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

Machine Learning based Hand Orthotic Device
Machine Learning based Hand Orthotic Device
Image Denoising using Variation Perona-Malik Model Based on the Variable Exponent
Image Denoising using Variation Perona-Malik Model Based on the Variable Exponent
Hybrid Solar and Archimedes Spiral Wind Turbine Tree for Microgrid
Hybrid Solar and Archimedes Spiral Wind Turbine Tree for Microgrid
Nanosurface Engineering of Bare Metallic Coronary Stents for Combating In-Stent Restenosis
Nanosurface Engineering of Bare Metallic Coronary Stents for Combating In-Stent Restenosis
Seaweed Project
Seaweed Project
Admissions Apply Now