Understanding and intervening on eating behavior often necessitates measurement of energy intake (EI); however, commonly utilized and widely accepted methods vary in accuracy and place significant burden on users (e.g., food diaries), or are costly to implement (e.g., doubly labeled water). Thus, researchers have sought to leverage inexpensive and low-burden technologies such as wearable sensors for EI estimation. Paradoxically, one such methodology that estimates EI via smartwatch-based bite counting has demonstrated high accuracy in laboratory and free-living studies, despite only measuring the amount, not the composition, of food consumed. This secondary analysis sought to further explore this phenomenon by evaluating the degree to which EI can be explained by a sensor-based estimate of the amount consumed versus the energy density (ED) of the food consumed. Data were collected from 82 adults in free-living conditions (51.2% female, 31.7% racial and/or ethnic minority; Mage = 33.5, SD = 14.7) who wore a bite counter device on their wrist and used smartphone app to implement the Remote Food Photography Method (RFPM) to assess EI and ED for two weeks. Bite-based estimates of EI were generated via a previously validated algorithm. At a per-meal level, linear mixed effect models indicated that bite-based EI estimates accounted for 23.4% of the variance in RFPM-measured EI, while ED and presence of a beverage accounted for only 0.2% and 0.1% of the variance, respectively. For full days of intake, bite-based EI estimates and ED accounted for 41.5% and 0.2% of the variance, respectively. These results help to explain the viability of sensor-based EI estimation even in the absence of information about dietary composition.

Simulator sickness has been a pervasive problem as head-mounted displays (HMDs) grow in popularity. Recent work showed that people can adapt to constant latency in an HMD, but latency that varies has not been examined. In this study, participants performed a shooting task while wearing an HMD during three sessions separated by 48 h under conditions of constant or varying latency. Performance was assessed for both accuracy (targets hit) and speed (time-to-hit targets). It was hypothesized that participants would adapt to constant, but not varying latency as indicated by decreasing simulator sickness over time. Further, it was hypothesized that participants would improve performance over time for both conditions due to practice, but the constant latency group would improve at a faster rate. Results showed reduced sickness with session regardless of latency condition. A similar trend was shown where performance improved with each session, with no effect of the latency condition. Change in sickness and performance were not correlated, suggesting that the changes were independently driven. These findings showed that people reduced sickness and improved performance with repeated exposure, even when experiencing different perturbations. This finding has implications for both HMDs and general understanding of the relationship between latency and adaptation.

This article considers detecting eating in free-living humans by tracking wrist motion. We are specifically interested in the effect of secondary activities that people conduct while simultaneously eating, such as walking, watching television, or working. These secondary activities cause wrist motions that obfuscate those associated with eating, increasing the difficulty of detecting periods of eating. We collected a large dataset of 4,680 hours of wrist motion from 351 participants during free living. Participants reported secondary activities in 72% of meals. Analysis of wrist motion data revealed that the wrist was resting 12.8% of the time during self-reported meals compared to only 6.8% of the time in a cafeteria dataset, whereas walking motion was found 5.5% of the time during meals in free living compared to 0% in a cafeteria. Augmenting an eating detection classifier to include walking and resting detection improved accuracy from 74% to 77% on our free-living dataset ( t [353] = 7.86, p < 0.001). Although eating detection could be improved using more sophisticated machine learning methods or sensor modalities, all approaches would be affected by secondary activities, as they affect the labeling of data itself. Our work suggests that future work should collect detailed ground truth on secondary activities being conducted during eating, as these activities could hold insights into when an eating activity starts or stops in the absence of video-based ground truth.

