BMET1960: Semester 1, 2025

Overview

Biomedical Engineering 1A introduces students to the exciting interdisciplinary field of Biomedical Engineering through a combination of expert lectures, deep-dive tutorials, creative research and design tasks with your peers, and practical hands-on training. Some of the areas you will learn about are: medical imaging; biomaterials and tissue engineering; nanomaterials and nanotechnology; medical devices and sensors; biomechanics and computational biomedical engineering; biomanufacturing; and bionics and neuromodulation. You’ll also be introduced to most of the Biomedical Engineering staff who you’ll encounter throughout the rest of your degree, discovering how they became interested and established in the field. We hope this introductory unit stirs your passion and interest in the exciting field of Biomedical Engineering!

Unit details and rules

Academic unit	Biomedical Engineering
Credit points	6
Prerequisites ?	None
Corequisites ?	None
Prohibitions ?	ENGG1960 or ENGG1800 or CIVL1900 or CHNG1108 or MECH1560 or AERO1560 or MTRX1701 or AMME1960 or ELEC1004 or ELEC1005 or ENVE1001
Assumed knowledge ?	HSC Mathematics Extension 1 (3 Unit)
Available to study abroad and exchange students	No

Teaching staff

Coordinator	Andre Kyme, andre.kyme@sydney.edu.au
Lecturer(s)	Andre Kyme, andre.kyme@sydney.edu.au

Assessment

The census date for this unit availability is 31 March 2025

Details
Criteria

Type	Description	Weight	Due	Length
Online task	Weekly quiz Weekly lecture quiz (released Wks 1,2,4-13; due Mon 12 pm Wks 2,3,5-14) Note: Students must attend the weekly tutorial for the corresponding weekly quiz to be counted	18%	Multiple weeks	n/a
Outcomes assessed:
Skills-based evaluation	Engineering Skills SolidWorks - lab module (10%) Arduino - lab module (10%)	20%	Multiple weeks	2x 3 h (SolidWorks) 2x 2 h (Arduino)
Outcomes assessed:
Online task	Early feedback task Lecture review quiz for early feedback; covers material from Weeks 1-3 #earlyfeedbacktask	2%	Week 04 Due date: 17 Mar 2025 at 12:00	n/a
Outcomes assessed:
Assignment	Assignment 1 Biomedical ethics creative presentation	15%	Week 05 Due date: 30 Mar 2025 at 23:59	n/a
Outcomes assessed:
Assignment	Assignment 2 Design, refine and document a targeted literature search	15%	Week 08 Due date: 16 Apr 2025 at 23:59	n/a
Outcomes assessed:
Assignment	Biomedical Design Task Group presentation in Week 13 tutorial; group report	20%	Week 13 Due date: 30 May 2025 at 23:59	n/a
Outcomes assessed:
Assignment	Tutorial Assessment Participation assessed across semester; 5-page reflective portfolio due Week 13	10%	Week 13 Due date: 01 Jun 2025 at 23:59	Whole semester
Outcomes assessed:
= group assignment ? = AI allowed ? = early feedback task ?

Early feedback task

This unit includes an early feedback task, designed to give you feedback prior to the census date for this unit. Details are provided in the Canvas site and your result will be recorded in your Marks page. It is important that you actively engage with this task so that the University can support you to be successful in this unit.

Assessment summary

Weekly lecture quiz (18%): Students are required to complete an online quiz following each lecture. Each quiz will assess students’ understanding of lecture content. The quiz will be released on Mon 2 pm in Wks 1, 2, 4-13 and students have 1 week to complete the quiz (2 attempts). Students may only use Generative AI for this assessment task as per the BMET1960 Generative AI Policy on Canvas.
Early feedback task (2%): The Week 3 weekly quiz functions as an early feedback task. This quiz will assess students' understanding of the lecture content from Wks 1-3. Students have 1 week to complete the quiz (2 attempts). Students may only use Generative AI for this assessment task as per the BMET1960 Generative AI Policy on Canvas.
Assignment 1 (15%): Group assignment requiring students to develop a creative and persuasive response to an ethically challenging biomedical scenario. Students may only use Generative AI for this assessment task as per the BMET1960 Generative AI Policy on Canvas.
Assignment 2 (15%): Documeted literature search design, refinement and reflection for a targeted area in biomedical engineering. Students may only use Generative AI for this assessment task as per the BMET1960 Generative AI Policy on Canvas.
Biomedical Design Task (20%): Group design task to develop a low-cost solution to a relevant biomedical engineering problem. Students may only use Generative AI for this assessment task as per the BMET1960 Generative AI Policy on Canvas.
Tutorials (10%): Students assessed on holistic participation in tutorials over the semester and a submitted portfolio demonstrating engagement with the course material. Students may only use Generative AI for this assessment task as per the BMET1960 Generative AI Policy on Canvas.
Engineering Skills (20%): Students assessed on skills, quality of work and practical knowledge for SolidWorks (10%) and microcontrollers (10%). Students may only use Generative AI for this assessment task as per the BMET1960 Generative AI Policy on Canvas.

