Outline

Overview

This course will equip students with the skills to extract or reveal useful information from biomedical sensor systems and use this information to design automated processing systems using signal processing. The student will gain a set of mathematical tools that will enable a deeper understanding of how biomedical devices and physiological systems work. The unit has a strong practical focus

Unit details and rules

Academic unit	Biomedical Engineering
Credit points	6
Prerequisites ?	(ENGG1810 or INFO1110 or INFO1910) and BMET2922
Corequisites ?	None
Prohibitions ?	BMET9997
Assumed knowledge ?	BMET2901 and BMET2925
Available to study abroad and exchange students	No

Teaching staff

Coordinator	Philip de Chazal, philip.dechazal@sydney.edu.au
Lecturer(s)	Wei Chen, wei.chenbme@sydney.edu.au

Assessment

The census date for this unit availability is 31 March 2025

Details
Criteria

Type	Description	Weight	Due	Length
Assignment	Major project report Individual Report on Major Project	35%	Formal exam period Due date: 13 Jun 2025 at 23:59	15-20 pages
Outcomes assessed:
Assignment	Report on Lab 1 Report on laboratory 1	10%	Week 04 Due date: 21 Mar 2025 at 23:59	10 pages
Outcomes assessed:
Assignment	Report on Lab 2 Report on laboratory 2	10%	Week 05 Due date: 28 Mar 2025 at 23:59	10 pages
Outcomes assessed:
Assignment	Report on Company Visit Report on company visit	10%	Week 07 Due date: 11 Apr 2025 at 23:59	3 pages
Outcomes assessed:
Tutorial quiz	Mid-semester test Assessment of course material weeks 1-9.	25%	Week 10 Due date: 05 May 2025 at 10:00	80 minutes
Outcomes assessed:
Presentation	Presentation on Major project Presentation on Major Project (powerpoint)	10%	Week 13 Due date: 26 May 2025 at 10:00	15 minutes
Outcomes assessed:
= group assignment ? = AI allowed ?

Assessment summary

Lab 1 report: Written report on individual contribution to the laboratory project
Mid term test, In class 80 minute assessment of course material in weeks 1-9 testing your understanding of concepts and application. The testwill be a mixture of multiple choice and free answer questions.
Major Project report, A 15-20 page report detailing your contribution to the major project.
Project presentation: A 15 minute powerpoint presentation describing the approaches and outcomes of the major project. There is one presentation per group

Assessment criteria

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

Result code	Result name	Mark range	Description
HD	High distinction	85 - 100	Awarded when you demonstrate the learning outcomes for the unit at an exceptional standard, as defined by grade descriptors or exemplars outlined by your faculty or school.
DI	Distinction	75 - 84	Awarded when you demonstrate the learning outcomes for the unit at a very high standard, as defined by grade descriptors or exemplars outlined by your faculty or school.
CR	Credit	65 - 74	Awarded when you demonstrate the learning outcomes for the unit at a good standard, as defined by grade descriptors or exemplars outlined by your faculty or school.
PS	Pass	50 - 64	Awarded when you demonstrate the learning outcomes for the unit at an acceptable standard, as defined by grade descriptors or exemplars outlined by your faculty or school.
FA	Fail	0 - 49	When you don’t meet the learning outcomes of the unit to a satisfactory standard.
AF	Absent fail	0 - 49	When you haven’t completed all assessment tasks or met the attendance requirements.
CN	Cancelled	No mark	When your enrolment has been cancelled.
DC	Discontinued not to count as failure	No mark or 0	When you discontinue a unit under special circumstances (outlined in clause 92 of the Coursework Policy), after the relevant census date.
DF	Discontinue – fail	No mark or 0	When you discontinue a unit after the relevant census date but before the DF deadline, and you have not been granted a discontinuation under special circumstances.
FR	Failed requirements	No mark	When you don’t meet the learning outcomes to a satisfactory standard, for units which are marked as either Satisfied requirements or Failed requirements.
SR	Satisfied requirements	No mark	When you meet the learning outcomes to a satisfactory standard, for units which are marked as either Satisfied requirements or Failed requirements.
WD	Withdrawn	No mark	When you discontinue a unit before the relevant census date. WD grades do not appear on your academic transcript.
NE	Not examinable	No mark or 0	When you have exhausted your options to sit replacement exams or replacement assessment tests. An NE does not count as a fail on your transcript and won’t be included in your weighted average mark (WAM).

