Objective monitoring of food intake and ingestive behavior in a free-living environment remains an open problem that has significant implications study treatment obesity eating disorders. In this paper, novel wearable sensor system (automatic ingestion monitor, AIM) is presented for objective free living. The proposed device integrates three modalities wirelessly interface to smartphone: jaw motion sensor, hand gesture accelerometer. A fusion pattern recognition method was developed...

Monitoring of posture allocations and activities enables accurate estimation energy expenditure may aid in obesity prevention treatment. At present, devices rely on multiple sensors distributed the body thus be too obtrusive for everyday use. This paper presents a novel wearable sensor, which is capable very recognition common postures activities. The patterns heel acceleration plantar pressure uniquely characterize typical while requiring minimal preprocessing no feature extraction. shoe...

The task of structural health monitoring (SHM) aging highway bridges and overpasses is important not only from the point preventing economic losses traffic delays detours but also a matter catastrophic failures loss human life. In recent years, wireless sensor technologies have been used extensively to develop SHM platforms for bridges. A limitation sensors finite life span batteries high cost battery replacements, which make such systems prohibitively expensive in many cases. Energy...

A methodology of studying ingestive behavior by non-invasive monitoring swallowing (deglutition) and chewing (mastication) has been developed. The target application for the developed is to study behavioral patterns food consumption producing volumetric weight estimates energy intake. Monitoring based on detecting a sound sensor located over laryngopharynx or bone-conduction microphone through below-the-ear strain sensor. Proposed sensors may be implemented in wearable device, thus enabling...

Objective and automatic sensor systems to monitor ingestive behavior of individuals arise as a potential solution replace inaccurate method self-report. This paper presents simple system related signal processing pattern recognition methodologies detect periods food intake based on non-invasive monitoring chewing. A piezoelectric strain gauge was used capture movement the lower jaw from 20 volunteers during quiet sitting, talking consumption. These signals were segmented into non-overlapping...

Our understanding of etiology obesity and overweight is incomplete due to lack objective accurate methods for monitoring ingestive behavior (MIB) in the free-living population. research has shown that frequency swallowing may serve as a predictor detecting food intake, differentiating liquids solids, estimating ingested mass. This paper proposes compares two acoustical detection from sounds contaminated by motion artifacts, speech, external noise. Methods based on mel-scale Fourier spectrum,...

Approximately one-third of people who recover from a stroke require some form assistance to walk. Repetitive task-oriented rehabilitation interventions have been shown improve motor control and function in with stroke. Our long-term goal is design test an intensive intervention that will utilize the two primary components constrained-induced movement therapy: massed, training behavioral methods increase use affected limb real world. The technological component based on wearable...

Introduction Accurately and precisely estimating free-living energy expenditure (EE) is important for monitoring balance quantifying physical activity. Recently, single multisensor devices have been developed that can classify activities, potentially resulting in improved estimates of EE. Purpose This study aimed to determine the validity EE estimation a footwear-based activity monitor compare this against variety research consumer monitors. Methods Nineteen healthy young adults (10 men, 9...

Presence of speech and motion artifacts has been shown to impact the performance wearable sensor systems used for automatic detection food intake. This work presents a novel device which can detect intake even when user is physically active and/or talking. The consists piezoelectric strain placed on temporalis muscle, an accelerometer, data acquisition module connected temple eyeglasses. Data from 10 participants was collected while they performed activities including quiet sitting, talking,...

Automatic recognition of activities daily living (ADL) is an important component in understanding energy balance, quality life, and other areas health well-being. In our previous work, we had proposed insole-based activity monitor-SmartStep, designed to be socially acceptable comfortable. The goals the current study were: first, validation SmartStep a broad set ADL; second, comparison wrist sensor testing these combination; third, evaluation SmartStep's accuracy measuring wear noncompliance...

Driven by the need to reduce installation cost and maintenance of structural health monitoring (SHM) systems, wireless sensor networks (WSNs) are becoming increasingly popular. Perfect time synchronization amongst sensors is a key factor enabling use low-cost, low-power WSNs for applications based on output-only modal analysis structures. In this paper we present theoretical framework impact created delays in measured system response reconstruction mode shapes using popular frequency domain...

In the current investigation, an innovative time-domain damage index is introduced for first time which based on local statistical features of waveform. This called 'normalized correlation moment' (NCM) and composed nth moment cross-correlation baseline comparison waves. The performance this novel compared some synthetic signals with that existing Pearson coefficient (signal difference coefficient, SDC). proposed shown to have significant advantages over SDC, including sensitivity...

Many methods for monitoring diet and food intake rely on subjects self-reporting their daily intake.These are subjective, potentially inaccurate need to be replaced by more accurate objective methods.This paper presents a novel approach that uses an Electroglottograph (EGG) device automatic detection of intake.Thirty participated in 4-visit experiment involving the consumption meals with self-selected content.Variations electrical impedance across larynx caused passage during swallowing were...

Purpose: The purpose of this study was to determine the ability a novel shoe-based sensor that uses accelerometers, pressure sensors, and pattern recognition with support vector machine (SVM) accurately identify sitting, standing, walking postures in people stroke. Methods: Subjects stroke wore while randomly assuming 3 main postures: walking. A SVM classifier used train validate data develop individual group models, which were tested for accuracy, recall, precision. Results: Eight subjects...

Monitoring of postures and activities is used in many clinical research applications, some which may require highly reliable posture activity recognition with desired accuracy well above 99% mark. This paper suggests a method for performing accurate from data collected by wearable shoe monitor (SmartShoe) through classification rejection. Signals pressure acceleration sensors embedded SmartShoe are either as raw sensor or after feature extraction. The Support vector machine (SVM) multilayer...

The goal of this pilot study is to evaluate the feasibility using a 3-axis accelerometer attached frame eyeglasses for automatic detection food intake. A 3D acceleration sensor was temple regular eyeglasses. Ten participants wore device in two visits (first, laboratory; second, free-living) on different days, reporting intake episodes pushbutton. Hold-one-out procedure used test algorithm detection. signal split into epochs varying durations (3s, 5s, 10s 15s, 20s, 25s, and 30s); 152 time...

Camera-based passive dietary intake monitoring is able to continuously capture the eating episodes of a subject, recording rich visual information, such as type and volume food being consumed, well behaviours subject. However, there currently no method that incorporate these clues provide comprehensive context from (e.g., subject sharing with others, what eating, how much left in bowl). On other hand, privacy major concern while egocentric wearable cameras are used for capturing. In this...

The first step in any dietary monitoring system is the automatic detection of eating episodes. To detect episodes, either sensor data or images can be used, and method result false-positive detection. This study aims to reduce number false positives episodes by a wearable sensor, Automatic Ingestion Monitor v2 (AIM-2). Thirty participants wore AIM-2 for two days each (pseudo-free-living free-living). were detected three methods: (1) recognition solid foods beverages captured AIM-2; (2)...

Life cycle monitoring of civil infrastructure such as bridges and buildings is critical to the long-term operational cost safety aging structures. The widespread use Structural Health Monitoring (SHM) systems limited due unavailability specialized data acquisition equipment, high generic absence fully automatic decision support systems. goals presented project include: first, design a Wireless Intelligent Sensor Actuator Network (WISAN) creation an inexpensive set instrumentation for tasks...

Understanding of eating behaviors associated with obesity requires objective and accurate monitoring food intake patterns. Accurate methods are available for measuring total energy expenditure its components in free-living populations, but people far less involve self-reporting or subjective monitoring. We suggest that chews swallows can be used ingestive behavior. This hypothesis was verified a human study involving 20 subjects. Chews were captured during periods quiet resting, talking,...