Increased incidence of obesity and longer life expectancies will place increased demands on load bearing joints. In the present work, a method of pre-clinical evaluation to assess the condition of the joint and potentially inform on cases of joint deterioration, is described. Acoustic emission (AE) is a non-destructive test methodology that has been used extensively in engineering for condition monitoring of machinery and structures. It is a passive technique that uses piezoelectric sensors to detect energy released from internal structural defects as they deform and grow. The technique has been used with some success in the past to identify characteristic signals generated from the knee joint during activities such as standing and sitting, in candidate arthroplasty patients (1,2). In this study, 40 asymptomatic subjects had AE data generated from their knee joints analysed. Subject characteristics such as age, gender, and lifestyle were disclosed and evaluated against the AE data. Each subject was invited to take a seated position and a piezoelectric AE sensor (Pancom P15, 150kHz resonance, 19mm diameter) was attached to the subject's knee using a wax couplant and tape as close to the articulating surface and on a bony prominence to avoid signal attenuation in the soft tissue. Subjects were invited to sit and stand 3 times. AE data were collected and processed using an AMSY5 AE processor (Vallen, Germany). Tests were repeated on a separate occasion and selected subjects were invited to participate on a third occasion. The AE data of particular interest were the peak amplitudes and the frequency power spectrum of the waveform. Post-test inspection of subject characteristics allowed them to be separated into three broad categories: no previous history (group A), some instances of pain in the knee (group B), and those who have had previous minor surgery on the knee (group C). The corresponding AE results were grouped separately. It was found that groups A and B demonstrated similar signal amplitude characteristics while group C produced much higher, significantly different (p<0.05) amplitudes and amplitude distributions. Typical results are shown in figure 1. At present, broad trends could be identified and relationships emerged between the data and subject history (prior surgery, typical daily activity). Further work will continue with asymptomatic subjects and the work will be extended to pre-operative patients to identify whether certain trends are amplified in this population

Osteotomy in spine and skull base surgery is a highly demanding task that requires very high precision. Compared to conventional surgical tools, laser allows contactless hard tissue removal with fewer traumas to the patient and higher machining accuracy. However, a key issue remains unsolved: how to terminate the ablation while the underlying critical soft tissue is reached?. Our research group has realised a closed-loop control of a CO. 2. -laser osteotomy system under the guidance of an optical coherence tomography (OCT). The OCT provides three-dimensional information about the microstructures beneath the bone surface with a resolution on micrometre scale and an imaging depth of about 0.5 mm. The OCT and CO. 2. -laser systems are integrated using a coaxial setup and a registration between their working spaces (mean absolute error 19.6 μm) was performed. The laser ablation and OCT scan are performed in turn. After correction of image distortions and speckle noise reduction, the position of the critical structure can be segmented in the enhanced OCT scans. The laser parameters for the next round of ablation are foresightedly planned based on the overlying residual bone thickness. After patient motion compensation by tracking artificial landmarks in the OCT scans (accuracy: RMS 27.2 μm), the ablation pattern can be precisely carried out by the CO. 2. -laser. The system was evaluated by performing laser cochleostomy on native porcine cochlea and mean ablation accuracy of 30 μm has been achieved. However, for narrow incisions that are only several tens of micrometres wide, very few pixels are visible beneath the incision bottom in the OCT and a robust segmentation of the critical structure is impossible. We are now developing a hybrid control system, which monitors the ablation-induced acoustic emission (AE) as a secondary control mechanism in addition to the OCT. When a pre-defined “switching” depth is reached, the AE-based control module is activated. Instead of analysing the acquired signals with conventional Fourier transform, a wavelet transform-based approach has been developed, which compares the correlation coefficients of the wavelet spectra of successive laser pulses. At the transition from bone tissue to the underlying soft tissue layer, a significant change in the coefficients can be observed, which is regarded as the signal for terminating the ablation. In order to keep the injury to the soft tissue layer to a minimal level, the laser energy is reduced after the switching. Preliminary experiments revealed that the wavelet-based approach is capable of controlling the ablation using pulses with extremely low energy down to 0.04mJ/pulse, resulting in an injured tissue layer of less than 10 μm. We expect to achieve the ablation accuracy on tens of micrometre scale using the proposed hybrid control mechanism

INTRODUCTION. Osteoarthritis (OA) is a growing societal burden, due to the ageing population. Less invasive, less damaging, and cheaper methods for diagnosis are needed, and sound technology is an emerging tool in this field. Some studies investigate ultrasound signals, while others look at acoustic signals in the audible range. AIMS. The aim of the current research was to: 1) investigate the potential of visual scalogram analysis of Acoustic Emission (AE) frequencies within the human audible range (20–20000 Hz) to diagnose knee OA, 2) correlate the qualitative visual scalogram analysis of the AE with OA symptoms, and 3) to do this based on information gathered during gait. METHODS. The analysis was carried out on a database collected during a prospective sound study on healthy and osteoarthritic knees. Sound recordings obtained with a contact microphone mounted on the patella and attached to a digital pre-amplifier, whilst patients were walking on a treadmill, were visualised, manually sampled, and transformed into scalograms. Features of the scalograms were described and qualitatively analysed through chi-squared tests for association with healthy or OA knees (knee status), and with severity of OA pain and functional symptoms and impact on quality of life (QoL), activities of daily living (ADL) and sports using the Knee Injury and Osteoarthritis Outcome Score (KOOS) subscales. RESULTS. 28 patients (56 knees) were included in the analysis. Our method provides a wide variety of different scalogram features: if no events were recorded, the scalogram was classified as ‘quiet’ (Fig 1). In case of abnormal recordings, data analysis evaluated association with the total count of the three most common events that appeared: 1. Peak (Fig 2), 2. Scattered (Fig 3) or 3. Island (localized noise but not presenting as a peak) (Fig 4) – “scalogram features”. No association was found between global scalogram characteristics (quiet versus ‘any noise’) and knee status (healthy or OA) (χ. 2. =3.163, p=0.075), but was found between knee status and three specific scalogram features (χ. 2. =9.743, p=0.008). The strongest association was a higher frequency of the “scattered” feature in the OA group (χ. 2. =9.06, p=0.01). Scalogram characteristics had no significant association with the sports and recreation (χ. 2. =1.74, p=0.419) nor the activities of daily living (χ. 2. =1.80, p=0.406) KOOS subscales. Significant association was found between scalogram characteristic and the pain (χ. 2. =10.34, p=0.006), quality of life (χ. 2. =6.58, p=0.037), and symptoms (χ. 2. =7.54, p=0.023) subscales. CONCLUSION. Promising results from analysis of individual features and of KOOS subscales establish the potential of acoustic analysis in evaluation of OA knees. More analysis of the data is needed to better define the variety of scalogram features. The future consequences of this research would be the development of a fast and affordable, non-invasive, radiation-free and potentially portable approach to evaluation, diagnosis and longitudinal monitoring of knee disorders. For any figures or tables, please contact the authors directly