[Show abstract][Hide abstract] ABSTRACT: Recently, wearable computers have become new members in the family of mobile electronic devices, adding new functions to those provided by smartphones and tablets. As "always-on" miniature computers in the personal space, they will play increasing roles in the field of healthcare. In this work, we present our development of eButton, a wearable computer designed as a personalized, attractive, and convenient chest pin in a circular shape. It contains a powerful microprocessor, numerous electronic sensors, and wireless communication links. We describe its design concepts, electronic hardware, data processing algorithms, and its applications to the evaluation of diet, physical activity and lifestyle in the study of obesity and other chronic diseases.
[Show abstract][Hide abstract] ABSTRACT: Image-based dietary assessment has recently received much attention in the community of obesity research. In this assessment, foods in digital pictures are specified, and their portion sizes (volumes) are estimated. Although manual processing is currently the most utilized method, image processing holds much promise since it may eventually lead to automatic dietary assessment. In this paper we study the problem of segmenting food objects from images. This segmentation is difficult because of various food types, shapes and colors, different decorating patterns on food containers, and occlusions of food and non-food objects. We propose a novel method based on a saliency-aware active contour model (ACM) for automatic food segmentation from images acquired by a wearable camera. An integrated saliency estimation approach based on food location priors and visual attention features is designed to produce a salient map of possible food regions in the input image. Next, a geometric contour primitive is generated and fitted to the salient map by means of multi-resolution optimization with respect to a set of affine and elastic transformation parameters. The food regions are then extracted after contour fitting. Our experiments using 60 food images showed that the proposed method achieved significantly higher accuracy in food segmentation when compared to conventional segmentation methods.
[Show abstract][Hide abstract] ABSTRACT: Non-nutritive sweeteners (NNSs) provide sweetness to foods and beverages without adding calories. They have thus been found useful in minimizing the dietary sugar content of diabetics and the dietary energy content of individuals attempting to lose or maintain body weight. Their usefulness in weight reduction has recently been questioned, however, based on the notion that they can actually increase hunger and food intake and thereby promote weight gain. The evidence offered in support of this idea comes principally from the fields of taste physiology, metabolic endocrinology, human behavior, and epidemiology. This review evaluates this evidence and does not find it compelling. Indeed, the most straightforward findings to the contrary derive from several intervention studies in both children and adults showing that the chronic, covert replacement of dietary sugar with NNSs does not increase, and can in fact reduce, energy intake and body weight. Expected final online publication date for the Annual Review of Food Science and Technology Volume 6 is February 28, 2015. Please see http://www.annualreviews.org/catalog/pubdates.aspx for revised estimates.
Review of Food Science and Technology 12/2014; 6(1). DOI:10.1146/annurev-food-022814-015635 · 6.29 Impact Factor
[Show abstract][Hide abstract] ABSTRACT: Accurate estimation of food portion size is of paramount importance in dietary studies. We have developed a small, chest-worn electronic device called eButton which automatically takes pictures of consumed foods for objective dietary assessment. From the acquired pictures, the food portion size can be calculated semi-automatically with the help of computer software. The aim of the present study is to evaluate the accuracy of the calculated food portion size (volumes) from eButton pictures.
Participants wore an eButton during their lunch. The volume of food in each eButton picture was calculated using software. For comparison, three raters estimated the food volume by viewing the same picture. The actual volume was determined by physical measurement using seed displacement.
Dining room and offices in a research laboratory.
Seven lab member volunteers.
Images of 100 food samples (fifty Western and fifty Asian foods) were collected and each food volume was estimated from these images using software. The mean relative error between the estimated volume and the actual volume over all the samples was -2·8 % (95 % CI -6·8 %, 1·2 %) with sd of 20·4 %. For eighty-five samples, the food volumes determined by computer differed by no more than 30 % from the results of actual physical measurements. When the volume estimates by the computer and raters were compared, the computer estimates showed much less bias and variability.
From the same eButton pictures, the computer-based method provides more objective and accurate estimates of food volume than the visual estimation method.
Public Health Nutrition 12/2013; 7(8):1-11. DOI:10.1017/S1368980013003236 · 2.68 Impact Factor
[Show abstract][Hide abstract] ABSTRACT: Dietary assessment is important in health maintenance and intervention in many chronic conditions, such as obesity, diabetes, and cardiovascular disease. However, there is currently a lack of convenient methods for measuring the volume of food (portion size) in real-life settings. We present a computational method to estimate food volume from a single photographical image of food contained in a typical dining plate. First, we calculate the food location with respect to a 3D camera coordinate system using the plate as a scale reference. Then, the food is segmented automatically from the background in the image. Adaptive thresholding and snake modeling are implemented based on several image features, such as color contrast, regional color homogeneity and curve bending degree. Next, a 3D model representing the general shape of the food (e.g., a cylinder, a sphere, etc.) is selected from a pre-constructed shape model library. The position, orientation and scale of the selected shape model are determined by registering the projected 3D model and the food contour in the image, where the properties of the reference are used as constraints. Experimental results using various realistically shaped foods with known volumes demonstrated satisfactory performance of our image based food volume measurement method even if the 3D geometric surface of the food is not completely represented in the input image.
