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1 Introduction

The cranial compartment is incompressible, and its internal pressure is determined by the sum of contributes due to three compartments: haematic, parenchymal and liquoral. It is difficult to define an ordinary intracranial pressure (ICP) value, i.e. it depends on patient’s age, position and clinical condition. An average value for a sane adult patient in horizontal position is in the range 7–15 mmHg [1].

ICP monitoring is considered the most useful clinical technique in the management of patients with intracranial disease. If the cerebral vessels are not reactive, an increase in cerebral perfusion pressure may result in several grave forms of pathology [2]. Since the 1980s continuous intracranial pressure monitoring has become more widely used, due to the development of new types of sensors.

ICP values analysis is strictly related to the investigating pathology, i.e. in case of suspect hydrocephalus a 15 mmHg value is to be deemed as an excessive one; whereas in case of suspect cerebral damage, the intensive care starts round about at 25 mmHg. Only in the last few years the scientific community has turned attention to the different components included in the ICP signal. Limiting the survey to the mean ICP value or to a fixed time windows could result in a heavy fault.

The aim of this work is to exploit an automatic system to make it easier, more quickly and costless the evaluation of ICP signal in cerebral pathology affected patients. The authors have developed a tool able to filter, analyze and extract features from ICP signal or recording.

2 ICP Measurement and the Used Sensor

For ICP monitoring, a small pressure transducer is inserted through the skull into the brain or ventricles to measure the cerebrospinal fluid (CSF) pressure. Pressure monitoring, either by the lumbar catheter or the intracranial method, requires admission to a hospital. It can detect an abnormal pattern of pressure waves as well as low or high pressure.

For the conducted study we have used the ICP MicroSensor which is a new miniature strain gauge device manufactured by Codman (Johnson and Johnson). It is slimmer and more flexible than fiber-optic sensors (e.g. Camino). These last ones are subject to fracture of the transducer at the neck of the fixation screw, while the MicroSensor is less likely to suffer from such breakage and is small enough to be inserted into the spinal column for lumbar monitoring.

The Codman MicroSensor ICP Transducer is a catheter with a micro miniature silicon strain gauge type sensor mounted at one end and an electrical connector at the other end. It is designed for use with Codman interface control monitor (ICP express). Moreover it may be interfaced to a wide variety of patient monitoring system for ICP waveform display and for consolidation of ICP data with other vital signs information [3].

The output signal of the transducer is the unbalanced output voltage of a resistive bridge sensor.

3 Infusion Test and Signal Acquisition

We studied 16 patients (X males and Y females, age range 24–78). All data analyzed come from continuous CSF pressure recordings of different patients who underwent an infusion test to investigate the altered dynamics of CSF. The test is performed to investigate the dynamic ICP trend under forced and modified condition. It requires the simultaneous infusion of artificial spinal fluid and measurement of CSF pressure and it is generally performed through a lumbar puncture by 1 or 2 needles inserted into the lumbar subarachnoid space (see Fig. 37.1). The infusion test is performed through the scheme shown in Fig. 37.1: the infusion pomp instills a 0.9% NaCl solution at settable constant rate (set at 1.5 ml/min) by means of a stiff saline-filled specific catheter which has mounted on it a pressure transducer.

Fig. 37.1
figure 1

It is shown the ICP monitoring diagram adopted to perform the infusion test, the most commonly performed test for evaluating NPH related features recording

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The test starts with calibration phase, fundamental to offset the atmospheric pressure. Then a couple of minutes is needed to determine the baseline ICP (ICPB), i.e. the medium value of ICP in not altered dynamic condition, after that the pump is switched on and it stays on until the ICP reaches a steady state medium value called Plateau ICP (ICPP) in fully agreement with safety condition for the patient. When this step is reached, the infusion is stopped but the recording is still going on to allow a further investigation on the dynamic of the reabsorbition phase.

4 Signal Processing

The digital signal processing (DSP) performed consists in: signal filtering, peaks identification, location of single pressure waves and extraction of features from each single wave (see Fig. 37.2). Noise and artifacts (i.e. unwanted patient’s movement, speeches and coughing during the recording) are pruned by means of signal filtering. Filtering is performed through a FIR equiripple low-pass filter, implemented with a suitable cut-off frequency.

Fig. 37.2
figure 2

(sx) Algorithm’s flowchart—(dx) Example of ICP signal and parameters computed on it

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Peaks and other features revelation is estimated through the use of an algorithm for high-precision signal period identification and single-waveform location [4]. The algorithm computes the running autocorrelation function on the acquired and filtered buffered signal to obtain the updated fundamental period of the signal. Additional error correction control is performed to cut off those maxima or minima values out of expected range. Once the fundamental period is knew, the algorithm process the samples to recognize the boundary of each single-wave (which composes the pressure signal) in the acquired signal. In the next step the algorithm performs the identification of relative maxima and minima of each single-wave and the successive calculation of the parameters of interest as indicated in Fig. 37.2.

5 Results

The outflow of the elaboration is composed by the 14 parameters trends: maxima, minima, ICPM, ?ICP, ?tMIN–MAX, ?tMAX–MIN, ?tMAX–MAX, ?tMIN–MIN, SWA, FWA, SLPUP, SLPDW, ROUT and RAP (Fig. 37.3).

Fig. 37.3
figure 3

Example of some trends

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6 Conclusions

We have addressed a study to allow a deep investigation in ICP signals. The authors’ algorithm developed allows an easy analysis of intracranial pressure. It can be intended as a valid, consistent, reliable and easy-computing tool that might be used by the medical team in all those cases that involve brain damages or diseases.