background: eHealth technologies have been found to facilitate health-promoting practices among cancer survivors with BMI in overweight or obese categories; however, little is known about their engagement with eHealth to promote weight management and facilitate patient-clinician communication. Objective: The objective of this study was to determin...

Prenatal stress exposure increases vulnerability to virtually all forms of psychopathology. Based on this robust evidence base, we propose a “Mental Health, Earlier” paradigm shift for prenatal stress research, which moves from the documentation of stress‐related outcomes to their prevention, with a focus on infant neurodevelopmental indicators of...

BACKGROUND Electronic health (eHealth) technologies have been found to facilitate health-promoting practices among cancer survivors with overweight or obesity. However, little is known about the characteristics of cancer survivors who demonstrate engagement with eHealth to promote weight management and facilitate patient-clinician communication. O...

The development and validation of computational models to detect daily human behaviors (e.g., eating, smoking, brushing) using wearable devices requires labeled data collected from the natural field environment, with tight time synchronization of the micro-behaviors (e.g., start/end times of hand-to-mouth gestures during a smoking puff or an eating...

We present the design, implementation, and evaluation of a multi-sensor, low-power necklace, NeckSense, for automatically and unobtrusively capturing fine-grained information about an individual's eating activity and eating episodes, across an entire waking day in a naturalistic setting. NeckSense fuses and classifies the proximity of the necklace...

Dietary intake, eating behaviors, and context are important in chronic disease development, yet our ability to accurately assess these in research settings can be limited by biased traditional self-reporting tools. Objective measurement tools, specifically, wearable sensors, present the opportunity to minimize the major limitations of self-reported...

Background Melanoma survivors often do not engage in adequate sun protection, leading to sunburn and increasing their risk of future melanomas. Melanoma survivors do not accurately recall the extent of sun exposure they have received, thus, they may be unaware of their personal UV exposure, and this lack of awareness may contribute towards failure...

We present the design, implementation, and evaluation of a multi-sensor low-power necklace 'NeckSense' for automatically and unobtrusively capturing fine-grained information about an individual's eating activity and eating episodes, across an entire waking-day in a naturalistic setting. The NeckSense fuses and classifies the proximity of the neckla...

Objectives Precision behavioral medicine techniques integrating wearable ultraviolet radiation (UVR) sensors may help individuals avoid sun exposure that places them at-risk for skin cancer. As a preliminary step in our patient-centered process of developing a just-in-time adaptive intervention, this study evaluated reactions and preferences to UVR...

Activity-oriented cameras are increasingly being used to provide visual confirmation of specific hand-related activities in real-world settings. However, recent studies have shown that bystander privacy concerns limit participant willingness to wear a camera. Researchers have investigated different image obfuscation methods as an approach to enhanc...

High levels of stress during pregnancy increase the chances of having a premature or low-birthweight baby. Perceived self-reported stress does not often capture or align with the physiological and behavioral response. But what if there was a self-report measure that could better capture the physiological response? Current perceived stress self-repo...

Background Conventional diet assessment approaches such as the 24-hour self-reported recall are burdensome, suffer from recall bias, and are inaccurate in estimating energy intake. Wearable sensor technology, coupled with advanced algorithms, is increasingly showing promise in its ability to capture behaviors that provide useful information for est...

BACKGROUND Conventional diet assessment approaches such as the 24-hour self-reported recall are burdensome, suffer from recall bias, and are inaccurate in estimating energy intake. Wearable sensor technology, coupled with advanced algorithms, is increasingly showing promise in its ability to capture behaviors that provide useful information for est...

Background: Young black women have an increased risk of cardiovascular disease, and thus identifying innovative prevention strategies is essential. A potential preventive strategy is mobile health; however, few studies have tested this strategy in young black women. Aim: The purpose of this study was to assess the feasibility of a mobile health...

Background Understanding the characteristics of smokers who are successful in quitting may help to increase smoking cessation rates. Purpose To examine heterogeneity in cessation outcome at 6 months following smoking cessation behavioral counseling with or without weight management counseling. Methods 2,540 smokers were recruited from a large qui...

Behavioral medicine is devoting increasing attention to the topic of participant engagement and its role in effective mobile health (mHealth) behavioral interventions. Several definitions of the term "engagement" have been proposed and discussed, especially in the context of digital health behavioral interventions. We consider that engagement refer...

In this paper, we present the design and implementation of the HABits necklace, a neck-worn device that estimates behavior. This neck-worn device is continuously evolving to provide researchers with the ability to use it in multiple applications including eating, gesture, and activity recognition. Our proposed HABits necklace generates four signal...

Self-reported perceived stress does not often correlate with physiologic and behavioral stress response. Current perceived stress self-report assessment methods require users to answer many questions at different time points of the day. Reducing it to one question at multiple time points throughout the day, using microinteraction-based Ecological M...

Wearable sensors can provide reliable, automated measures of health behaviors in free-living populations. However, validation of these measures is impossible without observable confirmation of behaviors. Participants have expressed discomfort during the use of ego-centric wearable cameras with first-person view. We argue that mounting the camera on...

Melanoma survivors are at risk to develop another melanoma and the same patterns of sun exposure that caused the initial melanoma contribute to the risk for a second melanoma.¹ Despite awareness of the risk of developing another melanoma and the benefit of sun protection in modifying that risk,² melanoma survivors often engage in unprotected episod...

Minutes of Unprotected Sun Exposure (MUSE) Inventory screenshots and notes.

One in five US adults will be diagnosed with skin cancer. As most skin cancers are attributable to sun exposure, this risk factor is an important target for research and intervention. Most sun exposure measures assess frequency of specific sun-protection behaviors, which does not account for the use of multiple, potentially overlapping sun-protecti...