[Show abstract][Hide abstract] ABSTRACT: Exercise raises brain serotonin release and is postulated to cause fatigue in athletes; ingestion of branched-chain amino acids (BCAA), by competitively inhibiting tryptophan transport into brain, lowers brain tryptophan uptake and serotonin synthesis and release in rats, and reputedly in humans prevents exercise-induced increases in serotonin and fatigue. This latter effect in humans is disputed. But BCAA also competitively inhibit tyrosine uptake into brain, and thus catecholamine synthesis and release. Since increasing brain catecholamines enhances physical performance, BCAA ingestion could lower catecholamines, reduce performance and thus negate any serotonin-linked benefit. We therefore examined in rats whether BCAA would reduce both brain tryptophan and tyrosine concentrations and serotonin and catecholamine synthesis. Sedentary and exercising rats received BCAA or vehicle orally; tryptophan and tyrosine concentrations and serotonin and catecholamine synthesis rates were measured 1 h later in brain. BCAA reduced brain tryptophan and tyrosine concentrations, and serotonin and catecholamine synthesis. These reductions in tyrosine concentrations and catecholamine synthesis, but not tryptophan or serotonin synthesis, could be prevented by co-administering tyrosine with BCAA. Complete essential amino acid mixtures, used to maintain or build muscle mass, were also studied, and produced different effects on brain tryptophan and tyrosine concentrations and serotonin and catecholamine synthesis. Since pharmacologically increasing brain catecholamine function improves physical performance, the finding that BCAA reduce catecholamine synthesis may explain why this treatment does not enhance physical performance in humans, despite reducing serotonin synthesis. If so, adding tyrosine to BCAA supplements might allow a positive action on performance to emerge.
[Show abstract][Hide abstract] ABSTRACT: Background & aims:
The ingestion by rats of different proteins causes large differences in the plasma ratio of tryptophan to other large neutral amino acids, which predicts brain tryptophan uptake and serotonin synthesis. We evaluated in humans whether ingesting these proteins also produces large excursions in the tryptophan ratio.
Fasting males (n = 6) ingested V-8 Juice containing 40 g of α-lactalbumin, gluten, zein or starch. Blood was drawn before and at 30 min intervals after ingestion for 4 h; tryptophan and other large neutral amino acids were quantitated.
Pre-meal plasma tryptophan was ~50 nmol/ml; the tryptophan ratio was ~0.010. α-Lactalbumin increased plasma tryptophan (3-fold) and the tryptophan ratio (50%); starch did not change either tryptophan variable, while gluten caused a modest (25%) and zein a large reduction (50%) in plasma tryptophan. Gluten and zein reduced the tryptophan ratio. The maximal difference in the tryptophan ratio occurred between α-lactalbumin and zein and was large (~3-fold).
Since the plasma tryptophan ratio predicts brain tryptophan uptake and serotonin synthesis in rats, the differences in the ratio produced in humans by these proteins may modify serotonin synthesis, and perhaps elicit serotonin-linked changes in behavior.
[Show abstract][Hide abstract] ABSTRACT: The daily nutritional requirement for l-tryptophan (Trp) is modest (5 mg/kg). However, many adults choose to consume much more, up to 4-5 g/d (60-70 mg/kg), typically to improve mood or sleep. Ingesting l-Trp raises brain tryptophan levels and stimulates its conversion to serotonin in neurons, which is thought to mediate its actions. Are there side effects from Trp supplementation? Some consider drowsiness a side effect, but not those who use it to improve sleep. Though the literature is thin, occasional side effects, seen mainly at higher doses (70-200 mg/kg), include tremor, nausea, and dizziness, and may occur when Trp is taken alone or with a drug that enhances serotonin function (e.g., antidepressants). In rare cases, the "serotonin syndrome" occurs, the result of too much serotonin stimulation when Trp is combined with serotonin drugs. Symptoms include delirium, myoclonus, hyperthermia, and coma. In 1989 a new syndrome appeared, dubbed eosinophilia myalgia syndrome (EMS), and was quickly linked to supplemental Trp use. Key symptoms included debilitating myalgia (muscle pain) and a high peripheral eosinophil count. The cause was shown not to be Trp but a contaminant in certain production batches. This is not surprising, because side effects long associated with Trp use were not those associated with the EMS. Over 5 decades, Trp has been taken as a supplement and as an adjunct to medications with occasional modest, short-lived side effects. Still, the database is small and largely anecdotal. A thorough, dose-related assessment of side effects remains to be conducted.