Background Women with chronic pelvic pain (CPP) have poor cardiovagal modulation. It is unclear whether this finding reflects a broader abnormality across many systems such as gastro-vagal modulation. Aim To determine if maladaptive cardiovagal activity in females with CPP is accompanied by maladaptive gastric myoelectric activity. Methods A total of 36 health controls (HC) and 75 CPP underwent supine (10 min), then upright (tilted 70 degrees head up; 30 min), and back to supine (10 min) positions. High-frequency heart rate variability (HF-HRV; 0.15-0.4 Hz) was measured as an index of cardiovagal activity. Cutaneous electrogastrography (EGG) assessed gastric myoelectric activity pre- and during-upright tilt. EGG measures from 16 HC and 31 CPP patients were available for analysis and included relative percentage of gastric activity within the normal (2-4 cpm) and tachygastria (4-10 cpm) ranges, plus ratio of normal/tachygastria. Results HF-HRV was lower in CPP individuals at all time points (eachp < .05). CPP individuals showed lesser decrease in HF-HRV from supine to upright, and poorer HF-HRV recovery from upright back to supine (F[1, 106] = 4.62,p = .034). HC showed increase in tachygastria activity (t[15] = -2.09,p = .054) while the CPP group showed no change in tachygastria activity from pre-upright to upright (t[30] = -0.62,p = .537). Conclusions Individuals with CPP going from supine to upright demonstrate an impairment in both tachygastria and the parallel decrement in HRV. These results support the hypothesis of a generalized blunting in the physiological modulation in CPP individuals affecting both cardiovascular and gastric systems.

Self-efficacy (SE) and information processing (IP) may be important constructs to target when designing mHealth interventions for weight loss. The goal of this study was to examine the relationship between SE and IP with weight loss at six-months as part of the Dietary Interventions Examining Tracking with mobile study, a six-month randomized trial with content delivered remotely via twice-weekly podcasts. Participants were randomized to self-monitor their diet with either a mobile app (n = 42) or wearable Bite Counter device (n = 39). SE was assessed using the Weight Efficacy Life-Style Questionnaire and the IP variables assessed included user control, cognitive load, novelty, elaboration. Regression analysis examined the relationship between weight loss, SE change & IP at six months. Results indicate that elaboration was the strongest predictor of weight loss (ß =−0.423, P = 0.011) among all SE & IP variables and that for every point increase in elaboration, participants lost 0.34 kg body weight.

Lack of standardization and unblinding threaten the research of mechanisms involved in expectancy effects on pain. We evaluated a computer-controlled virtual experimenter (VEx) to avoid these issues. Fifty-four subjects underwent a baseline-retest heat pain protocol. Between sessions, they received an expectancy manipulation (placebo or no-treatment) delivered by VEx or text-only control condition. The VEx provided standardized "social" interaction with the subjects. Pain ratings and psychological state/trait measures were recorded. We found an interaction of expectancy and delivery on pain improvement following the intervention. In the text conditions, placebo was followed by lower pain, whereas in the VEx conditions, placebo and no-treatment were followed by a comparable pain decrease. Secondary analyses indicated that this interaction was mirrored by decreases of negative mood and anxiety. Furthermore, changes in continuous pain were moderated by expectation of pain relief. However, retrospective pain ratings show an effect of expectancy but not of delivery. We conclude that we successfully applied an automated protocol for inducing expectancy effects on pain. The effect of the VEx regardless of treatment may be due to interactions of attention allocation and locus of control. This points to the diversity of expectancy mechanisms, and has implications for research and computer-based treatment applications.

