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Real-time algorithm for changes detection in depth of anesthesia signals

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Abstract

This paper presents a real-time algorithm for changes detection in depth of anesthesia signals. A Page–Hinkley test (PHT) with a forgetting mechanism (PHT-FM) was developed. The samples are weighted according to their “age” so that more importance is given to recent samples. This enables the detection of the changes with less time delay than if no forgetting factor was used. The performance of the PHT-FM was evaluated in a two-fold approach. First, the algorithm was run offline in depth of anesthesia (DoA) signals previously collected during general anesthesia, allowing the adjustment of the forgetting mechanism. Second, the PHT-FM was embedded in a real-time software and its performance was validated online in the surgery room. This was performed by asking the clinician to classify in real-time the changes as true positives, false positives or false negatives. The results show that 69 % of the changes were classified as true positives, 26 % as false positives, and 5 % as false negatives. The true positives were also synchronized with changes in the hypnotic or analgesic rates made by the clinician. The contribution of this work has a high impact in the clinical practice since the PHT-FM alerts the clinician for changes in the anesthetic state of the patient, allowing a more prompt action. The results encourage the inclusion of the proposed PHT-FM in a real-time decision support system for routine use in the clinical practice.

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Acknowledgments

The work of Raquel Sebastião and Margarida M. Silva is supported by FCT (Portuguese Foundation for Science and Technology) under the PhD Grants SFRH/BD/41569/2007 and SFRH/BD/60973/2009, respectively. This work is also funded by the ERDF through the Programme COMPETE and by FCT through - projects GALENO - Modeling and Control for Personalized Drug Administration (PTDC/SAU-BEB/103667/2008) and KDUDS - Knowledge Discovery from Ubiquitous Data Streams (PTDC/EIA-EIA/098355/2008). This work is part-funded by the ERDF - European Regional Development Fund through the COMPETE Programme (operational programme for competitiveness), by the Portuguese Funds through the FCT within project FCOMP - 01-0124-FEDER-022701. The authors gratefully acknowledge Dr. Simão Esteves and his colleagues from Hospital Geral de Santo António (HGSA), Centro Hospitalar do Porto, Portugal and Dr. Manuel Seabra and his colleagues from Hospital Pedro Hispano, Unidade Local de Saúde de Matosinhos, Portugal, for their participation in the data collection and collaboration in the results analysis.

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Authors and Affiliations

  1. LIAAD-INESC TEC, Universidade do Porto, Rua de Ceuta, 118, 6, 4050-190, Porto, Portugal

    Raquel Sebastião & João Gama

  2. Departamento de Matemática, Faculdade de Ciências, Universidade do Porto, Rua do Campo Alegre, 4169-007, Porto, Portugal

    Raquel Sebastião, Margarida M. Silva & Teresa Mendonça

  3. Division of Systems and Control, Department of Information Technology, Uppsala University, Box 337, 751 05, Uppsala, Sweden

    Margarida M. Silva

  4. Center for Research & Developments in Mathematics and Applications, Universidade de Aveiro, Campus Universitário de Santiago, 3810-193, Aveiro, Portugal

    Margarida M. Silva & Teresa Mendonça

  5. Unidade Local de Saúde de Matosinhos, EPE, Rua Dr. Eduardo Torres, 4464-513, Senhora da Hora, Portugal

    Rui Rabiço

  6. Faculdade de Economia, Universidade do Porto, Rua Dr. Roberto Frias, 4200-464, Porto, Portugal

    João Gama

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  1. Raquel Sebastião
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  2. Margarida M. Silva
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  3. Rui Rabiço
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  4. João Gama
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  5. Teresa Mendonça
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Correspondence to Raquel Sebastião.

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Sebastião, R., Silva, M.M., Rabiço, R. et al. Real-time algorithm for changes detection in depth of anesthesia signals. Evolving Systems 4, 3–12 (2013). https://doi.org/10.1007/s12530-012-9063-4

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  • DOI: https://doi.org/10.1007/s12530-012-9063-4

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