# Prediction of Blood Pressure after Induction of Anesthesia Using Deep Learning: A Feasibility Study
## 2 Materials and Methods
\begin{table}
\begin{tabular}{c l} \hline \hline
**Name** & **Description** \\ \hline HR & Heart-rate (number of heartbeats per minute) \\ ETCO2 & End tidal carbon dioxide \\  & (carbon dioxide concentration at the end of exhalation) \\ NIBP\_SBP & Non-invasive systolic blood pressure \\ NIBP\_MBP & (systolic blood pressure measured by sphygmomanometer) \\ NIBP\_MBP & Non-invasive mean blood pressure \\ NIBP\_DBP & (mean blood pressure measured by sphygmomanometer) \\ NIBP\_DBP & Non-invasive diastolic blood pressure \\  & (diastolic blood pressure measured by sphygmomanometer) \\ NMT\_TOF\_CNT & Neuromuscular transmission train-of-four count \\ NMT\_TOF\_CNT & (number of single twitches caused by consecutive four electrical stimuli) \\ RR\_TOTAL & Total respiratory rate \\  & (number of breaths per minute including mechanical and spontaneous breath) \\ TV & Tidal volume \\  & (volume in single breath) \\ MV & Minute ventilation \\  & (volume of air moved into and out of the lungs in a minute) \\ PIP & Peak inspiratory pressure \\  & (highest airway pressure during inspiration) \\ MAWP & Mean airway pressure \\  & (average airway pressure during inspiration) \\ PEEP\_TOTAL & Total Positive End-Expiratory Pressure (PEEP) \\  & (alveolar pressure above atmospheric pressure that exists at the end of expiration) \\ BIS/SEF & Spectral edge frequency \\  & (frequency at which 95\% of the total power lies below it) \\ BIS/SQI & Signal quality index \\  & (signal quality of the electroencephalography signal between 0 and 100\%) \\  & Electromyogram power \\ BIS/EMG & (a logarithmic scale of total power in the 70–110 Hz range, \\  & averaged over the preceding 10 s. \\  & It has a minimal value of 25 dB, and in the awake patients it is 40–60 dB) \\ BIS/BIS & BIS value \\  & (value provided by the bispectral index algorithm (range 0–100)) \\ BIS/TOTOW & Total power \\  & (absolute total power in the frequency range (0.5–30 Hz)) \\ PROPOFOL\_RATE & Propofol flow rate \\  & (speed of propofol administration (mL per hour)) \\ PROPOFOL\_CP & Propofol plasma concentration \\ PROPOFOL\_CE & (propofol concentration in the blood (microgram per mL)) \\ PROPOFOL\_CE & Propofol effect-site concentration \\  & (propofol concentration in the brain (microgram per mL)) \\ PROPOFOL\_CT & Propofol target concentration \\  & (set concentration of propofol to target brain concentration (microgram per mL)) \\ PROPOFOL\_VOL & Propofol infused volume \\  & (volume of propofol infused (mL)) \\ REMIFENTANIL\_RATE & Remifentanil flow rate \\  & (speed of remifentanil administration (mL per hour)) \\ REMIFENTANIL\_CP & Remifentanil plasma concentration \\  & (remifentanil concentration in the blood (nanogram per mL)) \\ REMIFENTANIL\_CE & Remifentanil effect-site concentration \\  & (remifentanil concentration in the brain (nanogram per mL)) \\ REMIFENTANIL\_CT & Remifentanil target concentration \\  & (set concentration of remifentanil to target brain concentration (nanogram per mL)) \\ REMIFENTANIL\_VOL & Remifentanil infused volume \\  & (volume of remifentanil infused (mL)) \\ \hline \hline \end{tabular}
\end{table} 
Table 1: Details of collected data. We transform the sequence of \(K\times(T_{r}/3)\) matrices into a shape for the real-time sequential prediction of future blood pressure as follows. First, for each \(t\)-th timestep where \(1\leq t\leq T_{r}/3\), we define the sequence of vital signs excluding blood pressures for previous \(W\) timesteps as an input \(i_{t}\) in other words, the input \(i_{t}\) is a \(K-3\times W\) matrix for the timesteps between \([t-W+1,t]\). We also add the timestep \(t\) into the \(i_{t}\), so finally the \(i_{t}\) becomes a \(K-2\times W\) matrix. Second, we define a normalized blood pressure at the \(t\)-th timestep as a supplementary input \(si_{t}\). If the blood pressure value is 125, then it is divided by 250 to be normalized (e.g., 125/250).