H-Index & Metrics Top Publications

H-Index & Metrics

Discipline name H-index Citations Publications World Ranking National Ranking
Computer Science H-index 54 Citations 12,119 171 World Ranking 2234 National Ranking 124

Research.com Recognitions

Awards & Achievements

2000 - Fellow of the Royal Academy of Engineering (UK)

Overview

What is he best known for?

The fields of study he is best known for:

  • Artificial intelligence
  • Internal medicine
  • Statistics

Lionel Tarassenko mostly deals with Artificial intelligence, Respiratory rate, Pattern recognition, Photoplethysmogram and Machine learning. Lionel Tarassenko merges Artificial intelligence with Construct in his research. His Respiratory rate research integrates issues from Vagal tone, Oxygen saturation, Vital signs and Intensive care medicine.

His study in Pattern recognition is interdisciplinary in nature, drawing from both Electroencephalography, Speech recognition, Probabilistic logic, Nonlinear system and Epilepsy. In his study, Pulse oximetry is inextricably linked to Kalman filter, which falls within the broad field of Photoplethysmogram. His Machine learning research is multidisciplinary, incorporating elements of Information system and Pattern recognition.

His most cited work include:

  • Review: A review of novelty detection (858 citations)
  • A dynamical model for generating synthetic electrocardiogram signals (841 citations)
  • Normal ranges of heart rate and respiratory rate in children from birth to 18 years of age: a systematic review of observational studies (563 citations)

What are the main themes of his work throughout his whole career to date?

The scientist’s investigation covers issues in Artificial intelligence, Vital signs, Artificial neural network, Pattern recognition and Medical emergency. His study looks at the relationship between Artificial intelligence and fields such as Data mining, as well as how they intersect with chemical problems. Lionel Tarassenko has researched Vital signs in several fields, including Observational study, Respiratory rate, Warning system, Intensive care medicine and Emergency medicine.

As part of one scientific family, he deals mainly with the area of Respiratory rate, narrowing it down to issues related to the Cardiology, and often Blood pressure. His Artificial neural network study integrates concerns from other disciplines, such as Speech recognition and Very-large-scale integration. His work deals with themes such as Mobile phone, Emergency department and Clinical trial, which intersect with Medical emergency.

He most often published in these fields:

  • Artificial intelligence (24.70%)
  • Vital signs (15.44%)
  • Artificial neural network (14.25%)

What were the highlights of his more recent work (between 2017-2021)?

  • Blood pressure (8.79%)
  • Vital signs (15.44%)
  • Emergency medicine (10.21%)

In recent papers he was focusing on the following fields of study:

Blood pressure, Vital signs, Emergency medicine, Respiratory rate and Randomized controlled trial are his primary areas of study. His Vital signs research is multidisciplinary, incorporating perspectives in Observational study, Patient safety, Video camera, Acute hospital and Pediatrics. His research in Respiratory rate intersects with topics in Electrocardiography, Photoplethysmogram, Neonatal intensive care unit and Pattern recognition.

Lionel Tarassenko has included themes like Remote patient monitoring, Wavelet, Artificial intelligence, Computer vision and Continuous monitoring in his Photoplethysmogram study. His Artificial intelligence and Artificial neural network and Cluster analysis investigations all form part of his Artificial intelligence research activities. His research integrates issues of Intervention, Self-management, Physical therapy and Glycemic in his study of Randomized controlled trial.

Between 2017 and 2021, his most popular works were:

  • Efficacy of self-monitored blood pressure, with or without telemonitoring, for titration of antihypertensive medication (TASMINH4): an unmasked randomised controlled trial (129 citations)
  • Breathing Rate Estimation From the Electrocardiogram and Photoplethysmogram: A Review (88 citations)
  • Comparing the Efficacy of a Mobile Phone-Based Blood Glucose Management System With Standard Clinic Care in Women With Gestational Diabetes: Randomized Controlled Trial. (42 citations)

In his most recent research, the most cited papers focused on:

  • Internal medicine
  • Artificial intelligence
  • Statistics

His primary areas of investigation include Emergency medicine, Blood pressure, Respiratory rate, Vital signs and Randomized controlled trial. His studies deal with areas such as Photoplethysmogram and Key as well as Respiratory rate. The study incorporates disciplines such as Remote patient monitoring, Longest common subsequence problem, Artificial intelligence, Video monitoring and Continuous monitoring in addition to Photoplethysmogram.

His Artificial intelligence research incorporates elements of Modulation, Signal, Computer vision and Pattern recognition. His Vital signs research includes themes of Respiratory failure, Retrospective cohort study and Pneumonia. The various areas that Lionel Tarassenko examines in his Randomized controlled trial study include Odds ratio, Abnormal oral glucose tolerance, Physical therapy and Obstetrics.

This overview was generated by a machine learning system which analysed the scientist’s body of work. If you have any feedback, you can contact us here.

Top Publications

Review: A review of novelty detection

Marco A. F. Pimentel;David A. Clifton;Lei Clifton;Lionel Tarassenko.
Signal Processing (2014)

1514 Citations

A dynamical model for generating synthetic electrocardiogram signals

P.E. McSharry;G.D. Clifford;L. Tarassenko;L.A. Smith.
IEEE Transactions on Biomedical Engineering (2003)

1270 Citations

Normal ranges of heart rate and respiratory rate in children from birth to 18 years of age: a systematic review of observational studies

Susannah Fleming;Matthew Thompson;Matthew Thompson;Richard Stevens;Carl Heneghan.
The Lancet (2011)

816 Citations

Novelty detection for the identification of masses in mammograms

L. Tarassenko;P. Hayton;N. Cerneaz;M. Brady.
international conference on artificial neural networks (1995)

440 Citations

A Guide to Neural Computing Applications

Lionel Tarassenko.
(1998)

416 Citations

A review of parametric modelling techniques for EEG analysis

J. Pardey;S. Roberts;L. Tarassenko.
Medical Engineering & Physics (1996)

360 Citations

Non-contact video-based vital sign monitoring using ambient light and auto-regressive models

L Tarassenko;M Villarroel;A Guazzi;J Jorge.
Physiological Measurement (2014)

359 Citations

Application of independent component analysis in removing artefacts from the electrocardiogram

Taigang He;Gari Clifford;Lionel Tarassenko.
Neural Computing and Applications (2006)

293 Citations

Quantifying errors in spectral estimates of HRV due to beat replacement and resampling

G.D. Clifford;L. Tarassenko.
IEEE Transactions on Biomedical Engineering (2005)

290 Citations

Combining measurements from different sensors

Lionel Tarassenko;Neil William Townsend;James David Price.
(2001)

289 Citations

Profile was last updated on December 6th, 2021.
Research.com Ranking is based on data retrieved from the Microsoft Academic Graph (MAG).
The ranking h-index is inferred from publications deemed to belong to the considered discipline.

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