Smart Wearable System for Medical Use

M2M ECG (Machine-to-Machine Electrocardiogram)

Smart Healthcare System Based on Medical Artificial Intelligence

Machine Learning Approach for Screening Vestibular Schwannoma based on Pure Tone Audiometry

Ultra-Low Latency Scalable Machine-to-Machine Communication System

Multi-UAV based Flying Object Real-time Visual Tracking System

And More…

Intelligent Cyber-Physical Systems for Real-Time Monitoring and Diagnosis of Heart Diseases

Our research aims to develop an intelligent cyber-physical system that can monitor and diagnose heart diseases in real-time. This system will leverage advanced machine learning techniques to provide accurate and timely diagnosis, which can significantly improve patient outcomes.

Machine Learning for Early Diagnosis of Hidden Hearing Loss

Our research aims to develop a machine learning-based system for analyzing large-scale data from pure tone audiometry to enable early diagnosis of hidden hearing loss. By leveraging the power of machine learning algorithms, we hope to significantly improve the accuracy and efficiency of hearing loss diagnosis.

M2M ECG Monitoring System with Ultra-Low Latency and High Reliability

Our research aims to develop an M2M ECG monitoring system that can provide ultra-low latency and high reliability for remote health monitoring. By developing advanced algorithms and leveraging state-of-the-art communication technologies, we aim to provide patients with reliable and timely health monitoring services.

Wearable Technology for Remote Monitoring and Diagnosis of Medical Conditions

Our research aims to investigate the use of wearable technology for remote monitoring and diagnosis of medical conditions. By developing smart wearables that can continuously monitor vital signs and other health parameters, we aim to provide patients with an efficient and effective way to manage their health.

Real-Time Communication Platform Based on IoT/LTE-M for Smart Healthcare Applications

Our research aims to develop a real-time communication platform based on IoT/LTE-M for smart healthcare applications. By leveraging the power of IoT and advanced communication technologies, we aim to enable real-time sharing of health data and facilitate efficient collaboration between healthcare professionals.

Medical Artificial Intelligence for Improved Diagnosis and Treatment

Our research aims to leverage medical artificial intelligence to improve the accuracy and efficiency of medical diagnosis and treatment. By developing advanced algorithms and leveraging big data analytics, we aim to enable more precise and personalized healthcare services.

UAVs for Real-Time Visual Tracking of Flying Objects in Smart Healthcare Systems

Our research aims to investigate the use of unmanned aerial vehicles (UAVs) for real-time visual tracking of flying objects in smart healthcare systems. By developing advanced computer vision algorithms and leveraging UAVs, we aim to enable efficient and effective monitoring of patient health in real-time.

Smart Wearables for Remote Monitoring and Early Diagnosis of Medical Conditions

Our research aims to develop a smart wearables platform for remote monitoring and early diagnosis of medical conditions. By leveraging advanced sensors and machine learning algorithms, we aim to provide patients with an efficient and effective way to manage their health.

Blockchain for Secure and Efficient Sharing of Medical Data in Smart Healthcare Systems

Our research aims to investigate the use of blockchain technology for secure and efficient sharing of medical data in smart healthcare systems. By leveraging the power of blockchain, we aim to provide patients with greater control over their health data and enable more efficient collaboration between healthcare professionals.

Scalable and Efficient System for Processing and Analyzing Medical Big Data in Real-Time

Our research aims to develop a scalable and efficient system for processing and analyzing medical big data in real-time. By developing advanced algorithms and leveraging state-of-the-art big data analytics technologies, we aim to enable more precise and personalized healthcare services.