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. 2015 Mar 10;15(3):5803-19.
doi: 10.3390/s150305803.

Fracture of human femur tissue monitored by acoustic emission sensors

Dimitrios G Aggelis  1 , Maria Strantza  2 , Olivia Louis  3 , Frans Boulpaep  4 , Demosthenes Polyzos  5 , Danny van Hemelrijck  6
Affiliations

Fracture of human femur tissue monitored by acoustic emission sensors

Dimitrios G Aggelis et al. Sensors (Basel). .

Abstract

The study describes the acoustic emission (AE) activity during human femur tissue fracture. The specimens were fractured in a bending-torsion loading pattern with concurrent monitoring by two AE sensors. The number of recorded signals correlates well with the applied load providing the onset of micro-fracture at approximately one sixth of the maximum load. Furthermore, waveform frequency content and rise time are related to the different modes of fracture (bending of femur neck or torsion of diaphysis). The importance of the study lies mainly in two disciplines. One is that, although femurs are typically subjects of surgical repair in humans, detailed monitoring of the fracture with AE will enrich the understanding of the process in ways that cannot be achieved using only the mechanical data. Additionally, from the point of view of monitoring techniques, applying sensors used for engineering materials and interpreting the obtained data pose additional difficulties due to the uniqueness of the bone structure.

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Figures

Figure 1
Figure 1
Different angle views of the test.
Figure 2
Figure 2
Typical AE waveform.
Figure 3
Figure 3
Load history and (a) cumulative AE activity of different sensors; and (b) rise time (RT) of sensor #1, for femur specimen #8. The RT solid line in (b) is the sliding average with window of 30 points.
Figure 4
Figure 4
Fractured femur specimens: (a) diagonal crack through the diaphysis (#8) and (b) femur head detachment (#7).
Figure 5
Figure 5
Load history and (a) cumulative AE activity of different sensors and (b) RT of sensor #2, for femur specimen #7. The rise time solid line in (b) is the sliding average with window of 30 points.
Figure 6
Figure 6
Cross section of a femur specimen with different thickness measurements.
Figure 7
Figure 7
(a) Correlation between partial power of the band 300–500 kHz with the average thickness of the bones; (b) Illustration of partial power feature.
Figure 8
Figure 8
Different fracture patterns: (a) and (b) through the femur body; (c) and (d) on the femur head.
Figure 9
Figure 9
Plot AF vs. RA for three pairs of femur specimens, as monitored by sensor 2 (at the head). Couples for comparison: (a) specimen 2 and 7; (b) specimens 6 and 11; (c) specimens 1 and 8.
Figure 10
Figure 10
Frequency distribution of RA values for both sensors: (a) torsion fracture and (b) bending fracture.
Figure 11
Figure 11
Typical AE waveforms recorded by sensor #2 (beneath the head) during torsion fracture of the diaphysis (a,b), and bending fracture of the head (c,d).
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