TY - JOUR
T1 - A novel method to quantify arterial pulse waveform morphology: attractor reconstruction for physiologists and clinicians
AU - Nandi, Manasi
AU - Venton, Jenny
AU - Aston, Philip
PY - 2018/9/26
Y1 - 2018/9/26
N2 - Current arterial pulse monitoring systems capture data at high frequencies (100{1000Hz). However, they typically report averaged or low frequency summary data such as heart rate and systolic, mean and diastolic blood pressure. In doing so, a potential wealth of information contained in the high delity waveform data is discarded, data which has long been known to contain useful information on cardiovascular performance. Here we summarise a new mathematical method, attractor reconstruction, which enables the quantication of arterial waveform shape and variability in real-time. The method can handle long streams of non-stationary data and does not require preprocessing of the raw physiological data by the end user. Whilst the detailed mathematical proofs have been described elsewhere (Aston et al., 2018), the authors were motivated to write a summary of the method and its potential utility for biomedical researchers, physiologists and clinician readers. Here we illustrate how this new method may supplement and potentially enhance the sen- sitivity of detecting cardiovascular disturbances, to aid with biomedical research and clinical decision making.
AB - Current arterial pulse monitoring systems capture data at high frequencies (100{1000Hz). However, they typically report averaged or low frequency summary data such as heart rate and systolic, mean and diastolic blood pressure. In doing so, a potential wealth of information contained in the high delity waveform data is discarded, data which has long been known to contain useful information on cardiovascular performance. Here we summarise a new mathematical method, attractor reconstruction, which enables the quantication of arterial waveform shape and variability in real-time. The method can handle long streams of non-stationary data and does not require preprocessing of the raw physiological data by the end user. Whilst the detailed mathematical proofs have been described elsewhere (Aston et al., 2018), the authors were motivated to write a summary of the method and its potential utility for biomedical researchers, physiologists and clinician readers. Here we illustrate how this new method may supplement and potentially enhance the sen- sitivity of detecting cardiovascular disturbances, to aid with biomedical research and clinical decision making.
U2 - 10.1088/1361-6579/aae46a
DO - 10.1088/1361-6579/aae46a
M3 - Article
SN - 0967-3334
JO - Physiological Measurement
JF - Physiological Measurement
ER -