Master’s in Wearables and Biosignals
Online master's programme of 1,900 hours in wearables and biosignals — ultra-low power, BLE, signal quality and clinical validation. 12 modules covering wearable devices, physiology and biosignals, sensors and electrodes, acquisition electronics, biosignal processing, machine learning, hardware and energy, connectivity, medical device regulation, privacy and usability, and applications, with an assigned technical tutor.
Master’s in Wearables and Biosignals — studying from Australia
Electronics and embedded systems underpin a wide range of Australian industries, including defence, mining automation, medical devices and consumer technology. The telecommunications sector is significant, with ongoing investment in fibre, mobile networks and satellite communications for remote regions. Research organisations such as CSIRO and university groups contribute to advances in sensing, communications and signal processing. Engineers typically work on hardware design, firmware development, testing and certification. Employers include telecommunications carriers, defence contractors, instrumentation companies and product manufacturers.
Fees for Australia: A$14,200 (AUD), with instalments and employer sponsorship available.
Relevant bodies in Australia
Typical roles
Questions from Australia
Is this qualification recognised for electronics engineering in Australia?
SEIUM's qualifications are private and not official state degrees, and they are not accredited by Engineers Australia or the Australian Communications and Media Authority. Recognition for electronics and telecom roles generally depends on accredited degrees, licences and experience. Employers or the relevant body make the final decision.
Which Australian employers hire embedded and telecom engineers?
Australia has telecommunications carriers, defence electronics firms, medical device makers, mining technology companies and IoT developers. Employers mostly assess your hands-on skills, project record and certifications. Ask prospective employers whether they would consider a private online qualification.
Can I study this part-time while working, and how is it supported?
The courses are 100% online and taught in English, so you can study from anywhere in Australia without needing a student visa. Specialist courses take 300 hours, diplomas 800 and master's 1,900. Each student has an assigned technical tutor, fees are payable in instalments, and employer sponsorship may be possible.
Take the controls.
Run a real engineering trade-off from this field. Move the sliders, watch the model react in real time and beat the challenge.
What you will be able to do
Understand the physiological origin of biosignals.
Select sensors and electrodes for wearable devices.
Design low-noise, low-power acquisition electronics.
Process biosignals and extract health indicators.
Apply machine learning to wearable data.
Integrate connectivity and health data platforms.
Apply medical device regulation to development.
Who it's for
- Wearable engineers.
- Biomedical engineers.
- Biosignal processing engineers.
- Medical firmware developers.
- Medical device regulatory specialists.
- Health data scientists.
- Engineering or science graduates looking to move into digital health.
What you'll work with
- Regulation (EU) 2017/745 (EU Medical Device Regulation)
- ISO 13485 (medical device quality management systems)
- ISO 14971 (medical device risk management)
- IEC 62304 (medical device software life cycle)
- IEC 60601-1 (medical electrical equipment safety)
- IEC 60601-2-47 (ambulatory electrocardiographic systems)
- IEC 62366-1 (usability engineering for medical devices)
- ISO 10993-1 (biological evaluation of medical devices)
- MATLAB
- Python NeuroKit2
- Nordic nRF Connect SDK
- KiCad
- Edge Impulse
12 modules
1.1Types of wearables1.2Smart bands and watches1.3Patches and smart textiles1.4Rings and earbuds1.5Medical versus wellness devices1.6Architecture of a wearable1.7Market and trends1.8Clinical use cases1.9Adoption challenges1.10Case study: analysis of a commercial wearable
2.1Origin of biosignals2.2Electrocardiogram2.3Electromyography2.4Electroencephalography2.5Electrodermal activity2.6Photoplethysmography2.7Temperature and respiration2.8Motion and inertia2.9Inter-individual variability2.10Practical: ECG acquisition with dry electrodes
3.1Wet and dry electrodes3.2The skin-electrode interface3.3PPG optical sensors3.4Accelerometers and gyroscopes3.5Bioimpedance sensors3.6Chemical sensors in sweat3.7Flexible sensors3.8Biocompatibility3.9Sensor selection3.10Lab: comparison of dry and wet electrodes
