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Postgraduate DiplomaElectronics, Embedded Systems & Telecom Applications open

Postgraduate Diploma in Bio-signal Acquisition/Quality

Online 800-hour Postgraduate Diploma in Bio-signal Acquisition/Quality. 8 modules covering IEC 60601-1:2005+A2:2020, IEC 60601-2-25:2011 and MATLAB Signal Processing Toolbox. Assigned tutor and open enrolment.

Duration800 h
ModeOnline
AwardSEIUM Institute diploma
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Learning outcomes

What you will be able to do

01

Characterise the main bio-signals and their artefacts.

02

Select electrodes and sensors according to the application.

03

Design low-noise analogue front-ends.

04

Configure synchronised digital acquisition systems.

05

Apply filtering techniques and event detection.

06

Assess signal quality using objective indices.

07

Meet the safety requirements of IEC 60601.

Profile

Who it's for

  • Biomedical engineer who wants to specialise in Bio-signal Acquisition/Quality.
  • Medical electronics designer who wants to specialise in Bio-signal Acquisition/Quality.
  • Signal processing engineer who wants to specialise in Bio-signal Acquisition/Quality.
  • Wearable device engineer who wants to specialise in Bio-signal Acquisition/Quality.
  • Medical device validation engineer who wants to specialise in Bio-signal Acquisition/Quality.
  • Neurotechnology researcher who wants to specialise in Bio-signal Acquisition/Quality.
  • Engineering or science graduates seeking to enter healthcare technology.
Standards & tools

What you'll work with

  • IEC 60601-1:2005+A2:2020
  • IEC 60601-2-25:2011
  • IEC 60601-1-2:2014+A1:2020
  • ISO 14971:2019
  • IEC 60601-2-47:2012
  • ISO 10993-1:2018
  • Regulation (EU) 2017/745 (MDR)
Syllabus

8 modules · 800 h

  1. 1.1Bioelectricity and action potentials
  2. 1.2ECG signal and leads
  3. 1.3EEG signal and brain rhythms
  4. 1.4Surface EMG signal
  5. 1.5PPG photoplethysmography and oximetry
  6. 1.6Respiration signals and bioimpedance
  7. 1.7Typical amplitudes and bandwidths
  8. 1.8Physiological and motion artefacts
  9. 1.9Electrode-skin interface and its model
  10. 1.10Workshop: characterisation of an ECG recording
  1. 2.1Wet Ag/AgCl electrodes
  2. 2.2Dry and textile electrodes
  3. 2.3Contact impedance and its measurement
  4. 2.4Optical sensors for PPG
  5. 2.5Accelerometers and inertial sensors
  6. 2.6Body temperature sensors
  7. 2.7Biocompatibility under ISO 10993
  8. 2.8Electrode placement and skin preparation
  9. 2.9Electrode ageing and drift
  10. 2.10Practice: electrode-skin impedance measurement
  1. 3.1Instrumentation amplifiers
  2. 3.2Common-mode rejection CMRR
  3. 3.3Driven right leg
  4. 3.4Antialiasing filters of appropriate order
  5. 3.5Integrated front-ends ADS1298 and AD8232
  6. 3.6Input noise and its budget
  7. 3.7Defibrillation protection
  8. 3.8Isolation and leakage currents
  9. 3.9PCB design for microvolt signals
  10. 3.10Laboratory: single-lead ECG front-end
  1. 4.1Sampling frequency and the Nyquist theorem
  2. 4.2High-resolution sigma-delta ADCs
  3. 4.3Multichannel synchronisation of channels
  4. 4.4Timestamps and clocks
  5. 4.5Wireless transmission of bio-signals
  6. 4.6EDF and WFDB formats
  7. 4.7Lossless compression
  8. 4.8Storage and metadata
  9. 4.9Latency in continuous monitoring
  10. 4.10Practice: multichannel acquisition with OpenBCI
  1. 5.1Filtering mains interference
  2. 5.2Removal of baseline drift
  3. 5.3Adaptive filters and reference
  4. 5.4Wavelet transform for denoising
  5. 5.5QRS detection with Pan-Tompkins
  6. 5.6EEG spectral analysis
  7. 5.7EMG envelope extraction
  8. 5.8Independent component analysis
  9. 5.9Real-time processing on embedded systems
  10. 5.10Laboratory: QRS detector in Python
  1. 6.1Signal quality indices SQI
  2. 6.2Automatic artefact detection
  3. 6.3Signal-to-noise ratio in real recordings
  4. 6.4Quality in ambulatory monitoring
  5. 6.5Detection of loose electrodes
  6. 6.6Saturation and clipping
  7. 6.7Manual annotation and consensus
  8. 6.8PhysioNet reference databases
  9. 6.9Impact of quality on algorithms
  10. 6.10Case study: SQI for an ECG patch
  1. 7.1Electrical safety under IEC 60601-1
  2. 7.2Particular requirements for electrocardiographs
  3. 7.3Electromagnetic compatibility under IEC 60601-1-2
  4. 7.4Equipment for home use
  5. 7.5Risk management under ISO 14971
  6. 7.6Software as a medical device
  7. 7.7Classification under the MDR
  8. 7.8Performance testing with simulators
  9. 7.9Technical documentation for the medical device
  10. 7.10Practice: test with a patient simulator
  1. 8.1Signal selection and use case
  2. 8.2Electrode and front-end design
  3. 8.3Digital acquisition design
  4. 8.4Processing and filtering
  5. 8.5Signal quality indicators
  6. 8.6Testing with volunteers and simulator
  7. 8.7Device risk analysis
  8. 8.8Technical validation report
  9. 8.9Written report and presentation
  10. 8.10Final review with the tutor
Methodology, software & labs