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 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

Weekly schedule

WK	Topic	Learning activity
Week 01	Introduction and Electrocardiogram (ECG)	Lecture (2 hr)
Week 02	Ballistocardiogram (BCG), Heart rate and heart rate variability (HRV), Electromyogram (EMG)	Lecture (2 hr)
Week 02	Laboratory: Physiological signal measurement	Practical (3 hr)
Week 03	Electroencephalogram (EEG) and Electrooculogram (EOG)	Lecture (2 hr)
Week 03	Laboratory: Physiological signal measurement	Practical (3 hr)
Week 04	Photoplethysmography (PPG) and functional Near Infrared Spectroscopy (fNIRS)	Lecture (2 hr)
Week 05	Activity and System Design	Lecture (2 hr)
Week 06	Sleep staging, Sleep disease monitoring, Sleep regulation	Lecture (2 hr)
Week 06	Company Visit (Resmed)	Field trip (3 hr)
Week 07	Digital signal concepts 1: Applications, sampling filters	Lecture (2 hr)
Week 07	Major project: Designing a QRS detection scheme	Practical (3 hr)
Week 08	Digital signal concepts 2: Domains, Discrete Fourier Transform, Spectral estimation	Lecture (2 hr)
Week 08	Major project: Designing a QRS detection scheme	Practical (3 hr)
Week 09	ECG signal processing: QRS detection, Heart rate variability	Lecture (2 hr)
Week 09	Major project: Designing a QRS detection scheme	Practical (3 hr)
Week 10	ECG signal processing II: ECG derived respiration, Cardiopulmonary coupling	Lecture (2 hr)
Week 10	Major project: Designing a QRS detection scheme	Practical (3 hr)
Week 11	Oximetry signal processing: Desaturation, time domain measures, frequency domain measures, Non-linear measures	Lecture (2 hr)
Week 11	Major project: Designing a QRS detection scheme	Practical (3 hr)
Week 12	EEG signal processing: Human sleep cycle, sleep staging, Spectral estimation and spectrum decomposition, Sleep spindle detection, Noise sources	Lecture (2 hr)
Week 12	Major project: Designing a QRS detection scheme	Practical (3 hr)
Week 13	Major project presentations	Lecture (2 hr)

Attendance and class requirements

It is the responsibility of students enrolled in units of study to attend scheduled classes, even if the classes are not directly tied to assessments. This unit of study requires that students must not have more than three unexplained absences from scheduled lectures, and must not have more than three unexplained absences from scheduled practicals. Live, in-person participation in these sessions is important for achieving the unit of study learning outcomes. Students who do not satisfy attendance and participation requirements may be deemed not to have completed this unit of study, according to Coursework Policy 2021 Clause 68.

The University attendance policy can be found here (see clause 68): https://www.sydney.edu.au/policies/showdoc.aspx?recnum=PDOC2014/378&RendNum=0

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.

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.

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

LO1. Demonstrate understanding on how the interdisciplinary approach from engineering, biology and medical viewpoints can be combined into sensor and signal processing applications to improve outcomes in healthcare.
LO2. Write reports to communicate technical and often complex material in clear and concise terms for a specific target audience.
LO3. Demonstrate understanding of how sensor and signal processing tools can be used to address important problems in healthcare and biology.
LO4. Be able to select appropriate combinations of signal processing methods on biological signals to achieve required outcomes
LO5. Be able to explain what physiological signals are and how they are measured, and demonstrate proficiency in using state-of-the-art tools and methods to analyse sensing data.
LO6. Present written reports and make presentations to communicate technical and often complex material in clear and concise terms for a specific target audience.

