Sascha Spors

Full Professor

University of Rostock
Country flagGermany

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About

Sascha Spors is a Full Professor at Universität Rostock, Germany. His research areas encompass software citation data quality, detection of hip replacement loosening through structure-borne sound, and assessment of physical activity post-surgery using integrated piezoelectric elements. Additionally, he investigates the use of free and open-source software in academic research and the current status of research data management in Mecklenburg-Vorpommern.

Articles (8)

Resultant hip joint forces can currently only be recorded in situ in a laboratory setting using instrumented total hip replacements (THRs) equipped with strain gauges. However, permanent recording is important for monitoring the structural condition of the implant, for therapeutic purposes, for self-reflection, and for research into managing the predicted increasing number of THRs worldwide. Therefore, this study aims to investigate whether a recently proposed THR with an integrated piezoelectric element represents a new possibility for the permanent recording of hip joint forces and the physical activities of the patient. Hip joint forces from nine different daily activities were obtained from the OrthoLoad database and applied to a total hip stem equipped with a piezoelectric element using a uniaxial testing machine. The forces acting on the piezoelectric element were calculated from the generated voltages. The correlation between the calculated forces on the piezoelectric element and the applied forces was investigated, and the regression equations were determined. In addition, the voltage outputs were used to predict the activity with a random forest classifier. The coefficient of determination between the applied maximum forces on the implant and the calculated maximum forces on the piezoelectric element was R2 = 0.97 (p < 0.01). The maximum forces on the THR could be determined via activity-independent determinations with a deviation of 2.49 ± 13.16% and activity-dependent calculation with 0.87 ± 7.28% deviation. The activities could be correctly predicted using the classification model with 95% accuracy. Hence, piezoelectric elements integrated into a total hip stem represent a promising sensor option for the energy-autonomous detection of joint forces and physical activities.

Year:

2024

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2024

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2024

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2023

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2023

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2022

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2021

Year:

2020

Collaborators (8)

Dagmar Waltemath

Professor of Medical Informatics

Universitätsmedizin Greifswald

GERMANY
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Erjia Yan

Assistant Professor

Drexel University

UNITED STATES
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Max Schröder

University of Rostock

GERMANY
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Frank Krüger

Professor

-

GERMANY
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Gero Szepannek

Professor

Hochschule Stralsund

GERMANY
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Ralf Schneider

University of Greifswald

GERMANY
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Daniel Kluess

-

GERMANY
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Christian Haubelt

University of Rostock

GERMANY
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