Dr Hajar Razaghi

Dr Hajar (Helga) Razaghi MSc, PhD, MIET, FHEA

Senior Lecturer


Dr Helga Razaghi is a lecturer in Electronic/Electrical Engineering. She has extensive experience in analogue and digital electronics, signal processing, programming and physics. She received her PhD in medical electronics from Sheffield Hallam University in 2016. Dr Razaghi joined Electronic Engineering subject group in August,  2017 having completed her post doctorate. Her main research interests include medical engineering, artificial intelligence and signal processing.


Dr Helga Razaghi is an active researcher whose expertise includes signal processing, medical electronics, biomedical signal processing, sensors and sensory systems. Her research findings resulted in publication and presentation in national and international peer-reviewed journals and conferences.

Having BSc and MSc in applied physics in addition to a PhD in Medical Electronics equipped her with multidisciplinary research skills which help greatly in understanding and explaining various technical information and research ideas. She has broad experience of collaboration with industry and NHS to find engineering solutions for real-world problems.

She is a reviewer for several peer reviewed international journals and conferences, a member of IET and IEEE and committed to continuous professional development regarding both teaching and research.

Dr Razaghi has successfully generated funding in support of her own research and academic functions. She has received several awards for the outstanding quality of her research including Early Career Award from the College of Business, Technology and Enterprise in 2018.


2011 – 2016- PhD in Digital Vibration Analysis Developments for Assessing Bone Fracture Risk in Children, Sheffield Hallam University in Sheffield.



Department of Engineering and Mathematics

College of Business, Technology and Engineering

Electronic and Electrical Engineering

Dr Razaghi strives to cultivate a stimulating environment in class to support innovative learning and critical thinking. Helga teaches on a number of modules in the area of electronic and electrical engineering including:

  • Analogue and digital systems
  • Analogue electronic engineering
  • Mechatronics
  • Professional engineering practice; PCB design
  • Project 1
  • programming


Current major projects:

2011 - Ongoing: Developing a Portable Bone Mineral Density Assessment System Utilising Vibration Analysis

A novel device has been developed to assess bone mineral density (BMD) using bone vibration responses recorded in vivo. It is cost effective, non-invasive, easy to operate and child friendly. It has been evaluated in several clinical trials on over 100 children who were referred to the hospital suspected of abnormal density and had Dual- energy X-ray Absorptiometry (DXA) scan as part of their examinations.

The bone vibration responses were analysed using complex digital signal processing methods and were interpreted using different statistical methods.

Findings showed over 80% similarity between the DXA-derived and vibration analysis estimated BMDs.

The purpose of the device is to provide a cost effective and an easy to use screening tool that is widely available to clinicians at hospitals and surgeries. It could assist with earlier detection of conditions like osteogenesis imperfecta thus reducing cost and improving patient experience.

This project has been funded by Innovate UK, The Children’s Hospital Charity (TCHC) and Medical research Council (MRC). Development of this novel device resulted in submission of an international Patent Cooperation Treaty (PCT) application by SHU. The developed device has the potential to be commercialised as a medical device.

This project is being carried out in collaboration with Sheffield Children’s NHS Foundation Trust.

2018 - Ongoing: Artificial Intelligence for smart sleep log and analysis

Sleep is essential for well-being. Understanding sleep-wake patterns helps diagnose and treat children’s sleep disorders. Current practice uses a paper sleep diary and a wearable sensor for monitoring sleep. The data provided by families (sometimes incomplete) and the wearable, requires hours of analysis for sleep specialists.

This project aims to provide a technical solution with integrated elements:

  • a user-friendly mobile application, enabling families to provide more helpful data about their child’s sleep
  • an artificial intelligence algorithm that provides detailed assessment of sleep patterns, to support clinical decision making.

This project has been funded by The Children’s Hospital Charity (TCHC) and SHU Advanced Wellbeing Research Centre (AWRC).

