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1. verify uniformity & artifacts
1. verify uniformity & artifacts
A proper sensor and patient positining shoule deliver a smooth, repeatable and uniform waveform with low to no artifacts. Use the examples below as a guideline.
common sources of artifacts
common sources of artifacts
🤒 Patient-Related Sources
🤒 Patient-Related Sources
Shivering or tremors (e.g., due to fever, hypothermia, Parkinsonism).
Coughing, hiccups, spontaneous movement, or posturing.
Agitation or ventilator dyssynchrony.
🛌 Bed and Equipment-Related Sources
🛌 Bed and Equipment-Related Sources
Bed motors (raising/lowering head/foot section).
Air mattresses/alternating pressure pumps.
Infusion pumps or syringe pumps mounted on bed rails.
Ventilator tubing movement or oscillatory modes (HFOV).
Cooling/warming blankets (circulating water or air).
🏥 Environmental Sources
🏥 Environmental Sources
Staff handling (turning, suctioning, physical exam).
Nearby equipment carts, monitors, or devices vibrating the bed frame.
Foot traffic or door slams causing floor resonance (important for highly sensitive sensors).
very good waveforms
very good waveforms
Clean, uniform waveforms with no artifacts.
They result in clean processed pulses with narrow confidence intervals.
good to average waveforms
good to average waveforms
Uniform waveforms with a lower quantity of artifacts
They result in acceptable processed pulses with medium confidence intervals.
bad waveforms
bad waveforms
Repeatable waveforms but with a high quantity of artifacts
They result in non ICP like processed pulses with wide confidence intervals
2. assess confidence intervals
2. assess confidence intervals
Check the confidence interval data displayed by the device.
Confidence interval represents the area where 95% of the pulses used to calculate parameters will fit. The norrower the better.
examples of narrow confidence intervals
examples of narrow confidence intervals
They indicate stable, reliable waveform data.
examples of wide confidence intervals
examples of wide confidence intervals
They suggest variability or low-quality data capture.
3. identify for initial deflection
3. identify for initial deflection
Assess for the presence of a large initial deflection before the first peak (P1).
If present, assess the P2 to P1 ratio (P2:P1) and Normalized Time-to-Peak (nTTP) values, noting that if a large initial deflection below the x-axis is present, these values can be artificially skewed low ⬇️
4. check for useful pulses
4. check for useful pulses
The percentage (%) of useful pulses also helps verify the quality of data collection.
high percentages
high percentages
Indicates adequate data quality for interpretation.
lower percentages
lower percentages
May require repeat measurement or repositioning of the headband.
5. review waveform shape
5. review waveform shape
Some waveforms may be clean and repeatable, however their shape is very distinct from a traditional invasive ICP waveform shape.
The processed pulses can have narrow confidence intervals but overall the shape distinct from a traditional invasive ICP waveform shape.
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