This work was supported by the UK Engineering and Physical Sciences Research Council (EPSRC, Grant EP/H019944/1), the National Institute for Health Research (NIHR) Biomedical Research Centre at Guy's and St Thomas' NHS Foundation Trust in partnership with King's College London, the NIHR Oxford Biomedical Research Centre Programme, the Oxford and King's College London Centres of Excellence in Medical Engineering funded by the Wellcome Trust and EPSRC under grant no. WT88877/Z/09/Z and grant no. WT088641/Z/09/Z, a Royal Academy of Engineering (RAEng) Research Fellowship awarded to David A Clifton, and an EPSRC Challenge Award to David A Clifton. The views expressed are those of the authors and not necessarily those of the EPSRC, NHS, NIHR, Department of Health, Wellcome Trust, or RAEng.

An introduction to the Respiratory Rate Estimation (RRest) project, with a focus on the assessment of RR algorithms reported in this publication: Charlton P.H. and Bonnici T. et al. An assessment of algorithms to estimate respiratory rate from the electrocardiogram and photoplethysmogram, Physiological Measurement, 37(4), 2016. DOI: http://dx.doi.org/10.1088/0967-3334/37/4/610 This presentation is designed for use in Journal Club settings. Originally presented at the University of Oxford on 11th May 2016.

{"references": ["Charlton P.H. and Bonnici T.\u00a0et al.\u00a0An assessment of algorithms to estimate respiratory rate from the electrocardiogram and photoplethysmogram,\u00a0Physiological Measurement, 37(4), 2016. DOI: 10.1088/0967-3334/37/4/610"]}