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Unit of study_

BMET9922: Computational Analysis for Biomedical Signals

Semester 2, 2022 [Normal day] - Camperdown/Darlington, Sydney

Biomedical engineering is being deeply reshaped by the advancements in computational tools and the utilisation of rich data. This unit will explore the processes involved in designing and building systems to perform computational analysis on biological signals, using microcontrollers and desktop or server computing. The main teaching activities will focus on the theory and practical skills for data capture, cleaning, communication, storage, and analytics. The purpose is to ensure that students develop the skills necessary to design systems that can be used for monitoring of patients, where the data can be used for analytics, e.g. prediction of an adverse event. This is relevant to a number of applications in modern healthcare such as continuous and remote monitoring devices. The unit will develop core skills in programming, solution design, sensor interfacing, and data analysis.

Unit details and rules

Unit code BMET9922
Academic unit Biomedical Engineering
Credit points 6
Assumed knowledge

Knowledge of basic biomedical engineering principles (BMET1960) and basic programming (ENGG1801 or ENGG1810 or ENGG9810 or INFO1110)

Available to study abroad and exchange students


Teaching staff

Coordinator Omid Kavehei,
Demonstrator(s) Daniel Babekuhl,
Lecturer(s) Young No,
Type Description Weight Due Length
Small continuous assessment Lab activities
Completion of prescribed lab activities during scheduled lab sessions
10% Multiple weeks During lab sessions
Outcomes assessed: LO1 LO7 LO5 LO4 LO3 LO2
Tutorial quiz Fortnightly mini-quizzes
Fortnightly mini-quizzes to reinforce lecture content
10% Multiple weeks ~20 minutes
Outcomes assessed: LO1 LO8 LO6
Assignment Major project - System Design Report Part 1
Written system design report in the lead up to major project
10% Week 04
Due date: 26 Aug 2022 at 23:59
Outcomes assessed: LO1 LO2 LO3 LO4 LO5 LO7
Assignment Major project - System Design Report Part 2
Written system design report in the lead up to major project
15% Week 07
Due date: 16 Sep 2022 at 23:59
Outcomes assessed: LO1 LO3 LO4 LO5 LO7 LO2
Assignment Biomedical Software Report
A short report on a biomedical software application example
10% Week 09
Due date: 07 Oct 2022 at 23:59
2 pages
Outcomes assessed: LO7 LO9
Presentation Live demonstration
Live demonstration of developed software during lab sessions
10% Week 12 ~3 minutes
Outcomes assessed: LO1 LO7 LO5 LO4 LO3
Assignment group assignment Major project - Project Report
Major project report
35% Week 13 n/a
Outcomes assessed: LO1 LO2 LO3 LO4 LO5 LO7
group assignment = group assignment ?

Assessment summary

“Keeping you on your toes” assessments

  • Lab activities: Students will be graded based on their level of completion of the prescribed weekly lab activities
  • Fortnightly mini-quizzes: Students will demonstrate understanding of the lecture content via fortnightly mini-quizzes. These can be completed anytime during the fortnight; a time limit (~20 mins) will be applied upon quiz start


Major Project

Students will develop a basic hardware/software setup using optical electrocardiography. Based on this major project, three deliverables are expected as outcomes:

  • Design report: Split into two parts for checkpointing purposes; total 25%
  • Live demonstration + brief commentary: Students will be asked to demonstrate their project and provide commentary during Week 12 lab sessions. These are anticipated to be ~3 mins each, worth 10%.
  • Major project report: A final report to outline and discuss the development process of the final product. 35% of coursework mark
  • Short research report (BMET9922 only): A short research report over the midsem break on a current biomedical software example


Assessment criteria


The University awards common result grades, set out in the Coursework Policy 2014 (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


High distinction

85 - 100



75 - 84



65 - 74



50 - 64



0 - 49

When you don’t meet the learning outcomes of the unit to a satisfactory standard.

For more information see


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:

The standard university policy regarding late submission will apply, unless noted otherwise on Canvas.

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.

