研究目的
Investigating the computation of the Analgesia Nociception Index (ANI) using standard photoplethysmography (PPG) and contactless PPG imaging (PPGI) for objective pain assessment.
研究成果
The study demonstrates the feasibility of using PPG and PPGI for ANI computation, offering an alternative to ECG-based methods. Future work includes improving PPGI signal quality and integrating multiple sources for more reliable ANI computation.
研究不足
The study acknowledges limitations in the sample rate of PPGI signals and the need for higher frame rates for accurate peak detection. Additionally, the ANI computation was not reliable for the animal trial due to high respiration rates.
1：Experimental Design and Method Selection:
The study involves the development and evaluation of algorithms for computing ANI using PPG and PPGI signals, comparing them with ECG-based ANI.
2：Sample Selection and Data Sources:
Data were recorded anonymously at the University Hospital of Aachen, Germany, from patients receiving anesthesia.
3：List of Experimental Equipment and Materials:
Equipment includes an MP70 patient monitor (Philips AG), a Primus or Cato anesthesia machine (Draeger Medical), syringe pumps (BBRaun), and a PPGI camera (AVT, Pike 210B).
4：Experimental Procedures and Operational Workflow:
The study involved recording ECG, PPG, and PPGI signals during surgical interventions, with preprocessing steps for signal analysis.
5：Data Analysis Methods:
The study used Matlab for data analysis, focusing on heart rate variability and beat-to-beat interval computation.
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