Journal of Nutrition 10/2012; 142(12). DOI:10.3945/jn.111.157065 · 3.88 Impact Factor
[Show abstract][Hide abstract] ABSTRACT: A novel method to estimate the 3D location of a circular feature from a 2D image is presented and applied to the problem of objective dietary assessment from images taken by a wearable device. Instead of using a common reference (e.g., a checkerboard card), we use a food container (e.g., a circular plate) as a necessary reference before the volumetric measurement. In this paper, we establish a mathematical model formulating the system involving a camera and a circular object in a 3D space and, based on this model, the food volume is calculated. Our experiments showed that, for 240 pictures of a variety of regular objects and food replicas, the relative error of the image-based volume estimation was less than 10% in 224 pictures.
Conference proceedings: ... Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Conference 08/2012; 2012:4545-8. DOI:10.1109/EMBC.2012.6346978
[Show abstract][Hide abstract] ABSTRACT: The ingestion of large neutral amino acids (LNAA), notably tryptophan, tyrosine and the branched-chain amino acids (BCAA), modifies tryptophan and tyrosine uptake into brain and their conversion to serotonin and catecholamines, respectively. The particular effect reflects the competitive nature of the transporter for LNAA at the blood-brain barrier. For example, raising blood tryptophan or tyrosine levels raises their uptake into brain, while raising blood BCAA levels lowers tryptophan and tyrosine uptake; serotonin and catecholamine synthesis in brain parallel the tryptophan and tyrosine changes. By changing blood LNAA levels, the ingestion of particular proteins causes surprisingly large variations in brain tryptophan uptake and serotonin synthesis, with minimal effects on tyrosine uptake and catecholamine synthesis. Such variations elicit predictable effects on mood, cognition and hormone secretion (prolactin, cortisol). The ingestion of mixtures of LNAA, particularly BCAA, lowers brain tryptophan uptake and serotonin synthesis. Though argued to improve physical performance by reducing serotonin function, such effects are generally considered modest at best. However, BCAA ingestion also lowers tyrosine uptake, and dopamine synthesis in brain. Increasing dopamine function in brain improves performance, suggesting that BCAA may fail to increase performance because dopamine is reduced. Conceivably, BCAA administered with tyrosine could prevent the decline in dopamine, while still eliciting a drop in serotonin. Such an LNAA mixture might thus prove an effective enhancer of physical performance. The thoughtful development and application of dietary proteins and LNAA mixtures may thus produce treatments with predictable and useful functional effects.
[Show abstract][Hide abstract] ABSTRACT: A remarkable amount of information has emerged in the past decade regarding sweet taste physiology. This article reviews these data, with a particular focus on the elucidation of the sweet taste receptor, its location and actions in taste transduction in the mouth, its nontaste functions in the gastrointestinal tract (e.g., in enteroendocrine cells), and the brain circuitry involved in the sensory processing of sweet taste. Complications in the use of rodents to model human sweet taste perception and responses are also considered. In addition, information relating to low-calorie sweeteners (LCS) is discussed in the context of these issues. Particular consideration is given to the known effects of LCS on enteroendocrine cell function.
Journal of Nutrition 05/2012; 142(6):1134S-41S. DOI:10.3945/jn.111.149567 · 3.88 Impact Factor
[Show abstract][Hide abstract] ABSTRACT: Measuring food volume (portion size) is a critical component in both clinical and research dietary studies. With the wide availability of cell phones and other camera-ready mobile devices, food pictures can be taken, stored or transmitted easily to form an image based dietary record. Although this record enables a more accurate dietary recall, a digital image of food usually cannot be used to estimate portion size directly due to the lack of information about the scale and orientation of the food within the image. The objective of this study is to investigate two novel approaches to provide the missing information, enabling food volume estimation from a single image. Both approaches are based on an elliptical reference pattern, such as the image of a circular pattern (e.g., circular plate) or a projected elliptical spotlight. Using this reference pattern and image processing techniques, the location and orientation of food objects and their volumes are calculated. Experiments were performed to validate our methods using a variety of objects, including regularly shaped objects and food samples.
[Show abstract][Hide abstract] ABSTRACT: Previous studies have shown that brain tyrosine (TYR) levels and catecholamine synthesis rate increase in rats as chronic dietary protein content increases from 2 to 10% (% weight). A single protein, casein, was examined. The present study explores how TYR levels and catecholamine synthesis (and tryptophan (TRP) levels and serotonin synthesis) change when different proteins are ingested chronically over the same range of dietary protein contents.