Robert M. Stern 1937–2020 Robert “Bob” M. Stern June 18, 1937-June 13, 2020 Robert M. Stern, 83, of State College died on Saturday, June 13, 2020. He is survived by his wife of 59 years, Wilma Olch Stern, and his daughters Jessica Leigh Benjamin and her husband, Eric Benjamin, of West Newton, Massachusetts; Alison Rachel Stern and her husband, Amoshaun Toft, of Seattle, Washington; and his sister, Janice Victor of Montclair, New Jersey. He was born in New York City on June 18, 1937, the son of Ervin Stern and Nellie Wachstetter Stern. He attended The Bronx High School of Science and earned his B.A. in Philosophy at Franklin & Marshall College, an M.A. at Tufts University, and Ph.D. at Indiana University, Bloomington, both in Psychology. After completing his doctorate with R.C. Davis he spent 2 years as a Research Associate at Indiana University and then, continued his career in Psychophysiology at the Department of Psychology at Penn State until 2005. In 1992 he was named a Distinguished Professor of Psychology. He was a highly productive researcher, a Ph.D. mentor to over 35 graduate students, a recognized undergraduate teacher, and an academic administrator. His research focused on the autonomic nervous system, especially on the validation and development of electrogastrography (EGG), a noninvasive electrophysiological technique used to record gastric electrical activity. The EGG has become an internationally used technique for the study of the mechanisms and management of gastrointestinal functioning including nausea and gastroparesis. His research and publications were conducted with numerous students and two close colleagues with whom he worked for many years, Dr. Kenneth Koch, now at Wake Forest University School of Medicine, and Professor William J. Ray of Penn State. Biofeedback, by Stern and Ray, received the National Media Award by the American Psychological Foundation (Stern & Ray, 1977). They were also the primary authors of Psychophysiological Recording, for many years the basic text for this field. The first edition was written with Chris Davis and the 2nd edition with Karen Quigley (Stern, Ray, & Davis, 1980; Stern, Ray, & Quigley, 2000). With Dr. Koch he wrote the Handbook of Electrogastrography (Stern & Koch, 2004) and, after his retirement, Nausea, Mechanisms and Management with Ken Koch and Paul Andrews (Stern, Koch, & Andrews, 2011). For several years he held grants from NASA for the study of motion sickness in space. Bob was a universally beloved mentor and teacher. In graduate mentoring, his unassuming, inclusive, and nurturing style created space for students from wide and diverse backgrounds to find their own voices and chart their own paths. He emphasized and instilled simplicity, creativity, compassion, and resourcefulness. He was fond of often repeating to those in his orbit a quote attributed to Albert Einstein: “Everything should be made as simple as possible, but not simpler.” A common rite of passage for students in their first semester of graduate school with Bob was to restore and operate an ancient and failing Grass polygraph (without aid from him or other students). Covered in ink and bleary-eyed by the end, this was a defining event for many, and it provided a first sense of empowerment and self-efficacy in graduate training that Bob continued to stoke. Bob was especially passionate about teaching Psychophysiology, Teaching of Psychology, and Introduction to Psychology. He always wore a tie to the 1st day of his classes because he said it was a “special occasion.” One of his favorite parts of teaching Psychophysiology (a small course) was taking his students out after a semester's worth of hard work and experimenting to treat them to ice cream at the Penn State Creamery. Those who were fortunate enough to be a teaching assistant or take one of his courses still practice and emulate what they saw in Bob as a teacher: patience, clarity, empathy, respect, open-mindedness, and a boundless sense of wonder at the ability of young minds to challenge you and stimulate new ideas. In June of 2005, dozens of Bob's former students and colleagues were thrilled to convene in State College to surprise Bob with a special event to commemorate his 40 years of mentorship. Through a series of informal talks and humorous anecdotes, participants were able to convey their love and affection for Bob, his generous spirit, and the profound impact he had on their lives. Many of Bob's former students met for the first time at the event; what became most evident in their conversations was the consistency of Bob's ability to nurture the passion and creativity of all those who had the fortune of interacting with him. His research was recognized by being granted the Award for Distinguished Scientific Contribution to Psychophysiology by the Society for Psychophysiological Research (SPR) in 2004. In the SPR presentation (Birbaumer, 2007), Niels Birbaumer described Bob Stern as follows: “a pioneer whose contributions paved the way for the development of Behavioral Medicine and Social Cognitive Psychophysiology. Robert Stern's textbooks educated and inspired countless students worldwide for psychophysiology and shaped a positive and critical attitude of the public toward our discipline. Robert Stern has been an active member of our society for more than 40 years, serving on the board and several committees, and is a brilliant scientist and an adviser on ethical and social–political issues.” In 2005, Bob was awarded a Lifetime Achievement Award by the International EGG Society. Many of his some 250 publications were devoted to the topic of gastric motility and its responsiveness to psychological factors. His work with Ken Koch was a very productive collaboration. Changes in gastric myoelectrical activity recorded noninvasively with the EGG methods in response to novel stimuli that evoked nausea was an aspect of psychophysiology that brought out the gastroenterologist in Bob and the psychologist in Ken Koch, a gastroenterologist at Penn State's College of Medicine for many years. Together they studied stimuli that ranged from illusory self-motion and nausea to nausea of pregnancy to nausea in patients with bulimia to patients with diabetic gastroparesis and nausea. Together they helped simplify the recording and analysis of the electrogastrogram signal and brought EGG into clinic research in gastroenterology as well as psychophysiology. Bob was always an open-minded, but critical thinker whose research courage and perseverance were inspirational for those from many different disciplines who came to know him. From 1978–1987 he served as the Head of the Department of Psychology at Penn State University. During that time, he organized the Department's Committee for Minority Graduate Students. His efforts led to grants from NIH, NASA, and NSF to train minority high school, undergraduate, and graduate students. The Department has been nationally recognized for these programs. Widely travelled, he received Fulbright and DAAD awards and was a visiting professor at the University of London, Simon Fraser University, University of Vienna, the Universities of Mainz and Tübingen, the Athens Naval Hospital, and Wake Forest University. For many years Bob served on the Board of Strawberry Fields, a nonprofit provider of community-based services for individuals with developmental delays, intellectual disabilities, and mental illness. In his honor the Board, many relatives, and friends established the Robert M. Stern Fund, for grants and loans to benefit staff. Having grown up within a block of Yankee Stadium, Bob was an avid fan who often watched Yankees games with friends from “tar beach,” the roof of his apartment building. His last book, Joe DiMaggio, Joe DiMaggio was privately printed in 2017 for his family and close associates. This book describes his adventures growing up in The Bronx and his college years at Franklin & Marshall. Bob Stern will be missed by the psychophysiology community for his pioneering work related to gastric motility and its measurement with the EGG. His influence on the field will continue to live on through the students he mentored as well as their students.

