| Abbreviation(s) |
Full name(s) |
| AAMI |
Association for the Advancement of Medical Instrumentation |
| ABP |
Arterial blood pressure |
| Acc. |
Accuracy |
| AE |
Absolute error |
| ANN |
Artificial neural network |
| ANSI |
American National Standards Institute |
| BCG |
Ballistocardiography |
| BHS |
British Hypertension Society |
| BMI |
Body mass index |
| BP |
Blood pressure |
| CHD |
Coronary heart disease |
| CNN |
Convolutional neural network |
| CO |
Cardiac output |
| CP |
Cardiac period |
| CV |
Cardiovascular |
| CVD |
Cardiovascular disease |
| CWT |
Continuous wavelet transform |
| DBP |
Diastolic blood pressure |
| DL |
Deep learning |
| DNN |
Deep neural network |
| DT |
Diastolic time |
| DWT |
Discrete wavelet transform |
| ECG |
Electrocardiography |
| FCNN |
Fully connected neural network |
| FFT |
Fast Fourier transform |
|
An inverse of the fast Fourier transform |
| GAN |
Generative adversarial network |
| GCG |
Gyrocardiography |
| GRU |
Gated recurrent unit |
| HT |
Hypertension |
| IBP |
Instant blood pressure |
| ICG |
Impedance cardiography |
| IEEE |
Institute of Electrical and Electronics Engineers |
| IMAR |
Iterative metal artifact reduction |
| IPG |
Impedance photoplethysmography |
| iPPG |
Imaging photoplethysmography |
| IR |
Infrared |
| JADE |
Joint Approximation Diagonalisation of Eigen-matrices |
| JHS |
Jackson Heart Study |
| LASSO |
Least absolute shrinkage and selection operator |
| LMS filter |
Least mean squares filter |
| LSTM |
Long short-term memory |
| MAE |
Mean absolute error |
| MAP |
Mean arterial pressure |
| MAPD |
Minimum absolute percentage difference |
| ME |
Mean error |
| MERS |
Middle East respiratory syndrome |
| MI |
Myocardial infarction |
| MIC |
Maximal information coefficient |
| MIMIC |
Medical Information Mart for Intensive Care |
| ML |
Machine learning |
| mNPV |
Modified normalised pulse volume |
| NT |
Normotension |
| OD |
Oscillometric device |
| OLE |
Ordinary least squares |
| PAT |
Pulse arrival time |
| PCA |
Principal component analysis |
| PCG |
Phonocardiogram |
| PD |
Phase difference |
| PEP |
Pulse ejection period |
| PHT |
Prehypertension |
| PIR |
Photoplethysmogram intensity ratio |
| PPG |
Photoplethysmography |
| PTT |
Pulse transit time |
| PWA |
Pulse wave analysis |
| PWV |
Pulse wave velocity |
| RMSE |
Root mean square error |
| RNN |
Recurrent neural network |
| ROI |
Regions of interest |
| rPPG |
Remote photoplethysmography |
| RZS |
Random zero sphygmomanometer |
| SARS |
Severe acute respiratory syndrome |
| SBP |
Systolic blood pressure |
| SBS |
Strain-based sensor |
| SCG |
Seismocardiography |
|
Oxygen saturation |
| SUT |
Systolic upstroke time |
| SV |
Support vector |
| SVM |
Support vector machine |
| TML |
Traditional machine learning |
| TOI |
Transdermal optical imaging |
| TPR |
Total peripheral resistance |
| UQVS |
The University of Queensland vital signs |