A First Approach to Miniaturized Optoacoustic Feedback Sensor for Smart Laser Osteotome : Fiber-Coupled Fabry-Pérot Etalon Sensor

Abstract

We used a custom-made, fiber-coupled Fabry-Perot etalon sensor to measure the acoustic shock waves (ASW) generated during laser ablation. Based on the ASW signal measured, we could differentiate hard bone, muscle, and fat tissues with an average classification error of 6.39 %. A frequency-doubled Nd:YAG laser (532 nm) with a 5 ns pulse duration, was used to produce craters on the surface of tissues derived from an extracted fresh porcine proximal femur. After recording the ASW signals generated during laser ablation, we split the Fourier spectrum of measured ASWs into six equal bands and each used as an input for Principal Component Analysis (PCA). We used PCA to reduce the dimensionality of each band, and the Mahalanobis distance measure to classify tissue types based on the PC-scores. The most accurate differentiation was possible in the band of 1.25–1.67 MHz. The first 840 data points measured were used as training data, while the last 360 were considered testing data. Based on a confusion matrix, the ASW-based scores yielded classification errors of 5 % (hard bone), 6.94 % (muscle) and 7.22 % (fat), respectively. The proposed method has the potential for real-time feedback during laser osteotomy.