In this paper, we present the FIU MARG Dataset (FIUMARGDB) of signals from the tri-axial accelero... more In this paper, we present the FIU MARG Dataset (FIUMARGDB) of signals from the tri-axial accelerometer, gyroscope, and magnetometer contained in a low-cost miniature magnetic–angular rate–gravity (MARG) sensor module (also known as magnetic inertial measurement unit, MIMU) for the evaluation of MARG orientation estimation algorithms. The dataset contains 30 files resulting from different volunteer subjects executing manipulations of the MARG in areas with and without magnetic distortion. Each file also contains reference (“ground truth”) MARG orientations (as quaternions) determined by an optical motion capture system during the recording of the MARG signals. The creation of FIUMARGDB responds to the increasing need for the objective comparison of the performance of MARG orientation estimation algorithms, using the same inputs (accelerometer, gyroscope, and magnetometer signals) recorded under varied circumstances, as MARG modules hold great promise for human motion tracking applica...
A major challenge in medical studies, especially those that are longitudinal, is the problem of m... more A major challenge in medical studies, especially those that are longitudinal, is the problem of missing measurements which hinders the effective application of many machine learning algorithms. Furthermore, recent Alzheimer's Disease studies have focused on the delineation of Early Mild Cognitive Impairment (EMCI) and Late Mild Cognitive Impairment (LMCI) from cognitively normal controls (CN) which is essential for developing effective and early treatment methods. To address the aforementioned challenges, this paper explores the potential of using the eXtreme Gradient Boosting (XGBoost) algorithm in handling missing values in multiclass classification. We seek a generalized classification scheme where all prodromal stages of the disease are considered simultaneously in the classification and decision-making processes. Given the large number of subjects (1631) included in this study and in the presence of almost 28% missing values, we investigated the performance of XGBoost on th...
This paper presents a new version of an EMG-based, hands-free, cursor control system, and compare... more This paper presents a new version of an EMG-based, hands-free, cursor control system, and compares its performance to that of a previous version. Both systems use classification algorithms that rely on the periodogram estimation of the power spectral density (PSD) of electromyogram (EMG) signals from muscles in the face. The older system requires three electrodes for EMG input, and utilizes an algorithm that calculates partial power accumulations over the frequency ranges of 0Hz - 145Hz and 145Hz - 600Hz in the PSDs of the EMG signals. The new system requires four electrodes for EMG input, and utilizes an algorithm that calculates mean power frequency (MPF) values to assist in distinguishing the cranial muscle that contracted. An experiment was devised to gauge the point-and-click capabilities of both systems. The experimental results were evaluated using Fitts' Law analysis. The results show that the new algorithm provides improved point-and-click performance over the old algor...
IEEE journal of biomedical and health informatics, 2013
A new thermal imaging framework with unique feature extraction and similarity measurements for fa... more A new thermal imaging framework with unique feature extraction and similarity measurements for face recognition is presented. The research premise is to design specialized algorithms that would extract vasculature information, create a thermal facial signature and identify the individual. The proposed algorithm is fully integrated and consolidates the critical steps of feature extraction through the use of morphological operators, registration using the Linear Image Registration Tool and matching through unique similarity measures designed for this task. The novel approach at developing a thermal signature template using four images taken at various instants of time ensured that unforeseen changes in the vasculature over time did not affect the biometric matching process as the authentication process relied only on consistent thermal features. Thirteen subjects were used for testing the developed technique on an in-house thermal imaging system. The matching using the similarity meas...
