Unit outline_

BMET1960: Biomedical Engineering 1A

Semester 1, 2026 [Normal day] - Camperdown/Darlington, Sydney

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
The census date for this unit availability is 31 March 2026
Type Description Weight Due Length Use of AI
In-person practical, skills, or performance task or test Tutorial engagement and contribution
Engagement and contribution assessed across the semester
10% Multiple weeks Whole semester AI prohibited
Outcomes assessed: LO1 LO2 LO8 LO5 LO6 LO7 LO9
In-person practical, skills, or performance task or test Solid Works lab engagement
Solid Works lab engagement
2.5% Multiple weeks 2x 3-hr labs AI prohibited
Outcomes assessed: LO2
In-person practical, skills, or performance task or test Arduino lab engagement
Arduino lab engagement
2.5% Multiple weeks 2x 3-hr labs AI prohibited
Outcomes assessed: LO4
Practical skill SolidWorks Lab
SolidWorks computer aided design lab module work
7.5% Multiple weeks 2x 3 hr labs AI allowed
Outcomes assessed: LO2
Practical skill group assignment Arduino Lab
Arduino microcontroller lab module (10%)
7.5% Multiple weeks 2x 3-hr labs AI allowed
Outcomes assessed: LO4
Out-of-class quiz Weekly quiz
Weekly lecture quiz (released Wks 1,2,4-12; due Mon 12 pm Wks 2,3,5-13) Note: Students must attend the weekly tutorial for the corresponding weekly quiz to be counted
13% Multiple weeks n/a AI allowed
Outcomes assessed: LO5 LO6 LO7 LO8 LO9
Out-of-class quiz Early Feedback Task Early feedback task
Lecture review quiz for early feedback; covers material from Weeks 1-3
2% Week 04
Due date: 16 Mar 2026 at 12:00
n/a AI allowed
Outcomes assessed: LO5 LO6 LO7 LO8 LO9
Creative work group assignment Assignment 1
Biomedical ethics creative presentation
15% Week 05
Due date: 29 Mar 2026 at 23:59
n/a AI allowed
Outcomes assessed: LO1 LO5 LO8
Written work hurdle task Assignment 2
Design, refine and document a targeted literature search
5% Week 07
Due date: 19 Apr 2026 at 23:59
n/a AI allowed
Outcomes assessed: LO1 LO6 LO7
In-person written or creative task Assignment 2 in-class response
A closed-book, in-class response based on the work done for Assignment 2. This test will be run in your timetabled tutorial class.
10% Week 08 40 min AI prohibited
Outcomes assessed: LO7
Q&A following presentation, submission or placement Biomedical Design Task Presentation
Biomedical Design Task presentation and Q&A
5% Week 13 Week 13 tutorial AI prohibited
Outcomes assessed: LO3 LO10
Written work group assignment Biomedical Design Task
Group design project and report
15% Week 13
Due date: 29 May 2026 at 23:59
n/a AI allowed
Outcomes assessed: LO1 LO2 LO3 LO9 LO10
Portfolio or journal Tutorial assessment (Reflection)
Engagement assessed across the semester via a 5-page reflective portfolio due Week 13
5% Week 13
Due date: 31 May 2026 at 23:59
n/a AI allowed
Outcomes assessed: LO5 LO6
hurdle task = hurdle task ?
group assignment = group assignment ?
early feedback task = 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).
  • 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).
  • Assignment 1 (15%): Group assignment requiring students to develop a creative and persuasive response to an ethically challenging biomedical scenario.
  • Assignment 2 (15%): Documeted literature search design, refinement and reflection for a targeted area in biomedical engineering.
  • Biomedical Design Task (20%): Group design task to develop a low-cost solution to a relevant biomedical engineering problem. This task is split into 15% Open and 5% Secure, where the secure component is based on the live presentation and Q&A.
  • Tutorials (10%): Students assessed on holistic participation in tutorials over the semester (5%, Secure) plus a submitted portfolio demonstrating engagement with the course material (5%, Open).
  • Engineering Skills (20%): Students assessed on skills, quality of work and practical knowledge for SolidWorks (10%) and microcontrollers (10%).

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)

You can use generative AI tools for open assessments. Restrictions on AI use apply to secure, supervised assessments used to confirm if students have met specific learning outcomes.

Refer to the assessment table above to see if AI is allowed, for assessments in this unit and check Canvas for full instructions on assessment tasks and AI use.

If you use AI, you must always acknowledge it. Misusing AI may lead to a breach of the Academic Integrity Policy.

Visit the Current Students website for more information on AI in assessments, including details on how to acknowledge its use.

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 University expects students to act ethically and honestly and will treat all allegations of academic integrity breaches seriously.

Our website provides information on academic integrity and the resources available to all students. This includes advice on how to avoid common breaches of academic integrity. Ensure that you have completed the Academic Honesty Education Module (AHEM) which is mandatory for all commencing coursework students

Penalties for serious breaches can significantly impact your studies and your career after graduation. It is important that you speak with your unit coordinator if you need help with completing assessments.

Visit the Current Students website for more information on AI in assessments, including details on how to acknowledge its use.

