Outline

Overview

Biomechatronics is the application of mechatronic engineering to human biology, and as such it forms an important subset of the overall biomedical engineering discipline. This unit focusses on a number of areas of interest including auditory and optical prostheses, artificial hearts and active and passive prosthetic limbs and examines the biomechatronic systems (hardware and signal processing) that underpin their operation.

Unit details and rules

Academic unit	Biomedical Engineering
Credit points	6
Prerequisites ?	(MECH3921 or BMET3921) or MTRX3700 or MTRX3760 or (AMME5921 or BMET5921 or BMET9921)
Corequisites ?	None
Prohibitions ?	AMME4790 or AMME5790
Assumed knowledge ?	Knowledge in mechanical and electronic engineering; adequate maths and applied maths skills; background knowledge of physics, chemistry and biology; Some programming capability: MATLAB, C, C++, software tools used by engineers including CAD and EDA packages.
Available to study abroad and exchange students	Yes

Teaching staff

Coordinator	Graham Brooker, graham.brooker@sydney.edu.au
Tutor(s)	Jett van der Wallen, jett.vanderwallen@sydney.edu.au

Type	Description	Weight	Due	Length
Final exam (Open book)	Final Exam Type C	30%	Formal exam period	2 hours
Outcomes assessed:
Tutorial quiz	MATLAB Tutorials MATLAB based signal processing development	20%	Multiple weeks	Variable-length
Outcomes assessed:
Tutorial quiz	Online or Live Labs Analysis of data generated by lab experiments	20%	Multiple weeks	Weekly 3 hours + writeup time
Outcomes assessed:
Assignment	Assignment research and Design	15%	Week 09	About 20 hours
Outcomes assessed:
Small test	Weekly Quizzes Consolidation of lecture content. Short answers or brief analysis	15%	Weekly	Variable-length
Outcomes assessed:
= group assignment ? = Type C final exam ?

Assessment summary

Matlab Tutorial: A number of hands-on tutorials will be undertaken in which the students are expected to apply and investigate what they have learned by developing models and software. Tutors will grade the individual submissions from students.

Quizzes: Quizzes will be held at the end of sections to ensure that students have understood the work covered so far

Lab Activities: Weekly individual online or live group-based activities will be held in which students will be required to analyse data from sensing, processing and actuation hardware that illustrates some biomechatronic concepts. For those labs that are live, groups of students will conduct physiological measurements that will be logged, or used to control a robot arm. Students will submit a completed worksheet at the end of each lab which will be marked by the lecturer and/or tutor

Assignment: The design assignment will take the form of an individual (or group) assignment based on student research to develop ideas for a biomechatronic device in stages throughout the first half of the semester as their knowledge and understanding of the subject develops. An individual assignment document will be generated and will be graded by the lecturer to determine how well the students have satisfied the requirements specified in the problem statement. This open-ended approach to an assignment allows students more scope to be creative, and throughout the course, creativity and an innovative approach will be encouraged.

Final Exam: Open-book examination. Final assessment will include a number of short-answer questions to assess the student’s knowledge of the basic concepts and an analysis section to test their ability to apply these concepts to solve problems. Note that students will be required to pass the exam, to pass the course.

Detailed information for each assessment can be found on Canvas.

Assessment criteria

Result Name	Mark Range	Description
Matlab tutorial	0-100	grade proportional to correct answers
Weekly Quiz	0-100	grade proportional to correct answers
Lab Activities	0-100	grade proportional to correct answers
Assignment	0-100	grade proportional to how well the criteria were addressed

For more information see guide to grades.

Late submission

In accordance with University policy, these penalties apply when written work is submitted after 11:59pm on the due date:

Deduction of 5% of the maximum mark for each calendar day after the due date.
After ten calendar days late, a mark of zero will be awarded.

This unit has an exception to the standard University policy or supplementary information has been provided by the unit coordinator. This information is displayed below:

A minimum penalty of 5% per day will be applied. With the application of heavier penalties at the discretion of the lecturer

Academic integrity

The Current Student website provides information on academic integrity and the resources available to all students. The University expects students and staff to act ethically and honestly and will treat all allegations of academic integrity breaches seriously.

We use similarity detection software to detect potential instances of plagiarism or other forms of academic integrity breach. If such matches indicate evidence of plagiarism or other forms of academic integrity breaches, your teacher is required to report your work for further investigation.

