Elderly Fall Detection System

A system will be developed for real time monitoring of elderly people and detecting if they face a fall. Falling; is a part of aging process as aging people are typically frailer, more unsteady and have slower reactions than younger individuals. If elderly people are living alone and fall down, it m

Project Title

Elderly Fall Detection System

Project Area of Specialization

Artificial Intelligence

Project Summary

A system will be developed for real time monitoring of elderly people and detecting if they face a fall. Falling; is a part of aging process as aging people are typically frailer, more unsteady and have slower reactions than younger individuals. If elderly people are living alone and fall down, it may be difficult for them to request for help. The main objective is to design a computer vision (CV) based fall detection system at affordable cost. The system will acknowledge the fall and report it to the caretaker or the person responsible. Basic aim is to develop a system that can be used in nursing homes; as such areas are usually equipped with surveillance cameras (or any other place with surveillance cameras).

   Computer vision (CV) is a field of computer science that works on enabling computers to see, identify and process images in the same way that human vision does, and then provide appropriate output. Using a real time video feed a sample is captured by the system that will be used by the system to decide whether or not a fall occurred. If a fall was detected, an alert will be generated. Following steps will be involved:

• Real time video acquisition
• Preprocess
  • Foreground segmentation
  • background subtraction (image processing)
• Machine learning (training the model)
• State classification
• Alert

Project Objectives

Our objective is to:

• To design a system that detects falls
• To improve probability of correct detection

• To make system independent from environmental features where environmental features cause problems when developing fall detection with environmental sensors like pressure sensors etc

To minimize hand-engineered image processing steps

Project Implementation Method

This project is about real-time fall detection. For this purpose we will be using dataset on which the system will be trained.

Data preprocessing in machine learning is a crucial step. It refers to the techniques of preparing raw data to make suitable for building and training of machine learning models. It is an integral step as quality of data that can be derived from it directly affects the ability of our model to learn. Therefore, after acquisition of dataset, it will be pre-processed.

To train classifier, machine learning algorithm will be used. Convolutional Neural Network (CNN); which is a deep neural network widely used for image- classification, will be used for classifying fall or not fall. The pre-processed data will be used for training of the classifier. The model can be trained once and used many times to perform classification.

Our project focuses on real-time fall detection, which means that a live video feed is required from the camera. From the video, frames will be extracted which will be pre-processed and passed to already trained classifier for classification as fall or not-fall.

If fall is detected, an alert will be generated to inform the care-taker about the fall. Otherwise, detection will continue.

Benefits of the Project

An unintentional event in which a person comes to rest on the ground, floor or lower level is known as a fall. According to World Health Organization (WHO), adults older than 65 years of age suffer the greatest number of fatal falls. The consequences of fall are death, injury, activity restriction, hospitalization, social isolation, quality of life, fear of falling. Falls may also precipitate adverse physical, psychological, social, financial and medical effects in the elderly. Falls can lead to severe:

• Physical consequences
• Psychological consequences
• Social consequences
• Financial and Medical consequences

   Thus, our system provides following benefits:

• It can help seniors remain independent.
• It prevents a senior from lying helpless for hours or days. This prevents seniors from suffering more serious complications including dehydration and hypothermia.
• Such system helps to alleviate a fear of falling. By not fearing falling seniors don’t curtail their activities and this helps them remain physically active and prevents functional decline.  

Our system aims at detecting falls and post the care-taker about it. So, that necessary action can be taken immediately.

Technical Details of Final Deliverable

HARDWARE:

Well formatted documentation

CD with all sources

Elderly Fall Detection System

Final Deliverable of the Project

Software System

Core Industry

Medical

Other Industries

Core Technology

Artificial Intelligence(AI)

Other Technologies

Sustainable Development Goals

Good Health and Well-Being for People

Required Resources

If you need this project, please contact me on contact@adikhanofficial.com