Vision 

The continuous advancements in sensing and computing technologies have enabled the development of smart and intelligent healthcare systems by integrating classical clinical practices with modern AI-based techniques. AI is now being extensively utilized for addressing critical challenges related to human health and wellbeing in both clinical and research perspectives. The Intelligent Biomedical Applications (IBA) lab at SPCAI envisions coping with the emerging problems of human health and wellbeing by conducting and translating AI-based research (leveraging the areas of machine learning, advanced biomedical signal processing, medical imaging, and pattern recognition) to design and development of intelligent healthcare solutions and applications. Therefore, the IBA lab primarily focuses on advancing state-of-the-art real-time health monitoring systems, introducing novel sensing modalities for human activity monitoring and behavior cognition, and integrating intelligent data analysis techniques within biomedical information systems to develop research-oriented yet reliable solutions for biomedical applications. The mission of the lab is to innovate, design, develop, and validate AI-based solutions for medical and clinical usage that span over the areas relevant to accidental falls, cardiovascular diseases, motor, and movement disorders, human behavior anomalies, pathology detection, pandemic prediction, motor rehabilitation, mental disorders, and bionics.  

Aims & Objectives

  • To drive cutting-edge research innovations in the areas relevant to biomedical systems and applications  
  • To address emerging challenges related to AI applications in health and biosciences   
  • To bridge the gaps between researchers/innovators and the medical community and contribute towards the sustainability of healthcare systems  
  • To utilize various analytical, theoretical, and experimental tools and develop state-of-the-art AI and machine learning-based algorithms for facilitating smart healthcare solutions  
  • To develop AI-based services and novel healthcare solutions that can respond to the increasing burden of chronic diseases or disabilities  

Research Areas 

  • Human activity and behavior analysis for assisted living based on smartphone and wearable sensors  
  • Personal attributes recognition and personality assessment based on physiological attributes  
  • Monitoring and analysis of human daily living activities for minimizing the propagation of non-communicable diseases  
  • Multimodal sensing for abnormal human activity detection and recognition  
  • Fall detection, prediction, and falling activity recognition  
  • Stress detection and assessment using EEG signals  
  • Emotion recognition based on physiological signals acquisition in restricted settings  
  • AI in Human Rehabilitation 
  • Pathology Detection 
  • Radiological diagnosis of cerebral tuberculosis using computer vision and machine learning  
  • Pulmonary Tuberculosis identification from cough and lung sounds using deep learning techniques 
  • Real-time Healthcare Monitoring System using AI Techniques. 
  • Wearable computing for human behavior monitoring and tracking 

Equipment 

The IBA Lab is furnished with the latest technology and state-of-the-art equipment for data acquisition, processing, and analysis supported by a variety of computational resources, tools, and platforms.  

  • Processing Boards (Arduino, Raspberry Pi, NodeMCU) 
  • Sensors (Temperature, Humidity, Pressure, Weight Sensor) 
  • Edge and Gateway devices 
  • Data Storage Equipment 
  • Specialized State-of-the-Art Equipment 
  • Electrical Muscle Stimulator (NMES) 
  • Electrical Nerve Stimulator (TENS) 
  • Treadmill  
  • Stethoscope 
  • Wearable Sensing Kits (Motion Sensor, Physiological Sensors) 
  • Portable EEG Headset 
  • Oscilloscope 
  • Function Generator 
  • Blood Pressure Monitor 
  • Digital Multimeter

Simulation resources include software like Matlab and Python IDE (PyCharm, Anaconda, Spyder) for running data processing and analysis algorithms. The computational resources include High-Performance Computing (HPC) and workstations. 

Projects

  • Human activity and behavior analysis using smart sensing 
  • Emotion recognition based on physiological signals acquisition 
  • Fall detection and recognition using wearable sensors 
  • Pathology detection 

Courses

  • Biomedical Imaging 
  • Deep Learning for Biomedical Applications 
  • AI for Biomedical Engineering 
  • Biomedical Signal Processing 
  • Biomedical Visualization