This project is being carried out in collaboration with Sheffield Children’s NHS Foundation Trust and NIHR Devices for Dignity MedTech Co-operative (D4D).


Journal articles

Barika, R., Elphick, H., Lei, N., Razaghi, H., & Faust, O. (2022). Environmental benefits of sleep apnoea detection in the home environment. Processes, 10 (9). http://doi.org/10.3390/pr10091739

Razaghi, H., Saatchi, R., Bishop, N.J., Burke, D., & Offiah, H. (2020). Evaluation of Vibration Analysis to Assess Bone Mineral Density in Children. WSEAS Transactions on Biology and Biomedicine, 17, 39-47. http://doi.org/10.37394/23208.2020.17.6

Faust, O., Razaghi, H., Barika, R., Ciaccio, E.J., & Acharya, U.R. (2019). A review of automated sleep stage scoring based on physiological signals for the new millennia. Computer Methods and Programs in Biomedicine, 176, 81-91. http://doi.org/10.1016/j.cmpb.2019.04.032

Harrison, R., Ward, K., Lee, E., Razaghi, H., Horne, C., & Bishop, N.J. (2015). Acute bone response to whole body vibration in healthy pre-pubertal boys. Journal of musculoskeletal and neuronal interactions, 15 (2), 112-122. http://www.ismni.org/jmni/pdf/60/01HARRISON.pdf

Razaghi, H., Saatchi, R., Offiah, A., Bishop, N., & Burke, D.P.A. (2013). Correlation analysis of bone vibration frequency and its mass: volume ratio. Bone Abstracts, 2, P175. http://doi.org/10.1530/boneabs

Razaghi, H., Saatchi, R., Offiah, A., Burke, D., Bishop, N., & Gautam, S. (2013). Assessing material densities by vibration analysis and independent component analysis. Malaysian Journal of Fundamental and Applied Sciences, 9 (3). http://doi.org/10.11113/mjfas.v9n3.96

Conference papers

Barika, R., Shenfield, A., Razaghi, H., & Faust, O. (2021). A smart sleep apnea detection service. 17th International Conference on Condition Monitoring and Asset Management, CM 2021. https://www.bindt.org/shopbindt/cd-roms/proceedings-of-cm-2021.html#.YWQX39rMIuV

Razaghi, H., Saatchi, R., & Offiah, A.C. (2020). Neural Network Analysis of Bone Vibration Signals to Assesses Bone Density. In Ball, A., Gelman, L., & Rao, B.K.N. (Eds.) Advances in Asset Management and Condition Monitoring: COMADEM 2019, (pp. 1285-1295). Springer: http://doi.org/10.1007/978-3-030-57745-2_106

Razaghi, H., Saatchi, R., & Offiah, A. (2016). Vibration analysis as a tool for bone mineral density assessment in children. In British Society of Paediatric Radiology Annual Scientific Meeting, London, 10 November 2016 - 11 November 2016. British Society of Paediatric Radiology: http://bspr.org.uk/

Razaghi, H., Saatchi, R., Huggins, T., Bishop, N., Burke, D., & Offiah, A.C. (2014). Correlation analysis of bone vibration frequency and bone mineral density in children. In 2014 9th International Symposium on Communication Systems, Networks and Digital Sign, CSNDSP 2014, (pp. 188-192). Institute of Electrical and Electronics Engineers: http://doi.org/10.1109/CSNDSP.2014.6923822

Razaghi, H., Saatchi, R., Burke, D., & Offiah, A.C. (2014). An investigation of relationship between bone vibration frequency and its mass-volume ratio. 2014 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP). http://doi.org/10.1109/icassp.2014.6854275

Razaghi, H., Saatchi, R., Offiah, A., Bishop, N., & Burke, D. (2012). Spectral analysis of bone low frequency vibration signals. In 8th IEEE, IET International Symposium on Communication Systems, Networks and Digital Signal Processing. Piscataway, NJ: IEEE: http://doi.org/10.1109/CSNDSP.2012.6292718

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