PRE2019 4 Group4

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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.

Objectives

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\> Over the years, the companies who develop care robots made a huge development in improving the efficiency of the robot, as it started with a simple robot that can only accomplish some basic physical task, to a robot that can communicate in human language with people, then a robot that can entertain the elderly people in different ways. Those companies always aim to improve its robots to satisfy the needs of the users, and adding the facial emotion recognition to the robot will be a big improvement and is expected to rise the desire of elderly people to have one of these care robots. The companies will definitely benefit from this technology as the need of care robots is expected to rise in the coming years. Studies have shown that in year 2050, the population of people over the age of 65 in Europe will represent 28.5% of the population. So this investment will come up with a huge profits to those companies

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

State of the art

Weekly contribution

Papers

  • The role of robots in the improving work of nurses, Blechar L.

Nurses cannot be replaced by robots. Their task is more complex than just the routine tasks that they deliver. However due to the enormous shortage of nurses the pressure on nurses also inhibits them to give this human side of care. Therefore robots cannot replace but can relieve the nurses from the routine care and create more time for empathic and more human care.

  • Robot Therapy: A New Approach for Mental Healthcare of the Elderly – A Mini-Review, Shibata T.

The elderly react positive to a robot companion (animal) when it reacts as they would expect. The more knowledge people have about the animal the robot is mimicking the more critical they are of their performance.

  • On overview of human interactive robots for psychological enrichment, Shibata T.

Humans learn about the behavior of the robot and this changes the relationship. If a robot can learn about the behavior of the human the relation may deepen even more since the relation is no longer one sided. Intelligence and learning capabilities are therefore important in a care robot.

  • Deep interaction: Wearable robot-assisted emotion communication for enhancing perception and expression ability of children with Autism Spectrum Disorders, Xiao W.

Inability to recognize emotion is a serious problem for autistic children. A system to recognize emotions was build. Incorporation of visual and audio cues to recognize emotion. Emotion recognition can be improved if audio cues are also considered.

  • Can nurses remain relevant in a technologically advanced future? Pepito J. A.

Nurses should be more involved in the development of care robots and other care technology. Nurses can oversee, use and apply the right technology for each specific patient. Seeing nurses as a main user should influence technology.

  • Tarnowski, P., Kołodziej, M., Majkowski, A., & Rak, R. J. (2017). Emotion recognition using facial expressions. Procedia Computer Science, 108, 1175–1184. doi: 10.1016/j.procs.2017.05.025

Abstract: In the article there are presented the results of recognition of seven emotional states (neutral, joy, sadness, surprise, anger, fear, disgust) based on facial expressions. Coefficients describing elements of facial expressions, registered for six subjects, were used as features

  • Jonathan, Lim, A. P., Paoline, Kusuma, G. P., & Zahra, A. (2018). Facial Emotion Recognition Using Computer Vision. 2018 Indonesian Association for Pattern Recognition International Conference (INAPR). doi: 10.1109/inapr.2018.8626999

Abstract:This paper examines how human emotion, which is often expressed by face expression, could be recognized using computer vision

  • Singh, D. (2012). Human Emotion Recognition System. International Journal of Image, Graphics and Signal Processing, 4(8), 50–56. doi: 10.5815/ijigsp.2012.08.07

Abstract: This paper discusses the application of feature extraction of facial expressions with combination of neural network for the recognition of different facial emotions (happy, sad, angry, fear, surprised, neutral etc..)

  • Meder, C., Iacono, L. L., & Guillen,, S. S. (2018). Affective Robots: Evaluation of Automatic Emotion Recognition Approaches on a Humanoid Robot towards Emotionally Intelligent Machines. World Academy of Science, Engineering and Technology International Journal of Mechanical and Mechatronics Engineering. doi: 10.1999/1307-6892/10009027

Abstract:In this paper, the emotion recognition capabilities of the humanoid robot Pepper are experimentally explored, based on the facial expressions for the so-called basic emotions, as well as how it performs in contrast to other state-of-the-art approaches with both expression databases compiled in academic environments and real subjects showing posed expressions as well as spontaneous emotional reactions

This article focuses on the values care robots for older people need to have. Many participants from different countries, including old people, informal careers, and formal careers for old people, were given different scenarios of how robots should be used. Based on that discussion, a set of values was derived and prioritized.

This article studies the facial expressions for different age groups. Moving Window Technique (MWT) was used to identify the different facial expression between old adults and young adults.


Week 1

Name Tasks Total hours
Cahitcan Research, Problem statement, finding papers -
Zakaria Introduction lecture(2h) - brainstorming ideas with the group(2h) - research about the topic(2h) - Users and their goals(30 min)- study scientific papers (3h) 9.5 hours
Lex Research, Approach, finding papers -
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