Use of generative artificial intelligence (AI) and automated writing tools

You may only use generative AI and automated writing tools in assessment tasks if you are permitted to by your unit coordinator. If you do use these tools, you must acknowledge this in your work, either in a footnote or an acknowledgement section. The assessment instructions or unit outline will give guidance of the types of tools that are permitted and how the tools should be used.

Your final submitted work must be your own, original work. You must acknowledge any use of generative AI tools that have been used in the assessment, and any material that forms part of your submission must be appropriately referenced. For guidance on how to acknowledge the use of AI, please refer to the AI in Education Canvas site.

The unapproved use of these tools or unacknowledged use will be considered a breach of the Academic Integrity Policy and penalties may apply.

Studiosity is permitted unless otherwise indicated by the unit coordinator. The use of this service must be acknowledged in your submission as detailed on the Learning Hub’s Canvas page.

Outside assessment tasks, generative AI tools may be used to support your learning. The AI in Education Canvas site contains a number of productive ways that students are using AI to improve their learning.

Learning support

Simple extensions

If you encounter a problem submitting your work on time, you may be able to apply for an extension of five calendar days through a simple extension.  The application process will be different depending on the type of assessment and extensions cannot be granted for some assessment types like exams.

Special consideration

If exceptional circumstances mean you can’t complete an assessment, you need consideration for a longer period of time, or if you have essential commitments which impact your performance in an assessment, you may be eligible for special consideration or special arrangements.

Special consideration applications will not be affected by a simple extension application.

Using AI responsibly

Co-created with students, AI in Education includes lots of helpful examples of how students use generative AI tools to support their learning. It explains how generative AI works, the different tools available and how to use them responsibly and productively.

Weekly schedule

WK	Topic	Learning activity
Week 01	Introduction to the Biomechatronics course, and Introduction to hearing	Lecture (2 hr)
Week 01	Introduction to online/live labs	Practical (3 hr)
Week 02	Hearing implants	Lecture (2 hr)
	Cochlear implant processing	Computer laboratory (1 hr)
	Measure Foundry - Graphs, Filtering and the FFT	Practical (3 hr)
Week 03	Cochlear implants and processing	Lecture (2 hr)
	Cochlear implant processing	Computer laboratory (1 hr)
	Sound propagation online laboratory	Practical (3 hr)
Week 04	Sight and sensory substitution for the blind	Lecture (2 hr)
	Sensory substitution vision to sound	Computer laboratory (1 hr)
	Microphone analysis	Practical (3 hr)
Week 05	Retinal and cortical implants	Lecture (2 hr)
	Sensory substitution vision to sound	Computer laboratory (1 hr)
	Microphone measurements analysis	Practical (3 hr)
Week 06	Introduction to cardiology and pacing	Lecture (2 hr)
	ECG analysis	Computer laboratory (1 hr)
	ECG and cardiac acoustics analysis	Practical (3 hr)
Week 07	Ventricular Assist Devices (VADs)	Lecture (2 hr)
	ECG analysis	Computer laboratory (1 hr)
	MF based Sphygmo measurements and analysis	Practical (3 hr)
Week 08	Sphygmomanometer data analysis	Computer laboratory (1 hr)
Week 08	MF based EMG logging	Practical (3 hr)
Week 09	Total Artificial Hearts (TAHs)	Lecture (2 hr)
	Sphygmomanometer data analysis	Computer laboratory (1 hr)
	MF based EMG signal processing	Practical (3 hr)
Week 10	Introduction to Respiration	Lecture (2 hr)
	Fleisch pneumotachograph data analysis	Computer laboratory (1 hr)
	MF based control of a PTU using serial	Practical (3 hr)
Week 11	Respiratory hardware, negative and positive ventilation	Lecture (2 hr)
	Fleisch pneumotachograph data analysis	Computer laboratory (1 hr)
	MF based serial control of a robot arm	Practical (3 hr)
Week 12	Introduction to limb prosthetics	Lecture (2 hr)
Week 12	MF based EMG control of a robot arm	Practical (3 hr)
Week 13	Control of active and passive prosthetics	Lecture (2 hr)
Week 13	MF based EMG control of a robot arm	Practical (3 hr)

Attendance and class requirements

Attendance at the labs (online or live) is required labs.

Attendance at lectures and tutes (online) is recommended.

Study commitment

Typically, there is a minimum expectation of 1.5-2 hours of student effort per week per credit point for units of study offered over a full semester. For a 6 credit point unit, this equates to roughly 120-150 hours of student effort in total.