4.1Instrumentation amplifiers4.2Analogue front-ends4.3Common-mode rejection4.4Analogue filtering4.5ADC converters4.6Right-leg drive circuits4.7Low-power design4.8Noise and artefacts4.9Integrated AFE chips4.10Practical: design of an ECG front-end
5.1Digital filtering5.2Removal of motion artefacts5.3QRS detection5.4Heart rate variability5.5SpO2 estimation5.6EEG spectral analysis5.7Muscle activity detection5.8Sensor fusion5.9Real-time processing5.10Lab: Pan-Tompkins algorithm
6.1Activity recognition6.2Arrhythmia detection6.3Sleep monitoring6.4Stress and emotions6.5Fall detection6.6Personalised models6.7On-device inference6.8PhysioNet public datasets6.9Clinical validation6.10Practical: atrial fibrillation detection
7.1Low-power microcontrollers7.2Power management7.3Small batteries7.4Energy harvesting7.5Wireless charging7.6Flexible PCB design7.7Encapsulation and sealing7.8Device ergonomics7.9Manufacturing7.10Lab: energy budget of a wristband
8.1Bluetooth Low Energy8.2GATT health profiles8.3Smartphone synchronisation8.4Cloud platforms8.5HL7 FHIR interoperability8.6Apple HealthKit and Health Connect8.7Data security8.8Firmware updates8.9Backend architecture8.10Practical: BLE transmission of ECG data
9.1Regulation (EU) 2017/7459.2Classification of medical software9.3ISO 13485 management system9.4ISO 14971 risk management9.5IEC 62304 software9.6IEC 60601 electrical safety9.7IEC 62366 usability9.8Clinical evaluation9.9CE marking9.10Case study: regulatory pathway for an ECG patch
10.1Health data and GDPR10.2Informed consent10.3Medical device cybersecurity10.4Bias in health algorithms10.5Darker skin tones and PPG10.6Patient-centred design10.7Adherence to use10.8Accessibility10.9Liability10.10Workshop: ethical assessment of a wearable
11.1Remote patient monitoring11.2Rehabilitation11.3High-performance sport11.4Occupational health and fatigue11.5Older people11.6Chronic diseases11.7Clinical research11.8Brain-computer interfaces11.9Lessons from cases11.10Practical: pilot study proposal
12.1Need and user12.2Biosignal selection12.3Hardware design12.4Firmware and connectivity12.5Processing algorithms12.6Functional prototype12.7Validation with volunteers12.8Regulatory pathway12.9Master's Thesis report12.10Master's Thesis: defence before a panel
How you'll learn
100% online learning on the SEIUM campus, with downloadable material, recorded classes and an assigned technical tutor. There are no fixed timetables: you progress at your own pace within the intake, so you can combine it with work.
Each module combines theory, guided reading of the original standard and applied exercises. The working software is MATLAB, Python NeuroKit2, Nordic nRF Connect SDK, KiCad and Edge Impulse, in free, academic or evaluation versions. Testing is studied through real procedures: biosignal acquisition with volunteers, validation of algorithms against reference equipment, and power consumption and battery life tests. Assessment is continuous by module, plus the final Master's Thesis.
Standards covered: Regulation (EU) 2017/745 (medical devices), ISO 13485, ISO 14971, IEC 62304, IEC 60601-1, IEC 60601-2-47, IEC 62366-1, ISO 10993-1.
Build it end to end
Your final project follows the real engineering workflow, step by step, reviewed by your tutor.
Where this takes you
Requirements
- University degree in engineering, science or architecture, or equivalent demonstrable professional experience.
- Internet connection and a computer able to run the programme software.
- English sufficient to read technical standards.
Ready to start?
Send your application today. Our admissions team replies within 72 hours with your study plan and funding options.
Frequently asked questions
The programme totals 1,900 hours over 12–14 months. You set your own pace within each intake, and your tutor helps you plan the workload around your job.
You work with MATLAB, Python NeuroKit2, Nordic nRF Connect SDK, KiCad and Edge Impulse, using free, academic or evaluation versions. Your tutor indicates the free alternative wherever one exists.
A SEIUM Institute diploma, awarded on passing the continuous assessment and the Master's Thesis. It is SEIUM's own qualification, not an official state degree; its recognition depends on the programme completed and the regulations of each country.
Yes. Modules passed in a course or postgraduate diploma in the same area are recognised in the higher programme. Ask about the recognition policy when you enrol.
A degree in engineering, science or architecture (or equivalent professional experience), a computer able to run the software and English sufficient to read technical standards.
Start dates are set by SEIUM's faculty for each intake. Our admissions team will confirm the next available date when you apply.
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