Peter Charlton gained the degree of MEng in Engineering Science in 2010 from the University of Oxford. Since then he held a research position, working jointly with Guy's and St Thomas' NHS Foundation Trust, and King's College London.

Peter’s research focuses on physiological monitoring of hospital patients, divided into three areas. The first area concerns the development of signal processing techniques to estimate clinical parameters from physiological signals. He has focused on unobtrusive estimation of respiratory rate for use in ambulatory settings (NCT01472133), invasive estimation of cardiac output for use in critical care, and novel techniques for analysis of the pulse oximetry (photoplethysmogram) signal. Secondly, he is investigating the effectiveness of technologies for the acquisition of continuous and intermittent physiological measurements in ambulatory and intensive care settings (NCT01549717). Thirdly, he is developing techniques to transform continuous monitoring data into measurements which are appropriate for real-time alerting of patient deteriorations.

The two clinical trials on which he is currently an investigator are:

1. 'Validation of Respiration Rate Algorithms' (NCT01472133), in which the performance of algorithms for estimating respiration rate from ECG and pulse oximetry signals is being assessed.
2. 'Feasibility and Efficacy of Continuous In-Hospital Patient Monitoring' (NCT01549717), in which the the feasibility and efficacy of continuous physiological monitoring for prediction of deteriorations is being evaluated and compared to standard ward practice in the ambulatory setting.

For his PhD, he is testing the hypothesis that

Deterioration of inpatients could be detected earlier by monitoring their physiological
trajectories.

To test this hypothesis, he is modelling physiological trajectories of patients recovering from cardiac surgery.

His Google Scholar profile is available here.

His Github profile is available here, which includes the Respiratory Rate Estimation Project.

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Peter Charlton is a member of the Critical Care Department at Guy's and St Thomas' NHS Foundation Trust; a member of the Haemodynamic Modelling Research Group at King's College London; and a member of the Computational Health Informatics Laboratory at the University of Oxford.

His research focuses on development, and clinical integration, of physiological monitoring techniques for early detection of clinical deteriorations. This involves: (i) testing early warning systems and wearable sensors in the hospital environment; (ii) developing signal analysis techniques to extract physiological parameters from physiological signals; and (iii) design of early warning algorithms by using machine learning to fuse physiological parameters, indicating the likelihood of deterioration.

His Google Scholar profile is available here.

His Github profile is available here, which includes the Respiratory Rate Estimation Project.