---
_id: '13101'
abstract:
- lang: eng
  text: "Introduction: In-line sensors, which are crucial for real-time (bio-) process
    monitoring, can suffer from anomalies. These signal spikes and shifts compromise
    process control. Due to the dynamic and non-stationary nature of bioprocess signals,
    addressing these issues requires specialized preprocessing. However, existing
    anomaly detection methods often fail for real-time applications.\r\n\r\nMethods:
    This study addresses a common yet critical issue: developing a robust and easy-to-implement
    algorithm for real-time anomaly detection and removal for in-line permittivity
    sensor measurement. Recombinant Pichia pastoris cultivations served as a case
    study. Trivial approaches, such as moving average filtering, do not adequately
    capture the complexity of the problem. However, our method provides a structured
    solution through three consecutive steps: 1) Signal preprocessing to reduce noise
    and eliminate context dependency; 2) Anomaly detection using threshold-based identification;
    3) Validation and removal of identified anomalies.\r\n\r\nResults and discussion:
    We demonstrate that our approach effectively detects and removes anomalies by
    compensating signal shift value, while remaining computationally efficient and
    practical for real-time use. It achieves an F1-score of 0.79 with a static threshold
    of 1.06 pF/cm and a double rolling aggregate transformer using window sizes w1
    = 1 and w2 = 15. This flexible and scalable algorithm has the potential to bridge
    a crucial gap in process real-time analytics and control."
article_number: '1609369'
article_type: original
author:
- first_name: Emils
  full_name: Bolmanis, Emils
  last_name: Bolmanis
- first_name: Selina
  full_name: Uhlendorff, Selina
  id: '85335'
  last_name: Uhlendorff
- first_name: Miriam
  full_name: Pein-Hackelbusch, Miriam
  id: '64952'
  last_name: Pein-Hackelbusch
  orcid: 0000-0002-7920-0595
- first_name: Vytautas
  full_name: Galvanauskas, Vytautas
  last_name: Galvanauskas
- first_name: Oskars
  full_name: Grigs, Oskars
  last_name: Grigs
citation:
  ama: Bolmanis E, Uhlendorff S, Pein-Hackelbusch M, Galvanauskas V, Grigs O. Anomaly
    detection and removal strategies for in-line permittivity sensor signal used in
    bioprocesses. <i>Frontiers in Bioengineering and Biotechnology</i>. 2025;13. doi:<a
    href="https://doi.org/10.3389/fbioe.2025.1609369">10.3389/fbioe.2025.1609369</a>
  apa: Bolmanis, E., Uhlendorff, S., Pein-Hackelbusch, M., Galvanauskas, V., &#38;
    Grigs, O. (2025). Anomaly detection and removal strategies for in-line permittivity
    sensor signal used in bioprocesses. <i>Frontiers in Bioengineering and Biotechnology</i>,
    <i>13</i>, Article 1609369. <a href="https://doi.org/10.3389/fbioe.2025.1609369">https://doi.org/10.3389/fbioe.2025.1609369</a>
  bjps: <b>Bolmanis E <i>et al.</i></b> (2025) Anomaly Detection and Removal Strategies
    for In-Line Permittivity Sensor Signal Used in Bioprocesses. <i>Frontiers in Bioengineering
    and Biotechnology</i> <b>13</b>.
  chicago: Bolmanis, Emils, Selina Uhlendorff, Miriam Pein-Hackelbusch, Vytautas Galvanauskas,
    and Oskars Grigs. “Anomaly Detection and Removal Strategies for In-Line Permittivity
    Sensor Signal Used in Bioprocesses.” <i>Frontiers in Bioengineering and Biotechnology</i>
    13 (2025). <a href="https://doi.org/10.3389/fbioe.2025.1609369">https://doi.org/10.3389/fbioe.2025.1609369</a>.
  chicago-de: Bolmanis, Emils, Selina Uhlendorff, Miriam Pein-Hackelbusch, Vytautas
    Galvanauskas und Oskars Grigs. 2025. Anomaly detection and removal strategies
    for in-line permittivity sensor signal used in bioprocesses. <i>Frontiers in Bioengineering
    and Biotechnology</i> 13. doi:<a href="https://doi.org/10.3389/fbioe.2025.1609369">10.3389/fbioe.2025.1609369</a>,
    .
