A5002504765- Indoor and Outdoor Localization Technologies
- Context-Aware Activity Recognition Systems
- Air Quality Monitoring and Forecasting
- Mobile Health and mHealth Applications
- Artificial Intelligence in Healthcare
- Air Quality and Health Impacts
- Speech and Audio Processing
- Wireless Body Area Networks
- Machine Learning in Healthcare
- Digital Mental Health Interventions
- Underwater Vehicles and Communication Systems
- Distributed Sensor Networks and Detection Algorithms
- Sparse and Compressive Sensing Techniques
- ECG Monitoring and Analysis
- Music and Audio Processing
- Microwave Imaging and Scattering Analysis
- Non-Invasive Vital Sign Monitoring
- Underwater Acoustics Research
- Marine animal studies overview
- COVID-19 Clinical Research Studies
- Retinal Imaging and Analysis
- AI in cancer detection
- Glaucoma and retinal disorders
- Traffic Prediction and Management Techniques
- COVID-19 diagnosis using AI
California State University, Long Beach
2025
California State University Los Angeles
2017-2024
California State University System
2017-2021
San Jose State University
2020
University of Southern California
2018
University of California, Los Angeles
2013-2016
Binghamton University
2011-2014
UCLA Health
2013-2014
Cornell University
2013
In the wake of COVID-19 disease, caused by SARS-CoV-2 virus, we designed and developed a predictive model based on Artificial Intelligence (AI) Machine Learning algorithms to determine health risk predict mortality patients with COVID-19. this study, used dataset more than 2,670,000 laboratory-confirmed from 146 countries around world including 307,382 labeled samples. This study proposes an AI help hospitals medical facilities decide who needs get attention first, has higher priority be...
Abstract In the wake of COVID-19 disease, caused by SARS-CoV-2 virus, we designed and developed a predictive model based on Artificial Intelligence (AI) Machine Learning algorithms to determine health risk predict mortality patients with COVID-19. this study, used documented data 117,000 world-wide laboratory-confirmed This study proposes an AI help hospitals medical facilities decide who needs get attention first, has higher priority be hospitalized, triage when system is overwhelmed...
Accurate air pollution monitoring is critical to understand and mitigate the impacts of pollu-tion human health ecosystems. Due limited number geographical coverage advanced high accurate sensors monitor pollutants, many low-cost but low accuracy have been deployed. Calibrating essential leverage them for filling this gap in sensor coverage. We examine systematically how different Machine Learning (ML) models open-source packages could help improve particulate matter (PM) 2.5 data collected...
Food intake levels, hydration, ingestion rate, and dietary choices are all factors known to impact the risk of obesity. This paper presents a novel wearable system in form necklace, which aggregates data from an embedded piezoelectric sensor capable detecting skin motion lower trachea during ingestion. The produces output voltage with varying frequencies over time. As result, we propose algorithm based on time-frequency decomposition, spectrogram analysis signals, accurately distinguish...
Due to the exploding costs of chronic diseasesstemming from physical inactivity, wearable sensor systems toenable remote, continuous monitoring individuals has increasedin popularity. Many research and commercial exist inorder track activity levels users general dailymotion detailed movements. This work examines this problemfrom space smartwatches, using Samsung GalaxyGear, a device containing an accelerometer agyroscope, be used in recognizing activity. workalso shows sensors features...
Remote health monitoring (RHM) systems are becoming more widely adopted by clinicians and hospitals to remotely monitor communicate with patients while optimizing clinician time, decreasing hospital costs, improving quality of care. In the Women's heart study (WHHS), we developed Wanda-cardiovascular disease (CVD), where participants received healthy lifestyle education followed six months technology support reinforcement. Wanda-CVD is a smartphone-based RHM system designed assist in...
Wearable and implantable wireless communication devices have in recent years gained increasing attention for medical diagnostics therapeutics. In particular, capsule endoscopy has become a popular method to visualize diagnose the human gastrointestinal tract. Estimating exact position of when each image is taken very critical issue endoscopy. Several approaches been developed by researchers estimate location. However, some unique challenges exist in-body localization, such as severe...
Air pollution is a lethal global threat. To mitigate the effects of air pollution, we must first understand it, find its patterns and correlations, predict it in advance. highly dependent on spatial temporal correlations prior meteorological, wildfire, structures. We use advanced deep predictive Convolutional LSTM (ConvLSTM) model paired with cutting-edge Graph Network (GCN) architecture to spatiotemporal hourly PM2.5 across Los Angeles area over time. Our deep-learning does not atmospheric...
