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ASTUTE 2020 Update September 2020

Here at ASTUTE 2020, we can support your business throughout this period of uncertainty. Our world-class academics and technical experts from across our strong Welsh Universities partnership are available to support you through research and innovation activities. If you wish to discuss opportunities for working with us e.g. to modify your production to develop solutions to support the fight against COVID-19, you can contact us via email.


Image: Recovering Signal of the Foetal Heart Rate from the Audio Data

Recovering Signal of the Foetal Heart Rate from the Audio Data

Business: SymlConnect Ltd.

Expertise: Manufacturing Systems Engineering Duration: 12 weeks

Results Area: Signal processing for foetal heartbeat monitor

Technology: Advanced filtering approach (Discrete Wavelet Transform)

Location: Swansea


SymlConnect is a health informatics company specialising in creating cost effective ICT solutions for better communication within the existing systems & professionals, anywhere anytime, using smart mobile devices for better integrated care delivery.


One of its latest products is the user friendly Syml_Beat+ which has the capability to capture the audio data, Foetal Heart Rate (FHR) from a Doppler device at a mother’s home or at the clinic and produce a CTG (cardiotocography) machine like graph.

The audio and the generated graph can be shared in real time with a Consultant located remotely for informed decision making. The information could be saved in the patient’s file for future referencing, which is currently not feasible.

The advantage is that only patients required to be admitted are admitted to the hospital, thus saving time and expense for both patient and the hospital.

While this approach would appear simple in concept, in practice the collected audio data from a Doppler device, contains noise originating from surrounding unwanted sources during the examination that cause the degradation in the accuracy of the FHR. To overcome this issue, advanced signal processing was required that employed an effective de-noising methodology to remove noise frequencies which are not associated with the FHR.


ASTUTE successfully developed efficient algorithms to de-noise the signal by using a Discrete Wavelet Transform technique, thus removing unwanted spurious frequencies from the signal. The FHR was then recovered from the de-noised audio data using modified autocorrelation techniques. By applying a complete filtering algorithm together with the conventional wavelet decomposition and reconstruction, ASTUTE was able to support SymlConnect enhancing its software application and pilot at Singleton Hospital.

“We were thrilled with the outcome and the personal supporting attitude that ASTUTE has shown which is helping us to move closer to a pilot phase of the project.”

- Sabarna Mukhopadhyay, CEO, SymlConnect Ltd.

Due to focus on Smart Specialisation, some of the expertise areas in the case studies might not be covered in the current ASTUTE 2020.