In this paper, a Predictive Analytics Model is designed, developed, and validated to determine the risk of manifesting osteoporosis in later life using big data processing. The proposed model leverages the novel genetic pleiotropic information in the 1,000 Genome Project of over 2,500 individuals worldwide. Also, the mutations associated with osteo...

In this paper, Big Data Processing was utilized to develop and validate a Predictive Analytics Model with the goal of determining the risk for an individual manifesting osteoporosis in later life. The analyzed dataset consists of the genomic information from over 2,500 individuals from all around the world. This model development leverages the nove...

In this paper, we utilize Big Data Processing and develop Predictive Analytics Models to examine and analyze mutations associated with osteoporosis and cardiovascular disease. The dataset consists of the genomic information of over 2,500 individuals. The genomic data was collected from all around the world. The data visualization allowed us to see...

Preventive medicine is heading towards a more personalized future; adjusting care based on the individual needs of the patient. This future is enabled by wearable devices: not just smartwatches, but devices embedded in clothing, necklaces, and other gadgets that will one day invisibly, continuously, and effortlessly monitor and understand the healt...

Problematic eating behaviors are a major cause of obesity. To improve our understanding of these eating behaviors, we need to be able to first reliably detect them. In this paper we use a wrist-worn sensor to test a generalized machine learning models' reliability in detecting eating episodes through data processing. We process data from a 6-axis i...

Energy balance is one component of weight management, but passive objective measures of caloric intake are non-existent. Given recent success of actigraphy as a passive objective measure of the physical activity construct that relieves participants of the burden of biased self-report, researchers are aiming to find a passive objective measure of ca...

As computer programming becomes more important to various fields and disciplines and as it is more commonly taught in education settings, the number of end-users with basic programming experience is increasing. The importance of being able to easily and quickly develop programs has prompted research in "opportunistic' programming methods. This rese...

Wearable devices monitoring food intake through passive sensing is slowly emerging to complement self-reporting of users’ caloric intake and eating behaviors. Though the ultimate goal for the passive sensing of eating is to become a reliable gold standard in dietary assessment, it is currently showing promise as a means of validating self-report me...

This article surveys techniques for evaluating eating habits for wellness applications, emphasizing sensor-based approaches such as audio signal processing, inertial sensing, image processing, and gesture recognition. The focus is on noninvasive technologies that could be developed into real-time wearable devices, rather than techniques whose use i...

Given substantial evidence that healthy lifestyle behaviors lessen the odds of cardiovascular disease, a guideline from the American Heart Association and American College of Cardiology¹ advises physicians to foster patients’ physical activity. But how is the clinician to evaluate a patient’s healthy lifestyle behaviors, let alone enhance them? Tra...

Wearable health-monitoring systems must achieve a balance between the often opposing goals of hardware overhead and classification accuracy. Prior works have presented various approaches to dynamically scale the accuracy of these systems as a function of available resources. In this paper, we present a framework which retroactively improves the acc...

Objective: The objective of our work is to describe and evaluate an algorithm to reduce power usage and increase battery lifetime for wearable health-monitoring devices. Methods: We describe a novel dynamic computation offloading scheme for real-time wearable health monitoring devices that adjusts the partitioning of data processing between the...

To allow health tracking, patient monitoring, and provide timely user interventions, sensor signals from body sensor networks need to be processed in real-time. Time subdivisions of the sensor signals are extracted and fed into a supervised learning algorithm, such as Support Vector Machines (SVM), to learn a model capable of distinguishing differe...

Background: Prior research has shown a correlation between poor dietary habits and countless negative health outcomes such as heart disease, diabetes, and certain cancers. Automatic monitoring of food intake in an unobtrusive, wearable form-factor can encourage healthy dietary choices by enabling individuals to regulate their eating habits. Methods...

Objective: Studies have revealed that non-adherence to prescribed medication can lead to hospital readmissions, clinical complications, and other negative patient outcomes. Though many techniques have been proposed to improve patient adherence rates, they suffer from low accuracy. Our objective is to develop and test a novel system for assessment...

Remote health monitoring (RHM) systems are becoming more widely adopted by clinicians and hospitals to remotely monitor and communicate with patients while optimizing clinician time, decreasing hospital costs, and improving quality of care. In the Women's Heart Health Study (WHHS) we developed Wanda-CVD, where participants received healthy lifestyl...

Among all of the major organizations, including the World Health Organization, the Centers for Disease Control and the Pew report the focus on disease prevention is critical. Given the rapid advances in technology it has become clear that there is a critical role for remote health monitoring systems (RHMS) in the prevention of chronic disease. The...

In this paper, we propose a novel methodology for utilizing disease diagnostic information to predict severity of condition for Congestive Heart Failure (CHF) patients. Our methodology relies on a novel, clustering-based, feature extraction framework using disease diagnostic information. To reduce the dimensionality we identify disease clusters usi...

Food intake levels, hydration, ingestion rate, and dietary choices are all factors known to impact the risk of obesity. This paper presents a novel wearable system in the form of a necklace, which aggregates data from an embedded piezoelectric sensor capable of detecting skin motion in the lower trachea during ingestion. The skin motion produces an...

Sleep constitutes a big portion of our lives and is a major part of health and well-being. The vital repair and regeneration tasks carried out during sleep are essential for our physical, mental and emotional health. Obstructive sleep apnea (OSA) is a sleep disorder that is characterized by repeated pauses in breathing during sleep. These pauses, o...

Sedentary behavior is a root cause of several chronic conditions affecting health of adults and children in the United States and worldwide. The chronic conditions that result from this cause not only health concerns for these individuals but significant economic burden. Exergaming, or the merger of exercise and health information with video games,...