Assessment of non-contacting optical methods to measure wear and surface roughness in ceramic total disc replacements

This study presents a method for measuring the low volumetric wear expected in ceramic total disc replacements, which can be used to replace intervertebral discs in the spine, using non-contacting optical methods. Alumina-on-alumina ball-on-disc tests were conducted with test conditions approximating those of cervical (neck region of the spine) total disc replacement wear tests. The samples were then scanned using a three-dimensional non-contacting optical profilometer and the data used to measure surface roughness and develop a method for measuring the wear volume. The results showed that the magnification of the optical lens affected the accuracy of both the surface roughness and wear volume measurements. The method was able to successfully measure wear volumes of 0.0001mm3, which corresponds to a mass of 0.0001 mg, which would have been undetectable using the gravimetric method. A further advantage of this method is that with one scan the user can measure changes in surface topography, volumetric wear and the location of the wear on the implant surface. This method could also be applied to more severe wear, other types of orthopaedic implants and different materials

Efficacy and patient satisfaction with autoadjusting CPAP with variable expiratory pressure vs standard CPAP: a two-night randomized crossover trial

Expiratory pressure relief (C-Flex) technology monitors the patient’s airflow during expiration and reduces the pressure in response to the patient. Increased comfort levels associated with C-Flex therapy have potential to improve patient adherence to therapy. The purpose of this study was to assess the combination of autoadjusting CPAP (APAP) and C-Flex in terms of (1) treatment efficacy, and (2) patient preference when compared to standard CPAP. Fifteen patients who had previously undergone formal CPAP titration polysomnography were treated with either one night of the APAP with C-Flex or one night of conventional CPAP, in a crossover trial. Patient satisfaction levels were recorded using visual analog scales (VAS) on the morning after the study. Mean patient age was 50 ± 12 years, body mass index (BMI) was 36 ± 6 kg/m(2), baseline AHI was 53 ± 31 events/h, and CPAP Pressure was 11 ± 2 cm/H(2)O. APAP with C-Flex was as effective as CPAP, with no differences detected in sleep latency (17 ± 5 vs 12.3 ± 3 min, p = 0.4), or respiratory indices (AHI of 4.2 ± 2 vs 2.4 ± 0.7 events/h, p = 0.1). VAS scores (scale 0–10) indicated a trend towards increased patient satisfaction while using APAP with C-Flex (7.9 vs 7.2, p = 0.07). 10 patients expressed a preference for APAP with C-Flex (VAS, 0 to10) over standard CPAP (total positive score of 68, mean score of 4.8 ± 4.3). One patient expressed no preference. Four patients expressed a preference for CPAP (total positive score of 13, mean score of 0.9 ± 1.9) (APAP with C-Flex vs standard CPAP, p < 0.01 paired t test). APAP with C-Flex eliminates sleep disordered breathing as effectively as standard CPAP. Patients indicated a preference for APAP with C-Flex suggesting a possible advantage in terms of patient adherence for this mode of treatment

Interaction of stable aggregates drives the precipitation of calcium phosphate in supersaturated solutions

Calcium phosphate is the main mineral phase within our bodies, but despite many studies there is not yet a consensus on how it nucleates. We have used molecular dynamics simulations to investigate the interactions of ions in solution and the stability of nanoparticles. At high concentrations, we show that calcium and hydrogen phosphate ions associate to form negatively charged clusters that grow further through a combination of ion attachment and particle–particle interactions. Additional analysis of a cluster of 16 ions at experimental concentrations showed that this is (meta)stable in solution and actually densifies during the simulation. Free energy calculations probing the stability of the nanoparticles further demonstrated that they occupy a free energy minimum lower than the free ions or ion pairs in solution suggesting that calcium phosphate nucleation and growth may occur through the aggregation of small negatively charged clusters

