Initial findings creating a temperature prediction model using vibroacoustic signals originating from tissue needle interactions
Abstract This research explores the acquisition and analysis of vibroacoustic signals generated during tissue-tool interactions, using a conventional aspiration needle enhanced with a proximally mounted MEMS audio sensor, to extract temperature information. Minimally invasive temperature monitoring...
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| Format: | Article |
| Language: | English |
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Nature Portfolio
2025-03-01
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| Series: | Scientific Reports |
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| Online Access: | https://doi.org/10.1038/s41598-025-92202-6 |
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| _version_ | 1850029972352139264 |
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| author | Michael Friebe Witold Serwatka Katharina Steeg Gabriele Krombach Hamza Oran Oğuzhan Berke Özdil Katarzyna Heryan Axel Boese Alfredo Illanes Dominik Rzepka |
| author_facet | Michael Friebe Witold Serwatka Katharina Steeg Gabriele Krombach Hamza Oran Oğuzhan Berke Özdil Katarzyna Heryan Axel Boese Alfredo Illanes Dominik Rzepka |
| author_sort | Michael Friebe |
| collection | DOAJ |
| description | Abstract This research explores the acquisition and analysis of vibroacoustic signals generated during tissue-tool interactions, using a conventional aspiration needle enhanced with a proximally mounted MEMS audio sensor, to extract temperature information. Minimally invasive temperature monitoring is critical in thermotherapy applications, but current methods often rely on additional sensors or simulations of typical tissue behavior. In this study, a commercially available needle was inserted into water-saturated foams with temperatures ranging from 25 to 55 °C, varied in 5° increments. Given that temperature affects the speed of sound, water’s heat capacity, and the mechanical properties of most tissues, it was hypothesized that the vibroacoustic signals recorded during needle insertion would carry temperature-dependent information. The acquired signals were segmented, processed, and analyzed using signal processing techniques and a deep learning algorithm. Results demonstrated that the audio signals contained distinct temperature-dependent features, enabling temperature prediction with a root mean squared error of approximately 3 °C. We present these initial laboratory findings, highlighting significant potential for refinement. This novel approach could pave the way for a real-time, minimally invasive method for thermal monitoring in medical applications. |
| format | Article |
| id | doaj-art-ab5783fa23d54b3ba970e2f1f1e57b79 |
| institution | DOAJ |
| issn | 2045-2322 |
| language | English |
| publishDate | 2025-03-01 |
| publisher | Nature Portfolio |
| record_format | Article |
| series | Scientific Reports |
| spelling | doaj-art-ab5783fa23d54b3ba970e2f1f1e57b792025-08-20T02:59:22ZengNature PortfolioScientific Reports2045-23222025-03-0115111110.1038/s41598-025-92202-6Initial findings creating a temperature prediction model using vibroacoustic signals originating from tissue needle interactionsMichael Friebe0Witold Serwatka1Katharina Steeg2Gabriele Krombach3Hamza Oran4Oğuzhan Berke Özdil5Katarzyna Heryan6Axel Boese7Alfredo Illanes8Dominik Rzepka9Faculty of Computer Science, AGH University of KrakówFaculty of Computer Science, AGH University of KrakówUniversity of GiessenUniversity of GiessenFaculty of Computer Science, AGH University of KrakówFaculty of Computer Science, AGH University of KrakówFaculty of Computer Science, AGH University of KrakówINKA Innovation Lab, Faculty of Medicine, Otto-von-Guericke-UniversityINKA Innovation Lab, Faculty of Medicine, Otto-von-Guericke-UniversityFaculty of Computer Science, AGH University of KrakówAbstract This research explores the acquisition and analysis of vibroacoustic signals generated during tissue-tool interactions, using a conventional aspiration needle enhanced with a proximally mounted MEMS audio sensor, to extract temperature information. Minimally invasive temperature monitoring is critical in thermotherapy applications, but current methods often rely on additional sensors or simulations of typical tissue behavior. In this study, a commercially available needle was inserted into water-saturated foams with temperatures ranging from 25 to 55 °C, varied in 5° increments. Given that temperature affects the speed of sound, water’s heat capacity, and the mechanical properties of most tissues, it was hypothesized that the vibroacoustic signals recorded during needle insertion would carry temperature-dependent information. The acquired signals were segmented, processed, and analyzed using signal processing techniques and a deep learning algorithm. Results demonstrated that the audio signals contained distinct temperature-dependent features, enabling temperature prediction with a root mean squared error of approximately 3 °C. We present these initial laboratory findings, highlighting significant potential for refinement. This novel approach could pave the way for a real-time, minimally invasive method for thermal monitoring in medical applications.https://doi.org/10.1038/s41598-025-92202-6Tissue temperatureThermotherapyThermal monitoringMinimal-invasive therapyVibroacoustic signals |
| spellingShingle | Michael Friebe Witold Serwatka Katharina Steeg Gabriele Krombach Hamza Oran Oğuzhan Berke Özdil Katarzyna Heryan Axel Boese Alfredo Illanes Dominik Rzepka Initial findings creating a temperature prediction model using vibroacoustic signals originating from tissue needle interactions Scientific Reports Tissue temperature Thermotherapy Thermal monitoring Minimal-invasive therapy Vibroacoustic signals |
| title | Initial findings creating a temperature prediction model using vibroacoustic signals originating from tissue needle interactions |
| title_full | Initial findings creating a temperature prediction model using vibroacoustic signals originating from tissue needle interactions |
| title_fullStr | Initial findings creating a temperature prediction model using vibroacoustic signals originating from tissue needle interactions |
| title_full_unstemmed | Initial findings creating a temperature prediction model using vibroacoustic signals originating from tissue needle interactions |
| title_short | Initial findings creating a temperature prediction model using vibroacoustic signals originating from tissue needle interactions |
| title_sort | initial findings creating a temperature prediction model using vibroacoustic signals originating from tissue needle interactions |
| topic | Tissue temperature Thermotherapy Thermal monitoring Minimal-invasive therapy Vibroacoustic signals |
| url | https://doi.org/10.1038/s41598-025-92202-6 |
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