Background Mobile dietary self-monitoring methods allow for objective assessment of adherence to self-monitoring; however, the best way to define self-monitoring adherence is not known. Objective The objective was to identify the best criteria for defining adherence to dietary self-monitoring with mobile devices when predicting weight loss. Design This was a secondary data analysis from two 6-month randomized trials: Dietary Intervention to Enhance Tracking with Mobile Devices (n=42 calorie tracking app or n=39 wearable Bite Counter device) and Self-Monitoring Assessment in Real Time (n=20 kcal tracking app or n=23 photo meal app). Participants/setting Adults (n=124; mean body mass index=34.7 +/- 5.6) participated in one of two remotely delivered weight-loss interventions at a southeastern university between 2015 and 2017. Intervention All participants received the same behavioral weight loss information via twice-weekly podcasts. Participants were randomly assigned to a specific diet tracking method. Main outcome measures Seven methods of tracking adherence to self-monitoring (eg, number of days tracked, and number of eating occasions tracked) were examined, as was weight loss at 6 months. Statistical analyses performed Linear regression models estimated the strength of association (R-2) between each method of tracking adherence and weight loss, adjusting for age and sex. Results Among all study completers combined (N=91), adherence defined as the overall number of days participants tracked at least two eating occasions explained the most variance in weight loss at 6 months (R-2=0.27; P<0.001). Self-monitoring declined over time; all examined adherence methods had fewer than half the sample still tracking after Week 10. Conclusions Using the total number of days at least two eating occasions are tracked using a mobile self-monitoring method may be the best way to assess self-monitoring adherence during weight loss interventions. This study shows that self-monitoring rates decline quickly and elucidates potential times for early interventions to stop the reductions in self-monitoring.

