Muhammad Farooq

University of Alabama | UA · Department of Electrical and Computer Engineering

Abstract Accurate and objective assessment of energy intake remains an ongoing problem. We used features derived from annotated video observation and a chewing sensor to predict mass and energy intake during a meal without participant self-report. 30 participants each consumed 4 different meals in a laboratory setting and wore a chewing sensor whil...

Video observations have been widely used for providing ground truth for wearable systems for monitoring food intake in controlled laboratory conditions; however, video observation requires participants be confined to a defined space. The purpose of this analysis was to test an alternative approach for establishing activity types and food intake bou...

The goal of this pilot study is to evaluate the feasibility of using a 3-axis accelerometer attached to the frame of eyeglasses for automatic detection of food intake. A 3D acceleration sensor was attached to the temple of the regular eyeglasses. Ten participants wore the device in two visits (first, laboratory; second, free-living) on different da...

To avoid the pitfalls of self-reported dietary intake, wearable sensors can be used. Many food ingestion sensors offer the ability to automatically detect food intake using time resolutions that range from 23 ms to 8 min. There is no defined standard time resolution to accurately measure ingestive behavior or a meal microstructure. This paper aims...

With the widespread use of smartphones, people are taking more and more images of their foods. These images can be used for automatic recognition of foods present and potentially providing an indication of eating habits. Traditional methods rely on computing a number of user derived features from image and then use a classification method to classi...

Objective: This work explored the potential use of a wearable sensor system for providing just-in-time (JIT) feedback on the progression of a meal and tested its ability to reduce the total food mass intake. Methods: Eighteen participants consumed three meals each in a lab while monitored by a wearable sensor system capable of accurately trackin...

Several methods have been proposed for automatic and objective monitoring of food intake, but their performance suffers in the presence of speech and motion artifacts. This work presents a novel sensor system and algorithms for detection and characterization of chewing bouts from a piezoelectric strain sensor placed on the temporalis muscle. The pr...

Research suggests that there might be a relationship between chewing rate and final energy intake. Wearable sensor systems have been proposed for automatic detection of food intake. This work presents the use of linear regression for estimation of chew counts from piezoelectric sensor signal. For known chewing sequences, four features are computed...

Research suggests that there might be a relationship between chew count as well as chewing rate and energy intake. Chewing has been used in wearable sensor systems for the automatic detection of food intake, but little work has been reported on the automatic measurement of chew count or chewing rate. This work presents a method for the automatic qu...

Selection and use of pattern recognition algorithms is application dependent. In this work, we explored the use of several ensembles of weak classifiers to classify signals captured from a wearable sensor system to detect food intake based on chewing. Three sensor signals (Piezoelectric sensor, accelerometer, and hand to mouth gesture) were collect...

Presence of speech and motion artifacts has been shown to impact the performance of wearable sensor systems used for automatic detection of food intake. This work presents a novel wearable device which can detect food intake even when the user is physically active and/or talking. The device consists of a piezoelectric strain sensor placed on the te...

Research shows that rapid weight gain in infancy is associated to the development of obesity at a later stage in life. Feeding behavior in infants contributes to the rapid weight in early life. Sucking counts can be used to quantify the feeding behavior in infants. This paper presents a new signal processing algorithm to estimate sucking counts in...

Results of recent research suggest that there may be a relationship between the eating rate and the total energy intake in a meal. The chewing rate is an indicator of the eating rate that may be measured by a sensor. A number of wearable solutions have been presented for the automatic detection of chewing, but little work has been done on counting...

Rapid weight gain during infancy increases the risk of obesity. Given that infant feeding may contribute to rapid weight gain, it would be useful to develop objective tools which can monitor infant feeding behavior. This paper presents an objective method for examining infant sucking count during meals. A piezoelectric jaw motion sensor and a video...

This chapter discusses the use of strain sensors in wearable devices. Strain sensors are used to monitor deformation under applied load. Various techniques for the fabrication of strain sensors are discussed and some example applications are presented. Special focus is placed on textile based and inkjet-printed strain sensors. Textile based strain...

Many methods for monitoring diet and food intake rely on subjects self-reporting their daily intake. These methods are subjective, potentially inaccurate and need to be replaced by more accurate and objective methods. This paper presents a novel approach that uses an electroglottograph (EGG) device for an objective and automatic detection of food i...

In Machine Learning applications, the selection of the classification algorithm depends on the problem at hand. This paper provides a comparison of the performance of the Support Vector Machine (SVM) and the Artificial Neural Network (ANN) for food intake detection. A combination of time domain (TD) and frequency domain (FD) features, extracted fro...

Selection of the most representative features is important for any pattern recognition system. This paper investigates the importance of time domain (TD) and frequency domain (FD) features used for automatic food intake detection in a wearable sensor system by using Random Forests classification. Features were extracted from signals collected using...

A critical part of structural health monitoring is accurate detection of damages in the structure. This paper presents the results of two multi-class damage detection and identification approaches based on classification using Support Vector Machine (SVM) and Artificial Neural Networks (ANN). The article under test was a fiber composite panel model...

Image registration is a process of overlaying various images of a scene. This process has four basic steps. In this work we have replaced a feature matching step with efficient and fast feature tracking. Several problems, arose due to this technique, are discussed and their solutions are proposed. The proposed algorithm is then tested on various se...

Image registration is a stepwise process of overlaying various images of a scene. Accurate image registration in a real time environment has always been a challenge involving the detection of analogous features and then construction of mosaic within plausible accuracy range. Digital Signal Processor is an asset in this regard; its advanced versions...

In this paper, a design for a wideband communication jamming system is presented which is capable of covering all commonly used communication frequencies. The sudden boom in telecommunication industry has magnified the need of a wideband communication jamming system which can simultaneously block the usage of cellular phones, GPS, WiFi, Bluetooth a...

In this paper we propose implementation of a viable algorithm for real time tracking of objects in a video sequence on a Digital Signal Processor (DSP). Three different tracking algorithms are simulated and on the basis of simulation results, the best algorithm is proposed for hardware implementation. The selected algorithm tracks objects by minimi...