A5030952581- Muscle activation and electromyography studies
- EEG and Brain-Computer Interfaces
- Neuroscience and Neural Engineering
- Advanced Sensor and Energy Harvesting Materials
- Blind Source Separation Techniques
- Artificial Intelligence in Healthcare
- Obesity, Physical Activity, Diet
- Climate Change and Health Impacts
- COVID-19 Clinical Research Studies
- ECG Monitoring and Analysis
- Cardiovascular Health and Risk Factors
- Health disparities and outcomes
- COVID-19 diagnosis using AI
- Long-Term Effects of COVID-19
- Motor Control and Adaptation
- Blood Pressure and Hypertension Studies
- Health Systems, Economic Evaluations, Quality of Life
- Diabetes, Cardiovascular Risks, and Lipoproteins
- Global Public Health Policies and Epidemiology
- Nutritional Studies and Diet
- Global Health Care Issues
- COVID-19 and Mental Health
- COVID-19 and healthcare impacts
- Neural dynamics and brain function
- Hand Gesture Recognition Systems
University of Isfahan
2016-2025
Universitat Politècnica de Catalunya
2016-2025
Tehran University of Medical Sciences
2024-2025
University of Washington
2023
Institute for Health Metrics and Evaluation
2023
Isfahan University of Medical Sciences
2017-2022
Imperial College London
2017-2022
Biomedical Research Networking Center in Bioengineering, Biomaterials and Nanomedicine
2022
FC Barcelona
2022
Chalmers University of Technology
2022
In the early months of COVID-19 pandemic with no designated cure or vaccine, only way to break infection chain is self-isolation and maintaining physical distancing. this article, we present a potential application Internet Things (IoT) in healthcare distance monitoring for situations. The proposed framework consists three parts: lightweight low-cost IoT node, smartphone (app), fog-based Machine Learning (ML) tools data analysis diagnosis. node tracks health parameters, including body...
Musculoskeletal disorders include more than 150 different conditions affecting joints, muscles, bones, ligaments, tendons, and the spine. To capture all health loss from death disability due to musculoskeletal disorders, Global Burden of Diseases, Injuries, Risk Factors Study (GBD) includes a residual category for other osteoarthritis, rheumatoid arthritis, gout, low back pain, neck pain. This is called includes, example, systemic lupus erythematosus spondylopathies. We provide updated...
Cancer is a collection of diseases that involves growing abnormal cells with the potential to invade or spread body. Breast cancer second leading cause death among women. A method for 5-year breast recurrence prediction presented in this manuscript. Clinicopathologic characteristics 579 patients (recurrence prevalence 19.3%) were analyzed and discriminative features selected using statistical feature selection methods. They further refined by Particle Swarm Optimization (PSO) as inputs...
A non-invasive fetal electrocardiogram (FECG) is used to monitor the electrical pulse of heart. Decomposing FECG signal from maternal ECG (MECG) a blind source separation problem, which hard due low amplitude FECG, overlap R waves, and potential exposure noise different sources. Traditional decomposition techniques, such as adaptive filters, require tuning, alignment, or pre-configuration, modeling desired map MECG FECG. The high correlation between fragments decreases performance...
In this paper, we propose a nonlinear minimally supervised method based on autoencoding (AEN) of EMG for myocontrol. The proposed was tested against the state-of-the-art (SOA) control scheme using Fitts' law approach. Seven able-bodied subjects performed series target acquisition myoelectric tasks AEN and SOA algorithms controlling two degrees-of-freedom (radial/ulnar deviation flexion/extension wrist), their online performance characterized by six metrics. Both methods allowed completion...
Deep learning has demonstrated excellent results for ECG anomaly detection, wherein most approaches used supervised learning. The requirement of thousands manually annotated samples is a concern state-of-the-art detection systems, especially fetal (FECG), and currently, there not publicly available FECG dataset each beat. In this paper, we offer modified active technique based on transfer learning, calibration probability, autoencoder-based sampling to reduce number requires annotate....
The aim of this study was to assess the accuracy convolution kernel compensation (CKC) method in decomposing high-density surface EMG (HDsEMG) signals from pennate biceps femoris long-head muscle. Although CKC has already been thoroughly assessed parallel-fibered muscles, there are several factors that could hinder its performance muscles. Namely, HDsEMG and muscles differ considerably terms number detectable motor units (MUs) spatial distribution motor-unit action potentials (MUAPs). In...
Coronary heart diseases/coronary artery diseases (CHDs/CAD), the most common form of cardiovascular disease (CVD), are a major cause for death and disability in developing/developed countries. CAD risk factors could be detected by physicians to prevent occurrence near future. Invasive coronary angiography, current diagnosis method, is costly associated with morbidity mortality patients. The aim this study was design computer-based noninvasive system clinically interpretable rules.
The COVID-19 is rapidly scattering worldwide, and the number of cases in Eastern Mediterranean Region rising. Thus, there a need for immediate targeted actions. We designed longitudinal study hot outbreak zone to analyze serial findings between infected patients detecting temporal changes from February 2020. In hospital-based open-cohort study, are followed admission until one year their discharge (the 1st, 4th, 12th weeks, first year). patient recruitment phase finished at end August 2020,...
The World Health Organization (WHO) is in the process of establishing a new global database on growth school children and adolescents. Limited national data exist from Asian children, notably those living Middle East North Africa (MENA). This study aimed to generate chart nationally representative sample Iranian aged 10-19 years, explore how well these anthropometric match with international references.In this nationwide study, were recorded students, who selected by multistage random...
Introduction This study aims to discuss and assess the impact of three prevalent methodological biases: competing risks, immortal-time bias, confounding bias in real-world observational studies evaluating treatment effectiveness. We use a demonstrative data example COVID-19 patients these biases propose potential solutions. Methods describe time-fixed by effectiveness hospitalized with COVID-19. For our analysis, we from registry who were admitted Bellvitge University Hospital Spain March...
This study was designed to develop a risk assessment chart for the clinical management and prevention of cardiovascular disease (CVD) in Iranian population, which is vital developing national programs. The Isfahan Cohort Study (ICS) population-based prospective 6504 adults ≥35 years old, followed-up ten years, from 2001 2010. Behavioral cardiometabolic factors were examined every five while biennial follow-ups occurrence events performed by phone calls or verbal autopsy. Among these...
Abstract The COVID-19 is rapidly scattering worldwide, and the number of cases in Eastern Mediterranean Region rising. Thus, there a need for immediate targeted actions. We designed longitudinal study hot outbreak zone to analyze serial findings between infected patients detecting temporal changes from February 2020. In hospital-based open-cohort study, are followed admission until one year their discharge (the 1st, 4th, 12th weeks, first year). patient recruitment phase finished at end...
The objective of the present systematic review was to incorporate previous studies investigating association birth order with risk systolic and diastolic blood pressure (DBP). We employed random-effects Bayesian meta-analyses, complemented by subgroup sensitivity analyses, including funnel plots, Begg's rank correlation test, Egger's linear regression Galbraith leave-one-out meta-analysis. Of 13 articles analyzed, 92% (12 articles) were published from 2010 onwards. aggregate sample comprised...
This paper presents a density-based method to automatically decompose single-channel intramuscular electromyogram (EMG) signals into their component motor unit action potential (MUAP) trains. In contrast most previous decomposition methods, which require pre-setting and (or) tuning of multiple parameters, the proposed takes advantage data-dependent strategies in pattern recognition procedures. this method, outliers (superpositions) are excluded prior classification MUAP templates identified...