ARTIFICIAL INTELLIGENCE ENGINEERING
Bachelor	TR-NQF-HE: Level 6	QF-EHEA: First Cycle	EQF-LLL: Level 6

Course Introduction and Application Information

Course Code	Course Name	Semester	Theoretical	Practical	Credit	ECTS
PTR4068	Assistive Technologies	Spring	2	0	2	6

This catalog is for information purposes. Course status is determined by the relevant department at the beginning of semester.

Basic information

Language of instruction:	English
Type of course:	Non-Departmental Elective
Course Level:	Bachelor’s Degree (First Cycle)
Mode of Delivery:	Hybrid
Course Coordinator :	Assoc. Prof. HASAN KEREM ALPTEKİN
Recommended Optional Program Components:	None
Course Objectives:	This course aims to present the knowledge and decision making skills to the students on the assistive technology needs of the people with disabilities.

Learning Outcomes

The students who have succeeded in this course;
1. To be able to decide assistive technology in the direction of the needs of the people with disabilities.
2. To acquire the ability to identify basic concepts of assistive technology.
3. To be able to explain robot-assisted rehabilitation systems.
4. To determine the World Health Organization - International Classification of Function (WHO-ICF) in the concept of assisive technology.

Course Content

This course provides the student with learning the principle concepts on assistive technology, the ways to support people with disabilities in the concept of rehabilitation engineering in house, society, school or work places to upgrade their functional and cognitive skills, including the topics below.

Weekly Detailed Course Contents

Week	Subject	Related Preparation
1)	Introduction to assistive technology and rehabilitation engineering
2)	World Health Organization - International Classification of Functioning (WHO-ICF)
3)	Decision making in assistive technology
4)	Robotic therapy in physiotherapy and rehabilitation
5)	Principles of biomedical engineering in assistive technology
6)	Commercial assistive technology products, sensor applications and design considerations of assistive technology devices
7)	Mid term
8)	Robotic assisted rehabilitation systems
9)	Computer accessibility tools, sensory aids, mobile devices, activity monitoring
10)	Exoskeletons and robotic locomotion
11)	Student studies in assistive technology
12)	Stimulation of vagus nerve, innovation of new products and technology development
13)	Student studies in assistive technology
14)	Student studies in assistive technology

Sources

Course Notes / Textbooks:

Haftalık olarak verilecektir. - Will be given weekly.

References:

1. WHO (2001) International Classification of Functioning, Disability and Health (ICF). Geneva: World Health Organization
2. Henderson, S., Skelton, H. & amp; Rosenbaum, P. (2008). Assistive Devices for Children with Functional Impairments impact on child and Caregiver Function. Developmental Medicine & Child Neurology, 50: 89–98
3. LoPresti, E.F., Mihailidis, A. & Kirsch, N. (2004) Assistive Technology for Cognitive Rehabilitation: State of the Art. Nurophysiological Rehabilitation, 14 (1/2), 5–39
4. Assistive Technology Decision Tree by UnumProvident (1999) http://www.microsoft.com/enable/download/default.aspx#righttech.
Accsess time : 30 th may 2011.
5. Galvin, J. C., Scherer, M. J. (1996). Evaluating, Selecting, and Using Appropriate Assistive Technology. Maryland: An Aspen Publication

Evaluation System

Semester Requirements	Number of Activities	Level of Contribution
Attendance	13	% 0
Midterms	1	% 40
Final	1	% 60
Total		% 100
PERCENTAGE OF SEMESTER WORK		% 40
PERCENTAGE OF FINAL WORK		% 60
Total		% 100

ECTS / Workload Table

Activities	Number of Activities	Duration (Hours)	Workload
Course Hours	13	2	26
Study Hours Out of Class	14	9	126
Midterms	1	2	2
Final	1	2	2
Total Workload			156

Contribution of Learning Outcomes to Programme Outcomes

No Effect	1 Lowest	2 Low	3 Average	4 High	5 Highest

	Program Outcomes	Level of Contribution
1)	Have sufficient background in mathematics, science and artificial intelligence engineering.
2)	Use theoretical and applied knowledge in the fields of mathematics, science and artificial intelligence engineering together for engineering solutions.
3)	Identify, define, formulate and solve engineering problems, select and apply appropriate analytical methods and modeling techniques for this purpose.
4)	Analyse a system, system component or process and design it under realistic constraints to meet desired requirements; apply modern design methods in this direction.
5)	Select and use modern techniques and tools necessary for engineering applications.
6)	Design and conduct experiments, collect data, and analyse and interpret results.
7)	Work effectively both as an individual and as a multi-disciplinary team member.
8)	Access information via conducting literature research, using databases and other resources
9)	Follow the developments in science and technology and constantly update themself with an awareness of the necessity of lifelong learning.
10)	Use information and communication technologies together with computer software with at least the European Computer License Advanced Level required by their field.
11)	Communicate effectively, both verbal and written; know a foreign language at least at the European Language Portfolio B1 General Level.
12)	Have an awareness of the universal and social impacts of engineering solutions and applications; know about entrepreneurship and innovation; and have an awareness of the problems of the age.
13)	Have a sense of professional and ethical responsibility.
14)	Have an awareness of project management, workplace practices, employee health, environment and work safety; know the legal consequences of engineering practices.