How you'll learn

Fully 100 % online training on the SEIUM Institute campus, with downloadable material, recorded classes and an assigned technical tutor. There is no fixed timetable: students progress at their own pace within the intake, which makes it possible to combine study with work.

Each module combines theory, guided reading of the original standard and applied exercises. The working software is MATLAB Signal Processing Toolbox, Python with NeuroKit2, OpenBCI GUI, EEGLAB, LTspice, in free, academic or evaluation versions. Tests are studied through real recording procedures with patient simulators, ambulatory acquisition with volunteers, and signal quality assessment using PhysioNet databases. Assessment is continuous, module by module, plus the final integrating project.

Accreditable laboratories(EN ISO/IEC 17025) with a rotor test rig, EMC/Lightning pre-compliance, HIL/SIL, vibration/acoustics.
Evidence-focused Master's Thesis:safety case, test plan, compliance dossier and operational limits.
Industry mentoring:faculty with a track record in training, , eVTOL/UAM and flight test.
Flexible format(hybrid/online), international cohorts and support from SEIUM Career Services.
Ethics and safety:a safety-by-design approach, with ciber-OT, DIH and compliance as its pillars.
Capstone project

Build it end to end

Your final project follows the real engineering workflow, step by step, reviewed by your tutor.

Signal selection and use case

Characterise the main bio-signals and their artefacts.

Electrode and front-end design

Select electrodes and sensors according to the application.

Digital acquisition design

Design low-noise analogue front-ends.

Processing and filtering

Configure synchronised digital acquisition systems.

Signal quality indicators

Apply filtering techniques and event detection.

Career opportunities

Where this takes you

Biomedical engineerMedical electronics designerSignal processing engineerWearable device engineerMedical device validation engineerNeurotechnology researcher
Admissions & scholarships

Requirements

  • Prior technical training or professional experience in the sector. No university degree is required.
  • Internet connection and a computer capable of running the programme's software.
  • Sufficient Spanish to follow technical regulatory reading.

Ready to start?

Send your application today. Our admissions team replies within 72 hours with your study plan and funding options.

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FAQ

Frequently asked questions

The programme consists of 800 hours in total, spread over 6 to 8 months. That is an average of 10 to 15 hours per week, compatible with a full-time job.

You will work with MATLAB Signal Processing Toolbox, Python with NeuroKit2, OpenBCI GUI, EEGLAB, LTspice. Free, academic or evaluation versions are used, and the tutor indicates the free alternative where one exists.

An SEIUM Institute diploma upon passing the continuous assessment and the integrating project. It is in-house training, not an official qualification from the Spanish Ministry of Education.

Yes. Modules passed in a course or postgraduate diploma in the same area can be credited towards the advanced programme. Consult the recognition policy when you enrol.

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