Professional background

Tim Bonnici studied medicine at Imperial College and undertook his medical training in London, Poole and Oxford. He is dual-accredited in intensive care and general internal medicine and has a special interest in the management of the acutely deteriorating inpatient on the general hospital ward and the interface between the intensive care unit and the general wards.

His PhD research, undertaken at St Thomas’ Hospital (KCL) and the John Radcliffe Hospital (University of Oxford), examined how wearable monitors and automated algorithms could be used to identify deteriorating ward patients. During this period, working with a multidisciplinary team of biomedical engineers, computer scientists, human factors specialists and clinicians he co-invented SEND, a digital vital signs charting system designed to be intuitive and highly usable. SEND has been cited in numerous NHS and government reports as an example of high quality NHS innovation.

He works as an intensive care consultant at UCLH and maintains an active research interest in digital health applied to patient safety and acute deterioration.


Research interests

Machine learning and artificial intelligence, wearable monitors, clinical informatics, complex systems engineering, rapid response systems/ the deteriorating patient, patient safety, human factors and usability


  • Dahella SS, Briggs JS, Coombes P, Farajidavar N, Meredith P, Bonnici T, Daryshire J, Watkinson P. Implementing a system for the real-time risk assessment of patients considered for intensive care. BMC Medical Informatics and Decision Making. 2020 Jul 16;20(1):224.
  • Gerry S, Bonnici T, Birks J, Kirtley S, Virdee PS, Watkinson PJ, et al. Early warning scores for detecting deterioration in adult hospital patients: systematic review and critical appraisal of methodology. BMJ. 2020 May 20;369:m1501.
  • Malycha J, Bonnici T, Clifton DA, Ludbrook G, Young JD, Watkinson PJ. Patient centred variables with univariate associations with unplanned ICU admission: a systematic review. BMC Medical Informatics and Decision Making. BioMed Central; 2019 Dec 1;19(1):98.
  • Charlton PH, Birrenkott DA, Bonnici T, Pimentel MAF, Johnson AEW, Alastruey J, et al. Breathing Rate Estimation from the Electrocardiogram and Photoplethysmogram: A Review. IEEE Rev Biomed Eng. 2018 Oct 23;11:2–20
  • Gerry S, Birks J, Bonnici T, Watkinson PJ, Kirtley S, Collins GS. Early warning scores for detecting deterioration in adult hospital patients: a systematic review protocol. BMJ Open. 2017 Dec 3;7(12):e019268.
  • Charlton P, Birrenkott DA, Bonnici T, Pimentel MAF, Johnson AEW, Alastruey J, et al. Breathing Rate Estimation from the Electrocardiogram and Photoplethysmogram: A Review. IEEE Rev Biomed Eng. 2017 Sep 6;PP(99):1–17.
  • Charlton PH, Bonnici T, Tarassenko L, Alastruey J, Clifton D, Beale R, et al. Extraction of respiratory signals from the electrocardiogram and photoplethysmogram: technical and physiological determinants. Physiol Meas. IOP Publishing; 2017 Mar 15;38(5):669–90. This paper was selected for the PMEA Highlights of 2017 marking it as one of the most influential papers published in Physiological Measurement that year.
  • Malycha J, Bonnici T, Sebekova K, Petrinic T, Young D, Watkinson P. Variables associated with unplanned general adult ICU admission in hospitalised patients: protocol for a systematic review. Systematic Reviews 2015 4:1. BioMed Central; 2017 Mar 28;6(1):67.
  • Wong DC, Bonnici T, Knight J, Gerry S. A ward-based time study of paper and electronic documentation for recording vital sign observations. Journal of the American Medical Informatics Association. 2017 Feb 11.
  • Bonnici T*, Charlton PH*, (*joint first author), Tarassenko L, Clifton DA, Beale R, Watkinson PJ. An assessment of algorithms to estimate respiratory rate from the electrocardiogram and photoplethysmogram. Physiol Meas. IOP Publishing; 2016 Apr 1;37(4):610–26.
  • Bonnici T, Gerry S, Wong D, Knight J, Watkinson P. Evaluation of the effects of implementing an electronic early warning score system: protocol for a stepped wedge study. BMC Medical Informatics and Decision Making. BioMed Central; 2016 Feb 9;16(1):1.
  • Wong D, Bonnici T, Knight J, Morgan L, Coombes P, Watkinson P. SEND: a system for electronic notification and documentation of vital sign observations. BMC Medical Informatics and Decision Making; 2015 Aug 13;15(1):702.
  • Orphanidou C, Bonnici T, Charlton P, Clifton D, Vallance D, Tarassenko L. Signal-quality indices for the electrocardiogram and photoplethysmogram: derivation and applications to wireless monitoring. IEEE J Biomed Health Inform. 2015 May;19(3):832–8.
  • Charlton P, Bonnici T, Clifton D, Alastruey J, Tarassenko L, Beale R et al. The Influence of Recording Equipment on the Accuracy of Respiratory Rate Estimation from the Electrocardiogram and Photoplethysmogram. In MEC Annual Meeting and Bioengineering 14 Programme and Abstracts. London: Imperial College London. 2014. p. 96-96. 116.
  • Bonnici T, Tarassenko L, Clifton DA, Watkinson PJ. The digital patient. Clinical Medicine. 2013 Jun 7;13(3):252–7.
  • Orphanidou C, Bonnici T, Vallance D, Darrell A, Charlton P, Tarassenko L. A method for assessing the reliability of heart rates obtained from ambulatory ECG. Proceedings of the 2012 IEEE 12th International Conference on Bioinformatics & Bioengineering (BIBE) 2012. pp. 193–6.
  • Bonnici T, Orphanidou C, Vallance D, Darrell A, Tarassenko L. Testing of Wearable Monitors in a Real-World Hospital Environment: What Lessons Can Be Learnt? Proceedings of Ninth International Conference on Wearable and Implantable Body Sensor Networks (BSN), 2012. p. 79–84.
  • Bonnici T, Goldsmith D. Renal and cardiac arterial disease: parallels and pitfalls. British Journal of Cardiology 2008;15:261.