Male rats ingested for 8 days diets contain 2 or 10% protein (zein, gluten, casein, soy protein, or alpha-lactalbumin). On the last day, they were killed 2.5 hours into the dark period, 30 minutes after receiving an injection of m-hydroxybenzylhydrazine, an inhibitor of aromatic l-amino acid decarboxylase. Brain samples were analyzed for amino acids, including 5-hydroxytryptophan (index of serotonin synthesis rate) and dihydroxyphenylalanine (index of catecholamine synthesis rate), by HPLC-electrochemical detection.
TYR levels and catecholamine synthesis rate in brain were unaffected by the particular protein ingested. However, TRP levels and serotonin synthesis rate varied markedly, depending on the protein ingested, with effects being most prominent in the 10% protein groups. The effect of dietary protein on brain TRP correlated very highly with its effect on serotonin synthesis.
The results indicate that the protein ingested can chronically modify TRP levels and serotonin synthesis in brain, but not TYR levels or catecholamine synthesis, with effects most distinct at an adequate level of protein intake (10%).
[Show abstract][Hide abstract] ABSTRACT: A new technique to extract and evaluate physical activity patterns from image sequences captured by a wearable camera is presented in this paper. Unlike standard activity recognition schemes, the video data captured by our device do not include the wearer him/herself. The physical activity of the wearer, such as walking or exercising, is analyzed indirectly through the camera motion extracted from the acquired video frames. Two key tasks, pixel correspondence identification and motion feature extraction, are studied to recognize activity patterns. We utilize a multiscale approach to identify pixel correspondences. When compared with the existing methods such as the Good Features detector and the Speed-up Robust Feature (SURF) detector, our technique is more accurate and computationally efficient. Once the pixel correspondences are determined which define representative motion vectors, we build a set of activity pattern features based on motion statistics in each frame. Finally, the physical activity of the person wearing a camera is determined according to the global motion distribution in the video. Our algorithms are tested using different machine learning techniques such as the K-Nearest Neighbor (KNN), Naive Bayesian and Support Vector Machine (SVM). The results show that many types of physical activities can be recognized from field acquired real-world video. Our results also indicate that, with a design of specific motion features in the input vectors, different classifiers can be used successfully with similar performances.
[Show abstract][Hide abstract] ABSTRACT: Serotonin (5HT) synthesis in brain is influenced by precursor (tryptophan (TRP)) concentrations, which are modified by food ingestion. Hence, in rats, a carbohydrate meal raises brain TRP and 5HT; a protein-containing meal does not, but little attention has focused on differences among dietary proteins. Recently, single meals containing different proteins have been shown to produce marked changes in TRP and 5HT. The present studies evaluate if such differences persist when rats ingest such diets chronically. Male rats were studied that ingested diets for 9 days containing zein, wheat gluten, soy protein, casein, or α-lactalbumin (17% dry weight). Brain TRP varied up to eightfold, and 5HT synthesis fivefold among the different protein groups. TYR and LEU concentrations, and catecholamine synthesis rate in brain varied much less. The effects of dietary protein on brain TRP and 5HT previously noted after single meals thus continue undiminished when such diets are consumed chronically.
Neurochemical Research 03/2011; 36(3):559-65. DOI:10.1007/s11064-010-0382-1 · 2.59 Impact Factor
[Show abstract][Hide abstract] ABSTRACT: In dietary studies, an accurate tool for diet assessment is highly required. In this paper, we present a new approach to the estimation of the food volume from a single input image based on the virtual reality (VR) technology. A virtual reality model is built for the estimation process and an algorithm is developed for the calculation of food volume. Experimental results have indicated high accuracy and robustness in the food volume estimation. I. INTRODUCTION Obesity has become an epidemic that threatens the health of millions of Americans and costs billions of dollars in health care. In studies of obesity and its potential treatments, accurate dietary assessment is essential. Currently, the most common type of dietary assessment used is derived from self-reports by respondents (1). However, this method is subject to significant error because it depends on the accuracy of respondents' memories and their willingness to report their true dietary intake. With recent rapid advances in the fields of image processing and computer vision techniques, some approaches have been developed for volume estimation using image-based computational algorithm to monitor dietary intake (2). This paper proposed a new approach based on Virtual Realty (VR) to accurately estimate food volume. The basic principle of this approach is using computer vision and VR technology to simulate the real world (3), in where a number of 3D wireframe objects could be built to fit specific food items in digital images. Different with traditional processes, our approach estimated specific food volume directly, producing accurate estimates of the volume of food from a single image.
[Show abstract][Hide abstract] ABSTRACT: Accurate estimation of food volume plays an important role in dietary assessment using digital photographs. In this paper, we present a new approach based on a circular object (e.g., a dining plate or a coin) as a physical reference to determine food portion size. A geometrical model relating the circular object and its image is built. An algorithm to estimate food volume using the geometric model is developed. Experimental results have shown high reliability and accuracy of this approach.
Bioengineering Conference, Proceedings of the 2010 IEEE 36th Annual Northeast; 04/2010