Back close

Behavioural Abnormality Detection for population with Mild cognitive impairment in a multi-occupant Ambient Assisted Living

Project Incharge:Dr. Subhasri Duttagupta
Behavioural Abnormality Detection for population with Mild cognitive impairment in a multi-occupant Ambient Assisted Living

Consider a multi-home multi-occupant AAL system that monitors elderly population for their daily activities (HAR) using both environmental and wearable sensors. The objectives of this research can be listed as follows: 

  • Provide a personalized assistance based on the occupants’ medical history. The assistance may depend on the specific activity (for example, taking certain medicines at a particular time)
  • Raise a timely alarm if some abnormality is detected for people who are having cognitive decline, this involves correlating with an occupant’s daily routine activities. 
  • Use a trained model to recognize the activities of a new user with very different physiological parameters, age and perhaps belonging to a different demographic background. 

Related Projects

Center of Excellence in Advanced Materials and Green Technologies
Center of Excellence in Advanced Materials and Green Technologies
Design and Development of an IoT Based Smart Irrigation and Fertilization System for Chilli Farming
Design and Development of an IoT Based Smart Irrigation and Fertilization System for Chilli Farming
Multi-User Detection in Sporadic 3GPP Massive M2M Communication via Compressed Sensing
Multi-User Detection in Sporadic 3GPP Massive M2M Communication via Compressed Sensing
Towards Next-generation Adaptable Computing
Towards Next-generation Adaptable Computing
Integration of AMoRA (Amrita Modular Robotic Arm) with RoboAnalyzer® for Effective Robotics Education
Integration of AMoRA (Amrita Modular Robotic Arm) with RoboAnalyzer® for Effective Robotics Education
Admissions Apply Now