Wearable hardware
Sensor selection, embedded systems and physiological data acquisition. We develop wearable platforms and the tools needed to capture and inspect their recordings.
Sensor integration · Embedded C · Prototyping
Biomedical engineering · Wales
Closer to
the signal.
Wearable hardware. Physiological signals.
Machine learning.
We develop sensing platforms and analysis methods for medical research, and help medical technology teams build theirs.
Physiology, in detailECG + PPG
From the sensor to the modelHardware development Research Consultancy
01 / Expertise
The whole measurement chain.
A useful model starts with a useful measurement. We work across the hardware, the physiology and the analysis, so decisions at each stage make sense together.
Signal processing
Understanding what is in a recording, and what can be trusted. Our work covers signal quality, beat detection, waveform features and analysis across multiple sensors.
PPG · ECG · Multimodal analysis
Machine learning
Machine learning and deep learning for biomedical data. We build processing and modelling pipelines, from dataset preparation and feature engineering to model evaluation.
Biomedical time series · ML · Deep learning
02 / Our hardware
More of the signal.
More room to investigate.
Research needs more than heart rate and beat intervals. It needs access to the underlying signals and a clear account of how they have been processed.
We are developing wearable sensing hardware that gives researchers greater freedom to explore physiological data. Our aim is to make raw recordings available where needed and provide a clear account of any processing applied, so researchers can understand their measurements and choose how to use them.
That flexibility extends to the analysis. Researchers can use their own methods or work with us on preprocessing, signal quality assessment and further analysis, with an approach suited to their study and a documented processing chain.
To make these capabilities useful in practice, we are designing around the people and services that will use them. Clinical workflows, the needs of clinicians and integration with healthcare services are considered from the outset, including how recordings are collected, reviewed and used within a study or care pathway.
Platform in developmentThe research workflowW / 01
01
Capture
Physiological and movement signals
02
Inspect
Signal quality and measurement behaviour
03
Analyse
Waveform features and relationships
04
Model
Reproducible machine learning pipelines
Hardware and analysis, developed together.
03 / Consultancy
Bring us the technical question.
We work with medical technology companies and research teams on specific engineering problems and broader development projects.
01
Sensing and technical feasibility
02
Signal processing and data quality
03
Machine learning and deep learning pipelines
04
Experimental analysis and prototype evaluation
04 / Research direction
What can a pulse
tell us about
vascular function?
We are interested in the detail of the PPG waveform and what it may reveal about cardiovascular physiology.
We have a particular interest in endothelial function. Our research direction explores whether PPG and complementary physiological measurements can provide useful information about vascular function, and how those measurements could be evaluated in clinical research.
This means connecting wearable measurements with physiological questions and evaluating them against appropriate reference methods. Applications in pregnancy and pre eclampsia are one area of interest within that broader work.
Discuss a research collaborationA closer look / PPG morphology
Features within a single pulse.
Pulse shape offers more to investigate than heart rate alone. Here, Δt marks the time between the systolic and diastolic peaks.
The notch and secondary peak are not distinct in every recording. These landmarks describe waveform shape, rather than a direct measurement of endothelial function.
Read the review on PPG and vascular ageing05 / About Wearalyze
Based in Wales.
Built on research.
Wales, United Kingdom
Wearalyze is a Welsh biomedical technology company founded by Dr David O’Connor, an engineer and researcher working across sensors, physiological monitoring and data analysis.
David’s experience includes wearable cardiovascular monitoring at Swansea University on projects funded by Wellcome Leap, and research and development at Cyden in a regulated medical device environment.
At Swansea University, he also worked with Boston Scientific on imaging and analysis of transcatheter aortic valve replacement (TAVR) devices, using stereo imaging and digital image correlation to measure their displacement and strain.
His background spans embedded sensing, cardiovascular modelling, experimental methods and biomedical data pipelines. Wearalyze brings that experience together through its own technology development and consultancy.
EngDSwansea University
Hardware + analysisAcross research and industry
Let’s talk
What are you
working on?
Tell us about your device, your data or the question you are trying to answer. We welcome consultancy enquiries and research collaborations.
contact@wearalyze.com