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The automated analysis, done for each minute at a time, includes all steps briefly described below which were developed based on established principles and methods described in literature, to isolate the desired surrogate ICP waveform signal for consistent processing:
Data input - data from a monitoring session that is temporarily stored in the Mobile App, which is connected to the B4C System sensor, is transferred to the B4C System. De-identified data is parsed and saved for processing.
Downsampling - the acquired signal is downsampled to a desired sampling frequency for analysis.
Signal de-trending - given the device’s mechanical properties certain trends in the monitoring session timeline are eliminated.
Signal filtering - high frequency waveform noise is removed.
Signal validation - non physiological waveforms are identified and removed.
Pulse finding - pulses contained in the captured signal are identified. At this point the subject device’s output derived heart rate (bpm) is calculated.
Check inversion - mirrored waveforms are identified and inverted.
Artifact removal - patient head movements, as well as bites, cringes, etc… are captured by the sensor and may create waveform pulse artifacts. These are identified and removed. At this point the system calculates the number of useful pulses, i.e., the number of pulses considered in the calculation of the average pulse.
Pulse alignment - after all pulses have been validated, they are symmetrically padded , i.e, they are “stretched” or “shrunk” time-wise in order to normalize their lengths without distortion.
Pulse averaging - all the aligned useful pulses for that same minute are finally used to calculate the mean pulse with a 95% two-tailed confidence interval. The mean pulse is the visible blue line and the grey zone is the confidence interval as seen in Figure 06figure below.At this point the subject device’s output pulse morphology as average per minute is generated.
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For each minute of average surrogate ICP waveform, two key parameters are estimated to derive derived from relevant physiological information from based on relative and / or normalized measurements. The most relevant parameters meeting those conditions are estimated P2/P1 ratio and normalized time to peak and they are described as follows.
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Based on the the observation of a subset of 1453 minutes of concurrent invasive ABP (arterial blood pressure) and invasive ICP (intracranial pressure) as well as non-invasive BcSs-PICNI-2000 (B4C Sensor device) from a clinical study demonstrated a significant statistical correlation between the waveform parameters shown on Figure 12.2figure below:
Invasive ICP’s percussion wave (A1) timing (T1) is almost the corresponding ABP’s waveform first peak
Invasive ICP’s notch (A3) timing (T3) is closely related to ABP’s dicrotic notch
Invasive ICP’s tidal wave (A2) timing (T2) is estimated to be midway between ABP’s T3 and T1
ABP based algorithm (research algorithm)
Based on this observation an algorithm was developed that estimates the timing of P1 and P2 amplitudes for the invasive ICP waveform, as well as the BcSs-PICNI-2000 (B4C Sensor) waveforms, based on the concurrent ABP pulse’s T1 and T2 normalized timings (Figure 12. 2). This allowed for indirect (surrogate) P1 and P2 estimation when they are not visually identifiable in the invasive ICP.
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A subsequent test was done to validate the production algorithm. All valid waveform data captured from the invasive ICP (invasive sensor) and non-invasive BcSs-PICNI-2000 (B4C Sensor device) had their minute by minute P2/P1 ratio calculated with the ABP based algorithm (research algorithm) and Production algorithm. When the P2/P1 ratio was calculated by both algorithms, one being the P2/P1 ratio estimated by using the concurrent APB waveform as defined in Figure 12.2 figure above, and the other being the estimation of the most probable position of P1 and P2, and then compared to each other, the correlation was high between both methods when applied to the waveform coming from both sensors:
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Normalized time to peak’s key hypothesis is that it is affected by compensatory reserve and intracranial compliance. The derived parameters required to identify time to peak are defined in Figure 12.3figure below.Normalizedtime to peak is identified from point A, the max slope of the calculated average waveform (moment in time where pulse slope is steepest) to point B, normalized duration from the identified average pulse’s Max slope to highest pulse amplitude.
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