The purpose of this study was to determine how latency in a head-mounted display (HMD) affects human performance. Virtual environments (VEs) are used frequently for training. However, VEs can cause simulator sickness. Prior work in our laboratory has examined the role of varying latency in simulator sickness. However, the effect of varying latency on task performance has not been examined. Subjects participated in a repeated measures study where they were exposed to two different latency conditions in an HMD: constant (70 ms) and varying (70-270 ms). During each HMD exposure, subjects used a laser pointer to repeatedly "shoot" at laser targets while accuracy and time-to-hit were recorded. Subjects scored fewer hits and took longer to hit targets in the varying latency condition. These findings Indicate that individuals exposed to varying latency perform worse than individuals exposed to a lower constant latency.

BACKGROUND:This study builds on previous research that seeks to estimate kilocalorie intake through microstructural analysis of eating behaviors. As opposed to previous methods, which used a static, individual-based measure of kilocalories per bite, the new method incorporates time- and food-varying predictors. A measure of kilocalories per bite (KPB) was estimated using between- and within-subjects variables.OBJECTIVE:The purpose of this study was to examine the relationship between within-subjects and between-subjects predictors and KPB, and to develop a model of KPB that improves over previous models of KPB. Within-subjects predictors included time since last bite, food item enjoyment, premeal satiety, and time in meal. Between-subjects predictors included body mass index, mouth volume, and sex.PARTICIPANTS/SETTING:Seventy-two participants (39 female) consumed two random meals out of five possible meal options with known weights and energy densities. There were 4,051 usable bites measured.MAIN OUTCOME MEASURES:The outcome measure of the first analysis was KPB. The outcome measure of the second analysis was meal-level kilocalorie intake, with true intake compared to three estimation methods.STATISTICAL ANALYSES PERFORMED:Multilevel modeling was used to analyze the influence of the seven predictors of KPB. The accuracy of the model was compared to previous methods of estimating KPB using a repeated-measured analysis of variance.RESULTS:All hypothesized relationships were significant, with slopes in the expected direction, except for body mass index and time in meal. In addition, the new model (with nonsignificant predictors removed) improved over earlier models of KPB.CONCLUSIONS:This model offers a new direction for methods of inexpensive, accurate, and objective estimates of kilocalorie intake from bite-based measures.

This study aimed to examine changes in Healthy Eating Index-2010 (HEI-2010) scores, components, and energy intake between automated Bite Counter (Bite) and traditional diet tracking mobile app (App) groups. This was a secondary analysis of the DIET Mobile study, a 6-month weight loss intervention. Assessments were conducted at baseline, 3 and 6 months. Twenty-four-hour dietary recall data were collected. Overweight/obese adults (N = 81) were randomized to Bite or App groups. The intervention was delivered through behavioral podcasts. Participants were provided customized calorie/bite goals and used their device to track intake. We assessed changes in HEI-2010 scores from baseline to 6 months between groups. t tests, chi-square, and repeated measures ANOVA were performed. Models included time, group, and group×time interaction, controlling for no other covariates. There were no significant changes in HEI-2010 scores, components, or energy intake between groups at 3 or 6 months. This study found that both the Bite and App groups were able to reduce their energy intake and there was no difference in changes in diet quality between groups, which provides some support for using the less intensive, more automated method (Bite Counter) for long-term dietary self-monitoring. The study had a low sample size according to power calculations. Future interventions aimed at improving diet quality through mHealth technology should investigate the potential to develop a new app or modify an existing app that would allow for dietary self-monitoring that provides specific feedback on how users’ diets align with diet quality components in the HEI to improve overall diet quality.