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

Alignment with Competency standards

Outcomes	Competency standards
	Engineers Australia Curriculum Performance Indicators - 1.1. Developing underpinning capabilities in mathematics, physical, life and information sciences and engineering sciences, as appropriate to the designated field of practice. 2.2. Application of enabling skills and knowledge to problem solution in these technical domains. 4.5. An ability to undertake problem solving, design and project work within a broad contextual framework accommodating social, cultural, ethical, legal, political, economic and environmental responsibilities as well as within the principles of sustainable development and health and safety imperatives. 5.5. Skills in the development and application of mathematical, physical and conceptual models, understanding of applicability and shortcomings. 5.8. Skills in recognising unsuccessful outcomes, sources of error, diagnosis, fault-finding and re-engineering.
	Engineers Australia Curriculum Performance Indicators - 3.1. An ability to communicate with the engineering team and the community at large. 3.2. Information literacy and the ability to manage information and documentation. 5.9. Skills in documenting results, analysing credibility of outcomes, critical reflection, developing robust conclusions, reporting outcomes.
	Engineers Australia Curriculum Performance Indicators - 2.2. Application of enabling skills and knowledge to problem solution in these technical domains. 2.4. Advanced knowledge and capability development in one or more specialist areas through engagement with: (a) specific body of knowledge and emerging developments and (b) problems and situations of significant technical complexity. 3.3. Creativity and innovation. 4.3. Proficiency in the engineering design of components, systems and/or processes in accordance with specified and agreed performance criteria. 5.3. Skills in the selection and characterisation of engineering systems, devices, components and materials. 5.5. Skills in the development and application of mathematical, physical and conceptual models, understanding of applicability and shortcomings.
	Engineers Australia Curriculum Performance Indicators - 2.4. Advanced knowledge and capability development in one or more specialist areas through engagement with: (a) specific body of knowledge and emerging developments and (b) problems and situations of significant technical complexity. 4.1. Advanced level skills in the structured solution of complex and often ill defined problems. 5.5. Skills in the development and application of mathematical, physical and conceptual models, understanding of applicability and shortcomings. 5.8. Skills in recognising unsuccessful outcomes, sources of error, diagnosis, fault-finding and re-engineering. 5.9. Skills in documenting results, analysing credibility of outcomes, critical reflection, developing robust conclusions, reporting outcomes.
	Engineers Australia Curriculum Performance Indicators - 2.4. Advanced knowledge and capability development in one or more specialist areas through engagement with: (a) specific body of knowledge and emerging developments and (b) problems and situations of significant technical complexity. 3.1. An ability to communicate with the engineering team and the community at large. 3.2. Information literacy and the ability to manage information and documentation. 5.9. Skills in documenting results, analysing credibility of outcomes, critical reflection, developing robust conclusions, reporting outcomes.
	Engineers Australia Curriculum Performance Indicators - 3.1. An ability to communicate with the engineering team and the community at large. 3.2. Information literacy and the ability to manage information and documentation. 3.3. Creativity and innovation. 3.4. An understanding of and commitment to ethical and professional responsibilities. 3.6. An ability to function as an individual and as a team leader and member in multi-disciplinary and multi-cultural teams. 5.4. Skills in the selection and application of appropriate engineering resources tools and techniques, appreciation of accuracy and limitations;.

Responding to student feedback

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

This is the first time this unit has been offered

Additional information

Site visit guidelines

Students to make their own way to ResMed campus in Bella Vista. Students to wear enclosed shoes

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

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

Learning outcomes

Learning outcomes

Graduate qualities

Outcome map

Alignment with Competency standards

Responding to student feedback

Responding to student feedback

Additional information

Additional information

Site visit guidelines

Disclaimer

On this page

Useful links

BMET3997: Biological Digital Signal Analysis

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

Overview

Overview

Unit details and rules

Teaching staff

Assessment

Assessment

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

Learning outcomes

Learning outcomes

Graduate qualities

Outcome map

Alignment with Competency standards

Responding to student feedback

Responding to student feedback

Additional information

Additional information

Site visit guidelines

Disclaimer

On this page

Useful links