Accurate air pollution monitoring is critical to understand and mitigate the impacts of on human health ecosystems. Due limited number geographical coverage advanced, highly accurate sensors pollutants, many low-cost low-accuracy have been deployed. Calibrating essential fill gap in sensor coverage. We systematically examined how different machine learning (ML) models open-source packages could help improve accuracy particulate matter (PM) 2.5 data collected by Purple Air sensors. Eleven ML...
Remote health monitoring (RHM) has emerged as a solution to help reduce the cost burden of unhealthy lifestyles and aging populations. Enhancing compliance prescribed medical regimens is an essential challenge many systems, even those using smartphone technology. In this paper, we provide technique improve battery consumption examine effects lifetime on compliance, in attempt enhance users' adherence remote systems. We deploy WANDA-CVD, RHM system for patients at risk cardiovascular disease...
Wireless communication medical implants are gaining an important role in healthcare systems by controlling and transmitting the vital information of patients. Recently, Capsule Endoscopy (WCE) has become a popular method to visualize diagnose human gastrointestinal (GI) tract. Estimating exact location capsule when each image is taken very critical issue endoscopy. Most common localization methods based on estimating one or more location-dependent signal parameters like TOA RSS. However,...
Classical geolocation based on time-difference-of-arrival (TDOA) and frequency-difference-of-arrival (FDOA) uses a two-stage estimation approach. The single-stage approach direct position determination (DPD) has been proposed to improve accuracy. However, unlike the classical method, DPD method does all processing at single node. That is not desirable when computational capabilities are limited makes nonrobust loss of central sensor. We develop assess several variants that address these issues.
Monitoring vital signs for Intensive Care Unit (ICU) patients is an absolute necessity to help assess the general physical health. In this research, we use machine learning make a classification forecast that uses continuous ICU measurements predict whether of next hour would reach critical value or not. With early warning, nurses and doctors can prevent emergency situations may cause organ dysfunction even death before it too late. study, data includes sign measurements, laboratory test...
In remote health monitoring of patient's physical activity, ensuring correctness and authenticity the received data is essential. Although many activity systems, devices techniques have been developed, preventing patient cheating an monitor has a primarily unaddressed challenge across board. Patients can manually shake device (sensor) with their hand watch points or rewards increase, we define this as "self-inflicted" cheating. A second type cheating, "impersonator" when subjects sensor over...
Obesity, caused primarily by overeating, is a preventable chronic disease yielding staggering healthcare costs. To detect overeating passively, machine learning framework was designed to and accurately count the number of feeding gestures during an eating episode characterize each
The utility of wearable sensors for continuous gait monitoring has grown substantially, enabling novel applications on mobility assessment in healthcare. Existing approaches cycle detection rely predefined or experimentally tuned platform parameters and are often specific, parameter sensitive, unreliable noisy environments with constrained generalizability. To address these challenges, we introduce CyclePro, <sup xmlns:mml="http://www.w3.org/1998/Math/MathML"...
The earth pressure balance tunnel boring machine (TBM) is advanced excavation machinery used to efficiently drill through subsurface ground layers while placing precast concrete segments. They have become prevalent in tunneling projects because of their adaptability, speed, and safety. Optimal usage these machines requires information data about the soil worksite that TBM drilling through. This paper proposes utilization artificial intelligence learning, particularly recurrent neural...
Remote health monitoring systems (RHMS) are gaining an important role in healthcare by collecting and transmitting patient vital information providing data analysis medical adverse event prediction (e.g. hospital readmission prediction). Reduction the rate is typically achieved early of based on collected from RHMS, then applying intervention to prevent readmission. Given diversity populations continuous nature monitoring, a single static predictive model insufficient for accurately...
Food intake levels, hydration, chewing and swallowing rate, dietary choices are all factors known to impact one's health. This paper presents a novel wearable system in the form of necklace, which aggregates data from an embedded piezoelectric sensor capable detecting skin motion lower trachea during ingestion. We propose algorithm based on spectrogram analysis signals accurately distinguish between food types such as liquid solid, hot cold drinks hard soft foods. The necklace transmits...
Wireless health systems enable remote and continuous monitoring of individuals, with applications in elderly care support, chronic disease management, preventive care. The underlying sensing platform provides constructs that consider the quality information driven from system ensure reliability/validity outcomes to support decision-making processes. In this paper, we present an approach integrate contextual within data processing flow order improve measurements. We focus on a pilot...
This paper describes ongoing work to investigate the development of a complex system designed for extracting information from large acoustic datasets. The system, called DeLMA is based on integrating advanced machine learning with high performance computing (HPC). goal this provide capability accurately detect and classify whale sounds in acoustics datasets collected using underwater sensors. case study focused detecting communication signals North Atlantic Right Whale, Eubalaena glacialis,...