International Journal on Artificial Intelligence Tools, 2009
While Eye Gaze Tracking (EGT) systems have demonstrated their potential as computer cursor contro... more While Eye Gaze Tracking (EGT) systems have demonstrated their potential as computer cursor control devices, their application outside the laboratory environment has been less prominent than originally expected. This may be due to limitations in the stability of the cursor controlled by EGT devices and in the potential for unintended selections…
In this paper, we present the FIU MARG Dataset (FIUMARGDB) of signals from the tri-axial accelero... more In this paper, we present the FIU MARG Dataset (FIUMARGDB) of signals from the tri-axial accelerometer, gyroscope, and magnetometer contained in a low-cost miniature magnetic–angular rate–gravity (MARG) sensor module (also known as magnetic inertial measurement unit, MIMU) for the evaluation of MARG orientation estimation algorithms. The dataset contains 30 files resulting from different volunteer subjects executing manipulations of the MARG in areas with and without magnetic distortion. Each file also contains reference (“ground truth”) MARG orientations (as quaternions) determined by an optical motion capture system during the recording of the MARG signals. The creation of FIUMARGDB responds to the increasing need for the objective comparison of the performance of MARG orientation estimation algorithms, using the same inputs (accelerometer, gyroscope, and magnetometer signals) recorded under varied circumstances, as MARG modules hold great promise for human motion tracking applica...
A major challenge in medical studies, especially those that are longitudinal, is the problem of m... more A major challenge in medical studies, especially those that are longitudinal, is the problem of missing measurements which hinders the effective application of many machine learning algorithms. Furthermore, recent Alzheimer's Disease studies have focused on the delineation of Early Mild Cognitive Impairment (EMCI) and Late Mild Cognitive Impairment (LMCI) from cognitively normal controls (CN) which is essential for developing effective and early treatment methods. To address the aforementioned challenges, this paper explores the potential of using the eXtreme Gradient Boosting (XGBoost) algorithm in handling missing values in multiclass classification. We seek a generalized classification scheme where all prodromal stages of the disease are considered simultaneously in the classification and decision-making processes. Given the large number of subjects (1631) included in this study and in the presence of almost 28% missing values, we investigated the performance of XGBoost on th...
This paper presents a new version of an EMG-based, hands-free, cursor control system, and compare... more This paper presents a new version of an EMG-based, hands-free, cursor control system, and compares its performance to that of a previous version. Both systems use classification algorithms that rely on the periodogram estimation of the power spectral density (PSD) of electromyogram (EMG) signals from muscles in the face. The older system requires three electrodes for EMG input, and utilizes an algorithm that calculates partial power accumulations over the frequency ranges of 0Hz - 145Hz and 145Hz - 600Hz in the PSDs of the EMG signals. The new system requires four electrodes for EMG input, and utilizes an algorithm that calculates mean power frequency (MPF) values to assist in distinguishing the cranial muscle that contracted. An experiment was devised to gauge the point-and-click capabilities of both systems. The experimental results were evaluated using Fitts' Law analysis. The results show that the new algorithm provides improved point-and-click performance over the old algor...
IEEE journal of biomedical and health informatics, 2013
A new thermal imaging framework with unique feature extraction and similarity measurements for fa... more A new thermal imaging framework with unique feature extraction and similarity measurements for face recognition is presented. The research premise is to design specialized algorithms that would extract vasculature information, create a thermal facial signature and identify the individual. The proposed algorithm is fully integrated and consolidates the critical steps of feature extraction through the use of morphological operators, registration using the Linear Image Registration Tool and matching through unique similarity measures designed for this task. The novel approach at developing a thermal signature template using four images taken at various instants of time ensured that unforeseen changes in the vasculature over time did not affect the biometric matching process as the authentication process relied only on consistent thermal features. Thirteen subjects were used for testing the developed technique on an in-house thermal imaging system. The matching using the similarity meas...
International Journal on Artificial Intelligence Tools, 2009
While Eye Gaze Tracking (EGT) systems have demonstrated their potential as computer cursor contro... more While Eye Gaze Tracking (EGT) systems have demonstrated their potential as computer cursor control devices, their application outside the laboratory environment has been less prominent than originally expected. This may be due to limitations in the stability of the cursor controlled by EGT devices and in the potential for unintended selections…
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Papers by Malek Adjouadi