Required readings

Brooker, G., Introduction to Biomechatronics, Scitech Publishing, Rayleigh NC. 2012

Learning outcomes

Learning outcomes are what students know, understand and are able to do on completion of a unit of study. They are aligned with the University's graduate qualities and are assessed as part of the curriculum.

Outcomes
Graduate qualities

At the completion of this unit, you should be able to:

LO1. develop a conceptual grasp of the intricate relationship between mind and body which will allow you to evaluate different forms of biofeedback that are used for diagnostics and rehabilitation
LO2. apply specialised engineering skills (mechanical and electrical) to analyse the performance of an active prosthetic device (e.g. prosthetic limb, hearing implant or artificial heart)
LO3. describe the operational principles of a number of implanted and attachable biomechatronic sensors used to monitor and/or stimulate physiological processes including those associated with hearing, seeing, thinking and movement amongst others
LO4. demonstrate an appreciation of the basics of the signal processing required to interpret bioelectrical signals and the ability to develop MATLAB code to perform this analysis.

Graduate qualities

The graduate qualities are the qualities and skills that all University of Sydney graduates must demonstrate on successful completion of an award course. As a future Sydney graduate, the set of qualities have been designed to equip you for the contemporary world.

GQ1	Depth of disciplinary expertise Deep disciplinary expertise is the ability to integrate and rigorously apply knowledge, understanding and skills of a recognised discipline defined by scholarly activity, as well as familiarity with evolving practice of the discipline.
GQ2	Critical thinking and problem solving Critical thinking and problem solving are the questioning of ideas, evidence and assumptions in order to propose and evaluate hypotheses or alternative arguments before formulating a conclusion or a solution to an identified problem.
GQ3	Oral and written communication Effective communication, in both oral and written form, is the clear exchange of meaning in a manner that is appropriate to audience and context.
GQ4	Information and digital literacy Information and digital literacy is the ability to locate, interpret, evaluate, manage, adapt, integrate, create and convey information using appropriate resources, tools and strategies.
GQ5	Inventiveness Generating novel ideas and solutions.
GQ6	Cultural competence Cultural Competence is the ability to actively, ethically, respectfully, and successfully engage across and between cultures. In the Australian context, this includes and celebrates Aboriginal and Torres Strait Islander cultures, knowledge systems, and a mature understanding of contemporary issues.
GQ7	Interdisciplinary effectiveness Interdisciplinary effectiveness is the integration and synthesis of multiple viewpoints and practices, working effectively across disciplinary boundaries.
GQ8	Integrated professional, ethical, and personal identity An integrated professional, ethical and personal identity is understanding the interaction between one’s personal and professional selves in an ethical context.
GQ9	Influence Engaging others in a process, idea or vision.

Outcome map

Learning outcomes	Graduate qualities
Learning outcomes

Responding to student feedback

This section outlines changes made to this unit following staff and student reviews.

This course is the rebadged AMME5790. Only minor changes have been made in transcribing the information.

Additional information

Work, health and safety

Students will need to complete on online tutorial relating to safety in the Mechatronics Lab. Competency will be assessed before access is granted

Details can be found in canvas

Disclaimer

The University reserves the right to amend units of study or no longer offer certain units, including where there are low enrolment numbers.

To help you understand common terms that we use at the University, we offer an online glossary.

Current students

Overview

Overview

Unit details and rules

Teaching staff

Assessment

Assessment

Assessment summary

Assessment criteria

Late submission

Academic integrity

Learning support

Learning support

Simple extensions

Special consideration

Using AI responsibly

Weekly schedule

Weekly schedule

Attendance and class requirements

Study commitment

Required readings

Learning outcomes

Learning outcomes

Graduate qualities

Outcome map

Responding to student feedback

Responding to student feedback

Additional information

Additional information

Work, health and safety

Disclaimer

On this page

Useful links

Media

Student links

About us

Connect

Current students

BMET5790: Introduction to Biomechatronics

Semester 2, 2021 [Normal day] - Remote

Overview

Overview

Unit details and rules

Teaching staff

Assessment

Assessment

Assessment summary

Assessment criteria

Late submission

Academic integrity

Learning support

Learning support

Simple extensions

Special consideration

Using AI responsibly

Weekly schedule

Weekly schedule

Attendance and class requirements

Study commitment

Required readings

Learning outcomes

Learning outcomes

Graduate qualities

Outcome map

Responding to student feedback

Responding to student feedback

Additional information

Additional information

Work, health and safety

Disclaimer

On this page

Useful links

Media

Student links

About us

Connect