BackgroundConclusions regarding bite count rates and body mass index (BMI) in free-living populations have primarily relied on self-report. The objective of this exploratory study was to compare the relationship between BMI and bite counts measured by a portable sensor called the Bite Counter in free-living populations and participants eating in residence.MethodsTwo previously conducted studies were analyzed for relationships between BMI and sensor evaluated bite count/min, and meal duration. Participants from the first study (N=77) wore the bite counter in a free-living environment for a continuous period of 14 days. The second study (N=214) collected bite count/min, meal duration, and total energy intake in participants who consumed one meal in a cafeteria. Linear regression was applied to examine relationships between BMI and bite count/min.ResultsThere was no significant correlation in the free-living participants average bite counts per second and BMI (R-2=0.03, p=0.14) and a significant negative correlation in the cafeteria participants (R-2=0.04, p=0.03) with higher bite count rates observed in lean versus obese participants. There was a significant correlation between average meal duration and BMI in the free-living participants (R-2=0.08, p=0.01). Total energy intake in the cafeteria participants was also significantly correlated to meal duration (R-2=0.31, p<0.001).ConclusionsWith additional novel applications of the Bite Counter, insights into free-living eating behavior may provide avenues for future interventions that are sustainable for long term application.

This paper considers the problem of recognizing eating gestures by tracking wrist motion. Eating gestures can have large variability in motion depending on the subject, utensil, and type of food or beverage being consumed. Previous works have shown viable proofs-of-concept of recognizing eating gestures in laboratory settings with small numbers of subjects and food types, but it is unclear how well these methods would work if tested on a larger population in natural settings. As more subjects, locations and foods are tested, a larger amount of motion variability could cause a decrease in recognition accuracy. To explore this issue, this paper describes the collection and annotation of 51,614 eating gestures taken by 269 subjects eating a meal in a cafeteria. Experiments are described that explore the complexity of hidden Markov models (HMMs) and the amount of training data needed to adequately capture the motion variability across this large data set. Results found that HMMs needed a complexity of 13 states and 5 Gaussians to reach a plateau in accuracy, signifying that a minimum of 65 samples per gesture type are needed. Results also found that 500 training samples per gesture type were needed to identify the point of diminishing returns in recognition accuracy. Overall, the findings provide evidence that the size a data set typically used to demonstrate a laboratory proofs-of-concept may not be sufficiently large enough to capture all the motion variability that could be expected in transitioning to deployment with a larger population. Our data set, which is 1-2 orders of magnitude larger than all data sets tested in previous works, is being made publicly available.

The purpose of this panel is to provide information on motion sickness in virtual environments and discuss human factors issues associated with visually induced motion sickness. With the continued growth of virtual reality devices comes challenges, one of which is the pervasiveness of motion sickness. A panel of experts on motion sickness will join to discuss how they incite and study sickness in their research, providing lessons on how it can impact other research topics and be avoided in future studies. Panelists use methods such as postural sway, psychophysiological measures, and subjective measures to study different aspects of motion sickness. Technology used by these experts ranges from rotating chairs to high fidelity driving simulators. This panel is oriented for those with simulators who want to know what interventions they can employ to alleviate sickness in their research, those who create virtual environments, and those who use virtual reality devices in their research. Considerations for the design of virtual and augmented reality devices and content will be discussed.

This paper considers the lexicographical challenge of defining actions a person takes while eating. The goal is to establish objective and repeatable gesture definitions based on discernible intent. Such a standard would support the sharing of data and results between researchers working on the problem of automatic monitoring of dietary intake. We define five gestures: taking a bite of food (bite), sipping a drink of liquid (drink), manipulating food for preparation of intake (utensiling), not moving (rest) and a non-eating category (other). To test this lexicography, we used our definitions to label a large data set and tested for inter-rater reliability. The data set consists of a total of 276 participants eating a single meal while wearing a watch-like device to track wrist motion. Video was simultaneously recorded and subsequently reviewed to label gestures. A total of 18 raters manually labeled 51,614 gestures. Every meal was labeled by at least 1 rater, with 95 meals labeled by 2 raters. Inter-rater reliability was calculated in terms of agreement, boundary ambiguity, and mistakes. Results were 92.5 exact agreement, 17.5 bite and 1.9 utensiling and 8.7 Finally, a comparison of gesture segments against single index labels of bites and drinks from a previous effort showed an agreement of 95.8 ambiguity and 3.6 developing a consensus lexicography of eating gestures for the research community.