  din1505-2-1: '<span style="font-variant:small-caps;">Bolmanis, Emils</span> ; <span
    style="font-variant:small-caps;">Uhlendorff, Selina</span> ; <span style="font-variant:small-caps;">Pein-Hackelbusch,
    Miriam</span> ; <span style="font-variant:small-caps;">Galvanauskas, Vytautas</span>
    ; <span style="font-variant:small-caps;">Grigs, Oskars</span>: Anomaly detection
    and removal strategies for in-line permittivity sensor signal used in bioprocesses.
    In: <i>Frontiers in Bioengineering and Biotechnology</i> Bd. 13. Lausanne, Frontiers
    Media SA (2025)'
  havard: E. Bolmanis, S. Uhlendorff, M. Pein-Hackelbusch, V. Galvanauskas, O. Grigs,
    Anomaly detection and removal strategies for in-line permittivity sensor signal
    used in bioprocesses, Frontiers in Bioengineering and Biotechnology. 13 (2025).
  ieee: 'E. Bolmanis, S. Uhlendorff, M. Pein-Hackelbusch, V. Galvanauskas, and O.
    Grigs, “Anomaly detection and removal strategies for in-line permittivity sensor
    signal used in bioprocesses,” <i>Frontiers in Bioengineering and Biotechnology</i>,
    vol. 13, Art. no. 1609369, 2025, doi: <a href="https://doi.org/10.3389/fbioe.2025.1609369">10.3389/fbioe.2025.1609369</a>.'
  mla: Bolmanis, Emils, et al. “Anomaly Detection and Removal Strategies for In-Line
    Permittivity Sensor Signal Used in Bioprocesses.” <i>Frontiers in Bioengineering
    and Biotechnology</i>, vol. 13, 1609369, 2025, <a href="https://doi.org/10.3389/fbioe.2025.1609369">https://doi.org/10.3389/fbioe.2025.1609369</a>.
  short: E. Bolmanis, S. Uhlendorff, M. Pein-Hackelbusch, V. Galvanauskas, O. Grigs,
    Frontiers in Bioengineering and Biotechnology 13 (2025).
  ufg: '<b>Bolmanis, Emils u. a.</b>: Anomaly detection and removal strategies for
    in-line permittivity sensor signal used in bioprocesses, in: <i>Frontiers in Bioengineering
    and Biotechnology</i> 13 (2025).'
  van: Bolmanis E, Uhlendorff S, Pein-Hackelbusch M, Galvanauskas V, Grigs O. Anomaly
    detection and removal strategies for in-line permittivity sensor signal used in
    bioprocesses. Frontiers in Bioengineering and Biotechnology. 2025;13.
date_created: 2025-07-31T09:23:31Z
date_updated: 2025-10-10T07:46:08Z
ddc:
- '570'
department:
- _id: DEP4028
- _id: DEP4000
doi: 10.3389/fbioe.2025.1609369
file:
- access_level: closed
  content_type: application/pdf
  creator: f6x-0e0
  date_created: 2025-07-31T09:24:49Z
  date_updated: 2025-07-31T11:35:18Z
  file_id: '13102'
  file_name: fbioe-1-1609369.pdf
  file_size: 2935650
  relation: main_file
file_date_updated: 2025-07-31T11:35:18Z
has_accepted_license: '1'
intvolume: '        13'
keyword:
- in-situ
- permittivity
- dielectric spectroscopy
- signal preprocessing
- dynamic threshold
- static threshold
- anomaly validation
- Pichia pastoris
language:
- iso: eng
main_file_link:
- open_access: '1'
  url: https://doi.org/10.3389/fbioe.2025.1609369
oa: '1'
place: Lausanne
publication: Frontiers in Bioengineering and Biotechnology
publication_identifier:
  eissn:
  - 2296-4185
publication_status: published
publisher: Frontiers Media SA
quality_controlled: '1'
status: public
title: Anomaly detection and removal strategies for in-line permittivity sensor signal
  used in bioprocesses
type: scientific_journal_article
user_id: '64952'
volume: 13
year: '2025'
...