PRE2019 4 Group4

Group Members

Name	Student Number	Study	Email
Cahitcan Uzman	1284304	Computer Science	c.uzman@student.tue.nl
Zakaria Ameziane	1005559	Computer Science	z.ameziane@student.tue.nl
Lex van Heugten	0973789	Applied Physics	l.m.v.heugten@student.tue.nl

Problem Statement

As the years pass, every people get older and they start to lose some abilities, due to the nature of biological human body. Older people get vulnerable in terms of health, their body movements slow down, the communication rate between neurons on their brain decreases which might cause mental problems, etc. Thus, their dependency on other people increases, in order to maintain their lives properly. In other words, older people may need to be cared by someone else, due to deformation of their bodies. However, some of the old people aren’t lucky to find someone to receive their support. For those people, the good news is that the technology and artificial intelligence is developing and one of the great applications is care robots for elder people. Although “care robots” is a great idea and most likely to ease the human life, the technology brings some concerns and ambiguities along with it. Since “communication with elder people” is an essential for caring, the benefit of care robots increases as the communication between the user and the robot gets clearer and easier. Moreover, emotion is one of the most important tools for communication, that’s why we aim to investigate the use of emotion recognition on care robots with the help of artificial intelligence. Our main goal is to make the communication between an old person and the robot more powerful by making the robot understand the current emotional situation of the user and behave correspondingly.

Users and their needs

The healthcare service: The healthcare services have a big shortage of human careers, which lead to the use of robots to take care of elderly people. The healthcare services want to provide care robots that are as similar as possible to the human careers.

Elderly people: The elderly people need someone to take care of them both physically, and also share their emotions with, so the care robot need to understand his/her emotions. That way it can understand what the person needs and act based on that.

Enterprises who develop the care robot: The enterprise aim to improve the care robots technology and make it as effective as a human career by adding features that can allow the robot to interact emotionally with people.

USE analysis

Users: <br\> The population of old people keeps growing in a high rate. In Europe, citizens aged 65 and over comprised 20.3 of the population in 2019(1) and it’s expected to keep increasing every year. For instance, the number of available careers in many countries is not enough to satisfy all the needs, Therefore the idea of care robots have been introduced.<br\> As people get older, not only they need someone to take care of them physically, but they also need human interactions, sharing their emotions.. otherwise they become vulnerable to loneliness and social isolation, that’s why a lot of people refuse the idea of using care robots. <br\> Introducing the technology of facial emotion recognition in care robots will help the robot understand the emotions of the person and react based on that, as for example if the person is sad, the robot may use some techniques to cheer up the person, or if the person is happy the robot can ask the person to share what made him/her happy. By sharing emotions, the elderly people will feel less lonely, and by understanding the emotion of the person, the robot will know more about what the person really need. <br\> <br\> Society:
This technology can have a big impact on the society. In many countries, the healthcare system can’t provide enough careers to cover all the needs, so this turns to be so difficult for the elderly people and especially for their families. Society will benefit from this technology because it will increase the overall happiness by providing the needs of elderly people and their families.<br\> <br\>

enterprise: <br\>

Approach

The subject of face recognition has strongly developed in the past few years. One can find face recognition and face tracking in daily life in camera's that automate the focus on the faces in view and of course snapchat filters. This technology will be a good starting point for this project. However, thee consistency of face recognition is very low. Factors like skin color, lighting and deformaties of the face are certain to upset most face recognition systems every once in a while. Especially the point of deformaties is important for our target user. As mentioned above, old age comes with many different effects and the decay of skin is especially relevant for this project. Skin on the face begins to hang, wrinkle and colorize at older age and might create issues for our face recognition software. Tuning this software to work with elderly will be the first milestone.

The second milestone will, of course, be the recognition of emotion. Recognition of emotion is complex. It needs a relevant large database to work correctly. Here we will probably come against the same problems. Namely working with older elderly as target group. Our software should be fine tuned to their face structure as well as creating a database that is created from relevant data. At last, the system should be consistent. This is designed to be part of a care robot. Care robots should relieve a part of the care that is given by human professionals and should therefore be consistent enough te actually take some of the work pressure of their hands.

Planning

Week 1:

• Brainstorming ideas
  
• Decide upon a subject
  
• Who are the users and their needs
  
• Study literatures about the topic
  

Week 2:

• USE aspects analysis
  
• Gathers RPCs
  
• Care robots that already exist
  
• Make research about the elderly opinion and their wishes/concerns
  

Week3:

• Analyze different aspects of this technology ( for example how the robot should react to different emotions ..)
  
• Different techniques that can be used for facial emotion recognition
  
• The use of convolutional Neural Network for facial emotion recognition
  
• Find a database of face pictures that is large enough for CNN training
  

Week4:

• Start the implementation of the facial emotion recognition
  

Week5:

• Implementation of the facial emotion recognition
  

Week6:

• Testing and improving
  

Week7:

• Prepare presentation and finalize the wiki page
  

Week8:

• Derive conclusions and possible future improvements
  
• Finalize presentation.
  

Deliverables:

• The wiki page: this will include all the steps we took to make this project, as well as all the analysis we’ve made and results we achieved.
• A software that will be able to recognize facial emotions
• A final presentation of our project

Weekly contribution

Week 1

	Time spent	tasks
name1	Cell 2	Cell 3
name2	Cell B	Cell C