Detailed information for each assessment can be found on Canvas.

Assessment criteria

The University awards common result grades, set out in the Coursework Policy 2021 (Schedule 1).

As a general guide, a high distinction indicates work of an exceptional standard, a distinction a very high standard, a credit a good standard, and a pass an acceptable standard.

Result name	Mark range	Description
High distinction	85 - 100	To be awarded to students who, in their performance in assessment tasks, demonstrate the learning outcomes for the unit at an exceptional standard as defined by grade descriptors or exemplars established by the faculty.
Distinction	75 - 84	To be awarded to students who, in their performance in assessment tasks, demonstrate the learning outcomes for the unit at a very high standard as defined by grade descriptors or exemplars established by the faculty.
Credit	65 - 74	To be awarded to students who, in their performance in assessment tasks, demonstrate the learning outcomes for the unit at a good standard as defined by grade descriptors or exemplars established by the faculty.
Pass	50 - 64	To be awarded to students who, in their performance in assessment tasks, demonstrate the learning outcomes for the unit at an acceptable standard as defined by grade descriptors or exemplars established by the faculty.
Fail	0 - 49	To be awarded to students who, in their performance in assessment tasks, fail to demonstrate the learning outcomes for the unit at an acceptable standard established by the faculty. This grade, with corresponding mark, should also be used in cases where a student fails to achieve a mandated standard in a compulsory assessment, thereby failing to demonstrate the learning outcomes to a satisfactory standard. In such cases the student will receive the mark awarded by the faculty up to a maximum of 49.

For more information see sydney.edu.au/students/guide-to-grades.

For more information see guide to grades.

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

Except for supervised exams or in-semester tests, you may use generative AI and automated writing tools in assessments unless expressly prohibited by your unit coordinator.

For exams and in-semester tests, the use of AI and automated writing tools is not allowed unless expressly permitted in the assessment instructions.

The icons in the assessment table above indicate whether AI is allowed – whether full AI, or only some AI (the latter is referred to as “AI restricted”). If no icon is shown, AI use is not permitted at all for the task. Refer to Canvas for full instructions on assessment tasks for this unit.

Your final submission must be your own, original work. You must acknowledge any use of automated writing tools or generative AI, and any material generated that you include in your final submission must be properly referenced. You may be required to submit generative AI inputs and outputs that you used during your assessment process, or drafts of your original work. Inappropriate use of generative AI is considered a breach of the Academic Integrity Policy and penalties may apply.

The Current Students website provides information on artificial intelligence in assessments. For help on how to correctly acknowledge the use of AI, please refer to the  AI in Education Canvas site.

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.

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.

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.

Support for students

The Support for Students Policy 2023 reflects the University’s commitment to supporting students in their academic journey and making the University safe for students. It is important that you read and understand this policy so that you are familiar with the range of support services available to you and understand how to engage with them.

The University uses email as its primary source of communication with students who need support under the Support for Students Policy 2023. Make sure you check your University email regularly and respond to any communications received from the University.

Learning resources and detailed information about weekly assessment and learning activities can be accessed via Canvas. It is essential that you visit your unit of study Canvas site to ensure you are up to date with all of your tasks.

If you are having difficulties completing your studies, or are feeling unsure about your progress, we are here to help. You can access the support services offered by the University at any time:

Support and Services (including health and wellbeing services, financial support and learning support)
Course planning and administration
Meet with an Academic Adviser