You may only use artificial intelligence and writing assistance tools in assessment tasks if you are permitted to by your unit coordinator, and if you do use them, you must also acknowledge this in your work, either in a footnote or an acknowledgement section.

Studiosity is permitted for postgraduate units unless otherwise indicated by the unit coordinator. The use of this service must be acknowledged in your submission.

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.

WK Topic Learning activity Learning outcomes
Week 01 Unit overview + Python revisited Lecture and tutorial (2 hr) LO1 LO2
Python introduction Practical (3 hr) LO1 LO3
Week 02 Microcontroller fundamentals Lecture and tutorial (2 hr) LO1 LO2 LO3 LO4
Microcontroller Familiarisation - ESP32 Practical (3 hr) LO1 LO4
Week 03 Python control flow + Project briefing Lecture and tutorial (2 hr) LO1 LO2 LO3
Microcontroller Sensor Interfacing Practical (3 hr) LO1 LO4
Week 04 Biomedical Sensors and Signal Processing Lecture and tutorial (2 hr) LO1 LO3 LO4
Microcontroller Signal Processing and Host Data Visualisation Practical (3 hr) LO1 LO3
Week 05 Python Classes and Data Communication Lecture and tutorial (2 hr) LO1 LO3 LO4 LO5
Microcontroller Communications Practical (3 hr) LO1 LO3 LO4
Week 06 Python Dictionaries and pysimpleGUI Lecture and tutorial (2 hr) LO1 LO3 LO5
Graphic User Interfaces Practical (3 hr) LO1 LO2 LO3 LO4 LO5
Week 07 Data acquisition and storage Lecture and tutorial (2 hr) LO3 LO4
Catchup Lab Practical (3 hr) LO1 LO2 LO3 LO4 LO5
Week 08 Signal Power and Energy; System design and test Practical (3 hr) LO1 LO2 LO3 LO4 LO5
Week 09 C Functions, multiple files and static variables Lecture and tutorial (1 hr) LO1 LO3 LO4 LO5
Fast Fourier transform of datasets; System design and test Practical (3 hr) LO1 LO2 LO3 LO4 LO5
Week 10 Software development methodologies Lecture and tutorial (2 hr) LO1 LO6
System design and test Practical (3 hr) LO1 LO2 LO3 LO4 LO5
Week 11 Biomedical Software Standards Lecture and tutorial (2 hr) LO1 LO6
System design and test Practical (3 hr) LO1 LO2 LO3 LO4 LO5
Week 12 Case Study Lecture and tutorial (2 hr) LO1 LO2 LO3 LO4 LO5 LO6
System demonstration Practical (3 hr) LO7
Week 13 Course review Lecture and tutorial (2 hr) LO1 LO2 LO3 LO4

Attendance and class requirements

Opportunities for discussion of course concepts are provided in lectures and labs. Students are expected to attend a minimum of 90% of all timetabled activities.

See the Faculty resolutions for more information:

Attendance in labs (practical sessions) is required and will be assessed.


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 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. Understand and communicate the principles of operation of computational systems in a biomedical device context.
  • LO2. Produce a design plan for capturing and analysing biomedical signals
  • LO3. Program solutions for biomedical signal processing tasks using existing software packages and libraries.
  • LO4. Integrate bio-electronic sensors with micro-controllers to capture biological signals
  • LO5. Apply computational tools to capture, store, transmit, analyse, and display biomedical signal data
  • LO6. Understand the need for appropriate documentation and reference to standards in the development of biomedical software tools
  • LO7. Work individually or in small groups to carry out a prescribed engineering design task and present the outcomes in an oral, written or video format
  • LO8. Apply engineering principles to answer questions relating to biomedical software systems in a quiz format.
  • LO9. Analyse the success of biomedical software currently used in the market

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

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

Course has been adapted based on last year's comments.

Work, health and safety

The course assumes knowledge of “c” and python. In 2021 additional lecture and lab content has been added to provide python knowledge. From 2022 python knowledge will be assumed from ENGG1810. “c” and some micrcontroller knowledge is assumed from BMET1960.



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

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