A5074311458- Non-Invasive Vital Sign Monitoring
- Mobile Health and mHealth Applications
- Healthcare Technology and Patient Monitoring
- Hemodynamic Monitoring and Therapy
- Neural Networks and Applications
- ECG Monitoring and Analysis
- Heart Rate Variability and Autonomic Control
- Sepsis Diagnosis and Treatment
- EEG and Brain-Computer Interfaces
- Fault Detection and Control Systems
- Blood Pressure and Hypertension Studies
- Anomaly Detection Techniques and Applications
- Diabetes Management and Research
- Chronic Obstructive Pulmonary Disease (COPD) Research
- Medication Adherence and Compliance
- Emergency and Acute Care Studies
- Machine Learning in Healthcare
- Gestational Diabetes Research and Management
- Time Series Analysis and Forecasting
- Advanced Memory and Neural Computing
- Digital Mental Health Interventions
- Blind Source Separation Techniques
- Respiratory Support and Mechanisms
- Phonocardiography and Auscultation Techniques
- Analog and Mixed-Signal Circuit Design
University of Oxford
2016-2025
Institute of Biomedical Science
2014-2025
Oxford BioMedica (United Kingdom)
2012-2023
Science Oxford
2002-2022
St Thomas' Hospital
2022
King's College London
2013-2022
ORCID
2022
University of Southampton
2022
The Stables
2022
University of Birmingham
2022
A dynamical model based on three coupled ordinary differential equations is introduced which capable of generating realistic synthetic electrocardiogram (ECG) signals. The operator can specify the mean and standard deviation heart rate, morphology PQRST cycle, power spectrum RR tachogram. In particular, both respiratory sinus arrhythmia at high frequencies (HFs) Mayer waves low (LFs) together with LF/HF ratio are incorporated in model. Much beat-to-beat variation timing human ECG, including...
The identification of the exact positions first and second heart sounds within a phonocardiogram (PCG), or sound segmentation, is an essential step in automatic analysis recordings, allowing for classification pathological events. While threshold-based segmentation methods have shown modest success, probabilistic models, such as hidden Markov recently been to surpass capabilities previous methods. Segmentation performance further improved when priori information about expected duration...
Remote sensing of the reflectance photoplethysmogram using a video camera typically positioned 1 m away from patient's face is promising method for monitoring vital signs patients without attaching any electrodes or sensors to them. Most papers in literature on non-contact sign report results human volunteers controlled environments. We have been able obtain estimates heart rate and respiratory preliminary changes oxygen saturation double-monitored undergoing haemodialysis Oxford Kidney...
<h2>Summary</h2><h3>Background</h3> Studies evaluating titration of antihypertensive medication using self-monitoring give contradictory findings and the precise place telemonitoring over alone is unclear. The TASMINH4 trial aimed to assess efficacy self-monitored blood pressure, with or without telemonitoring, for in primary care, compared usual care. <h3>Methods</h3> This study was a parallel randomised controlled done 142 general practices UK, included hypertensive patients older than 35...
The identification of invalid data in recordings obtained using wearable sensors is particular importance since from mobile patients is, general, noisier than nonmobile patients. In this paper, we present a signal quality index (SQI), which intended to assess whether reliable heart rates (HRs) can be electrocardiogram (ECG) and photoplethysmogram (PPG) signals collected sensors. algorithms were validated on manually labeled data. Sensitivities specificities 94% 97% achieved for the ECG 91%...
Over 100 algorithms have been proposed to estimate respiratory rate (RR) from the electrocardiogram (ECG) and photoplethysmogram (PPG). As they never compared systematically it is unclear which algorithm performs best.
Goal: Current methods for estimating respiratory rate (RR) from the photoplethysmogram (PPG) typically fail to distinguish between periods of high- and low-quality input data, perform well on independent "validation" datasets. The lack robustness existing directly results in a penetration such systems into clinical practice. present work proposes an alternative method improve estimation RR PPG. Methods: proposed algorithm is based use multiple autoregressive models different orders...
We assessed the effect of automated treatment adherence support delivered via mobile phone short message system (SMS) text messages on blood pressure.In this pragmatic, single-blind, 3-arm, randomized trial (SMS-Text Adherence Support [StAR]) undertaken in South Africa, patients treated for high pressure were randomly allocated a 1:1:1 ratio to information only, interactive SMS messaging, or usual care. The primary outcome was change systolic at 12 months from baseline measured with...
<h3>Importance</h3> Studies have established the importance of physical activity and fitness, yet limited data exist on associations between objective, real-world patterns, sleep, cardiovascular health. <h3>Objectives</h3> To assess feasibility obtaining measures activity, sleep from smartphones to gain insights into patterns associated with life satisfaction self-reported disease. <h3>Design, Setting, Participants</h3> The MyHeart Counts smartphone app was made available in March 2015,...
Treatment of hyperglycemia in women with gestational diabetes mellitus (GDM) is associated improved maternal and neonatal outcomes requires intensive clinical input. This currently achieved by hospital clinic attendance every 2 to 4 weeks limited opportunity for intervention between these visits.We conducted a randomized controlled trial determine whether the use mobile phone-based real-time blood glucose management system manage GDM remotely was as effective controlling standard care...
Breast cancer is the major cause of death amongst women in 35 to 55 age group. Mammography only feasible imaging modality for screening large numbers women. With present policy, there are three million mammograms be analysed each year UK; therefore a need (as yet unmet) an automated analysis system which could highlight areas interest. In first instance, interest might simply any mass-like structures and this indeed approach reported on paper. typical many problems medicine: class real...
Spectral estimates of heart rate variability (HRV) often involve the use techniques such as fast Fourier transform (FFT), which require an evenly sampled time series. HRV is calculated from variations in beat-to-beat (RR) interval timing cardiac cycle are inherently irregularly spaced time. In order to produce series prior FFT-based spectral estimation, linear or cubic spline resampling usually employed. this paper, by using a realistic artificial RR generator, interpolation and shown result...
The pulse-stream technique, which represents neural states as sequences of pulses, is reviewed. Several general issues are raised, and generic methods appraised, for pulsed encoding, arithmetic, intercommunication schemes. Two contrasting synapse designs presented compared. first based on a fully analog computational form in the only digital component signaling mechanism itself-asynchronous, pulse-rate encoded voltage pulses. In this circuit, multiplication occurs voltage/current domain....
To determine whether mobile phone based monitoring improves asthma control compared with standard paper strategies.Multicentre randomised controlled trial cost effectiveness analysis.UK primary care.288 adolescents and adults poorly (asthma questionnaire (ACQ) score ≥ 1.5) from 32 practices.Participants were centrally to twice daily recording transmission of symptoms, drug use, peak flow immediate feedback prompting action according an agreed plan or monitoring.Changes in scores on self...
The detection of novel or abnormal input vectors is importance in many monitoring tasks, such as fault complex systems and patterns medical diagnostics. We have developed a robust method for novelty detection, which aims to minimize the number heuristically chosen thresholds decision process. achieve this by growing gaussian mixture model form representation training set “normal” system states. When previously unseen data are be screened we use same threshold was used during define boundary....