Weekly schedule

WK	Topic	Learning activity
Week 01	Introduction to course; introduction to tomographic medical imaging.	Lecture (2 hr)
Week 02	Introduction to engineering ethics; understanding units as engineers	Lecture (2 hr)
Week 02	Introduction to unit; choosing and evaluating sources; academic integrity; paper discussion (med imaging); BME mindmap; Assignment 1 introduction	Tutorial (2 hr)
Week 03	Anatomy and physiology for engineers.	Lecture (2 hr)
Week 03	Assignment 1 planning	Tutorial (2 hr)
Week 04	Introduction to biomaterials, tissue engineering and mechanobiology.	Lecture (2 hr)
Week 04	Biomaterials and tissue engineering deep-dive; research skills: reading with purpose; Assignment 1 planning	Tutorial (2 hr)
Week 05	Nanomaterials in medicine.	Lecture (2 hr)
Week 05	Research skills: units; nanoparticles deep-dive; Assignment 1 planning	Tutorial (2 hr)
Week 06	Introduction to technology in disability; introduction to bioelectronics	Lecture (2 hr)
Week 06	Research skills: literature reviews; introduction to Assignment 2; Assignment 2 planning	Tutorial (2 hr)
Week 07	Fluid dynamics, microfluidics and their applications in biomedical engineering.	Lecture (2 hr)
Week 07	Introduction to bioelectronics; bioelectronics problem solving; assignment 2 planning	Tutorial (2 hr)
Week 08	Application of biomedical engineering in sleep research and medical devices.	Lecture (2 hr)
Week 08	Biomedical design principles; introduction to the Biomedical Design; research skills: concept drawings; Biomedical Design Task planning	Tutorial (2 hr)
Week 09	Biomechanics and computational biomedical engineering.	Lecture (2 hr)
Week 09	Introduction to fluid dynamics; Biomedical Design Task planning and consultation	Tutorial (2 hr)
Week 10	Introduction to regulatory affairs; introduction to biomanufacturing.	Lecture (2 hr)
Week 10	Introduction to regulatory affairs; regulatory affairs in practice; Biomedical Design Task planning and consultation	Tutorial (2 hr)
Week 11	Introduction to neuromodulation and implantable bionics.	Lecture (2 hr)
Week 11	Introduction to biomechanics; biomechanics in action; Biomedical Design Task planning	Tutorial (2 hr)
Week 12	Introduction to Industry - networking, presentation and Q&A	Lecture (2 hr)
Week 12	Biomedical industry focus; biomedical research focus (PhD Showcase)	Tutorial (2 hr)
Week 13	CANNES Film Festival (Assignment 1 showing + award)	Lecture (2 hr)
Week 13	Biomedical Design Task presentations	Tutorial (2 hr)
Weekly	Private revision	Independent study (3 hr)

Attendance and class requirements

Attendance at lectures is each student's responsibility - marks are not allocated for lecture attendance. However, students are strongly encouraged to attend lectures live and in-person for maximum benefit and engagement, and to best manage their weekly time allocation to the unit.

Since tutorials are key for understanding and applying the course material, helping with assignments, and interacting with peers, in-person attendance at the weekly tutorial is a requirement in order for the corresponding weekly quiz submission to be considered. In addition, 5% of the tutorial assessment is also based on holistic engagement with the tutorial material and activities over the course of the semester – students will not score well in this component if they are not present.

All lectures are recorded and available for viewing after the lecture. No tutorials are recorded.

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

There are no required text books for the course, however various readings will be provided/recommended to students throughout the course (on Canvas) to supplement the tutorials and lectures.

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. generate a concise engineering report
LO2. develop basic skills in engineering drawing, specifications and computer aided design
LO3. develop and articulate a design and development process for a medical device
LO4. develop basic design skills for biomedical engineering, including sustainable design
LO5. gain a working understanding of microcontrollers (Arduino) and how to implement such a device in a simple biomedical project
LO6. understand what Biomedical Engineering is as a discipline and how it relates in a professional context to the medical devices industry and healthcare sector
LO7. understand and relate the key anatomical and physiological systems for medical device applications: (1) support and movement; skeletal system and muscular system; (2) control; nervous system; (3) regulation and maintenance; cardiovascular system
LO8. understand and articulate the interrelationships between different areas of biomedical engineering
LO9. understand the current state-of-the-art in some areas of biomedical engineering
LO10. understand and apply ethical principles and regulations as they relate to biomedical engineering research and industry
LO11. understand some of the key mathematical concepts, tools and tasks in biomedical engineering
LO12. design, describe and justify a rigorous scientific experimental approach to solve a biomedical engineering problem

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.

Several changes will be made for 2025, including: Assignment 2 revamp to focus specifically on literature searching, but still feeding into the Biomedical Design Task; improved clarity of the weekly quiz questions; updated lecture content to include additional research skills (literature reviews, units); updated tutorials to diversify activities and increase student engagement.

Additional information

BMET1960 has a Generative AI Policy outlining how these technologies can and cannot be used in the course. Students must familiarise themselves with this policy and abide by it for all assessment tasks. Each of the Assignments requires submission of a Generative AI Use Statement, regardless of whether these technologies were used or not. Full details are available on our Canvas site.

Disclaimer

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

This unit of study outline was last modified on 12 Feb 2025.

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

Early feedback task

Assessment summary

Assessment criteria

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

Late submission

Academic integrity

Learning support

Learning support

Simple extensions

Special consideration

Using AI responsibly

Support for students

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

Disclaimer

On this page

Useful links

Media

Student links

About us

Connect

Current students

BMET1960: Biomedical Engineering 1A

Semester 1, 2025 [Normal day] - Camperdown/Darlington, Sydney

Overview

Overview

Unit details and rules

Teaching staff

Assessment

Assessment

Early feedback task

Assessment summary

Assessment criteria

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

Late submission

Academic integrity

Learning support

Learning support

Simple extensions

Special consideration

Using AI responsibly

Support for students

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

Disclaimer

On this page

Useful links

Media

Student links

About us

Connect