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 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. 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

WK Topic Learning activity Learning outcomes
Week 01 Introduction to course; introduction to tomographic medical imaging. Lecture (2 hr) LO5 LO6 LO7 LO9
Week 02 Introduction to engineering ethics; understanding units as engineers Lecture (2 hr) LO5 LO8 LO9
Introduction to unit; choosing and evaluating sources; academic integrity; paper discussion (med imaging); BME mindmap; Assignment 1 introduction Tutorial (2 hr) LO5 LO6 LO7 LO8 LO9
Week 03 Anatomy and physiology for engineers. Lecture (2 hr) LO5 LO6 LO7 LO9
Assignment 1 planning Tutorial (2 hr) LO5 LO8
Week 04 Introduction to biomaterials, tissue engineering and mechanobiology. Lecture (2 hr) LO5 LO6 LO7 LO9
Biomaterials and tissue engineering deep-dive; research skills: reading with purpose; Assignment 1 planning Tutorial (2 hr) LO5 LO6 LO7 LO9
Week 05 Nanomaterials in medicine. Lecture (2 hr) LO5 LO6 LO7 LO9
Research skills: units; nanoparticles deep-dive; Assignment 1 planning Tutorial (2 hr) LO1 LO5 LO6 LO7 LO9
Week 06 Introduction to technology in disability; introduction to bioelectronics Lecture (2 hr) LO5 LO6 LO7 LO9
Research skills: literature reviews; introduction to Assignment 2; Assignment 2 planning Tutorial (2 hr) LO1 LO5 LO7 LO9 LO10
Week 07 Fluid dynamics, microfluidics and their applications in biomedical engineering. Lecture (2 hr) LO5 LO6 LO7 LO9
Introduction to bioelectronics; bioelectronics problem solving; assignment 2 planning Tutorial (2 hr) LO1 LO5 LO7 LO9 LO10
Week 08 Application of biomedical engineering in sleep research and medical devices. Lecture (2 hr) LO5 LO6 LO7 LO9
Biomedical design principles; introduction to the Biomedical Design; research skills: concept drawings; Biomedical Design Task planning Tutorial (2 hr) LO1 LO2 LO3 LO4 LO6 LO7 LO9 LO10
Week 09 Biomechanics and computational biomedical engineering. Lecture (2 hr) LO5 LO6 LO7 LO9
Introduction to fluid dynamics; Biomedical Design Task planning and consultation Tutorial (2 hr) LO1 LO2 LO3 LO4 LO6 LO7 LO9 LO10
Week 10 Introduction to regulatory affairs; introduction to biomanufacturing. Lecture (2 hr) LO5 LO6 LO7 LO8 LO9
Introduction to regulatory affairs; regulatory affairs in practice; Biomedical Design Task planning and consultation Tutorial (2 hr) LO1 LO2 LO3 LO4 LO6 LO7 LO9 LO10
Week 11 Introduction to neuromodulation and implantable bionics. Lecture (2 hr) LO5 LO6 LO7 LO9
Introduction to biomechanics; biomechanics in action; Biomedical Design Task planning Tutorial (2 hr) LO1 LO2 LO3 LO4 LO6 LO7 LO9 LO10
Week 12 Introduction to Industry - networking, presentation and Q&A Lecture (2 hr) LO5 LO6 LO7
Biomedical industry focus; biomedical research focus (PhD Showcase) Tutorial (2 hr) LO5 LO7
Week 13 CANNES Film Festival (Assignment 1 showing + award) Lecture (2 hr) LO5 LO8
Biomedical Design Task presentations Tutorial (2 hr) LO1 LO3 LO10
Weekly Private revision Self-directed learning (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 vital for understanding, reinforcing 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 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.

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. gain a working understanding of microcontrollers (Arduino) and how to implement such a device in a simple biomedical project
  • LO5. understand and articulate what Biomedical Engineering is as a discipline, the interrelationships between different fields of biomedical engineering, and how it relates in a professional context to the medical devices industry and healthcare sector
  • LO6. 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
  • LO7. understand the current state-of-the-art in some areas of biomedical engineering
  • LO8. understand and apply ethical principles and regulations as they relate to biomedical engineering research and industry
  • LO9. understand some of the key mathematical concepts, tools and tasks in biomedical engineering
  • LO10. 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
GQ1 GQ2 GQ3 GQ4 GQ5 GQ6 GQ7 GQ8 GQ9

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

For 2026 we will make the following updates: - continue refining the assessment profile to ensure it reinforces the key foundational learning outcomes required for the rest of the BME degree - extend the Arduino labs to include a longer introduction and more time to explore and investigate the hardware - refresh the SolidWorks labs and provide additional tutor support in the classes - check and update tutorial activities to enhance engagement and alignment with the course content and learning outcomes

BMET1960 has a Generative AI Guidelines outlining how AI technologies can be used in the course. These guidelines are in addition to the University-wide policies on responsible AI use in degree programs. Students must familiarise themselves with the University policy and the BMET1960 guidelines. Each of the main BMET1960 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

Important: the University of Sydney regularly reviews units of study and reserves the right to change the units of study available annually. To stay up to date on available study options, including unit of study details and availability, refer to the relevant handbook.

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