Multi-feature snore sound analysis in obstructive sleep apnea-hypopnea syndrome

Snoring is the most common symptom of obstructive sleep apnea hypopnea syndrome (OSAHS), which is a serious disease with high community prevalence. The standard method of OSAHS diagnosis, known as polysomnography (PSG), is expensive and time consuming. There is evidence suggesting that snore-related sounds (SRS) carry sufficient information to diagnose OSAHS. In this paper we present a technique for diagnosing OSAHS based solely on snore sound analysis. The method comprises a logistic regression model fed with snore parameters derived from its features such as the pitch and total airway response (TAR) estimated using a higher order statistics (HOS)-based algorithm. Pitch represents a time domain characteristic of the airway vibrations and the TAR represents the acoustical changes brought about by the collapsing upper airways. The performance of the proposed method was evaluated using the technique of K-fold cross validation, on a clinical database consisting of overnight snoring sounds of 41 subjects. The method achieved 89.3% sensitivity with 92.3% specificity (the area under the ROC curve was 0.96). These results establish the feasibility of developing a snore-based OSAHS community-screening device, which does not require any contact measurements

Inter-hemispheric asynchrony of the brain during events of apnoea and EEG arousals

Sleep apnoea hypopnea syndrome ( SAHS) is a serious sleep disorder affecting a large percentage of the population. Apnoea/hypopnea and electroencephalographic-arousal ( EEGA) events occur frequently in SAHS patients. These events significantly disturb the sleep architecture, as revealed through nocturnal EEG signals. Even though EEG carries vital information on the state of the brain, its use in clinical SAHS diagnosis is limited mainly to routine sleep staging. In this paper, we address this issue. We propose a novel measure, called the inter-hemispheric asynchrony (psi (a -> b)), to capture EEG-symmetry changes associated with a transition a -> b between the brain states 'a' and 'b'. Our work takes into account macro-states such as the traditional sleep stages, and micro-states such as EEGA and apnoea/hypopnea events. We measured EEG data using electrodes C4-A2 and C3-A1 of the International 10/20 System from 18 subjects undergoing polysomnography ( PSG) testing. These electrode pairs are symmetrical about the brain mid-line and allow us to discern any hemispheric EEG asymmetry. EEG data were segmented and filtered into classical bands delta( 0.5-4 Hz), theta( 4.1-8 Hz), alpha( 8.1-12 Hz) and beta( 12.1-16 Hz). Then they were further categorized according to the particular sleep state of their origin. Spectral correlation coefficients were computed between the EEG data from the two hemispheres and averaged over the overnight EEG recording. This was done for each frequency band and state of interest, and then the measure psi(a -> b) was computed. Results from the 18 subjects showed that psi(a -> b) increased significantly ( p b) changes significantly ( p b) provides a novel insight into the functional asymmetry of the brain during SAHS events

Normal probability testing of snore signals for diagnosis of obstructive sleep apnea

Obstructive Sleep Apnea (OSA) is a highly prevalent disease in which upper airways are collapsed during sleep, leading to serious consequences. The standard method of OSA diagnosis is known as Polysomnography (PSG), which requires an overnight stay in a specifically equipped facility, connected to over 15 channels of measurements. PSG requires (i) contact instrumentation and, (ii) the expert human scoring of a vast amount of data based on subjective criteria. PSG is expensive, time consuming and is difficult to use in community screening or pediatric assessment. Snoring is the most common symptom of OSA. Despite the vast potential, however, it is not currently used in the clinical diagnosis of OSA. In this paper, we propose a novel method of snore signal analysis for the diagnosis of OSA. The method is based on a novel feature that quantifies the non-Gaussianity of individual episodes of snoring. The proposed method was evaluated using overnight clinical snore sound recordings of 86 subjects. The recordings were made concurrently with routine PSG, which was used to establish the ground truth via standard clinical diagnostic procedures. The results indicated that the developed method has a detectability accuracy of 97.34%

Multi-feature snore sound analysis in obstructive sleep apnea-hypopnea syndrome

Snoring is the most common symptom of obstructive sleep apnea hypopnea syndrome (OSAHS), which is a serious disease with high community prevalence. The standard method of OSAHS diagnosis, known as polysomnography (PSG), is expensive and time consuming. There is evidence suggesting that snore-related sounds (SRS) carry sufficient information to diagnose OSAHS. In this paper we present a technique for diagnosing OSAHS based solely on snore sound analysis. The method comprises a logistic regression model fed with snore parameters derived from its features such as the pitch and total airway response (TAR) estimated using a higher order statistics (HOS)-based algorithm. Pitch represents a time domain characteristic of the airway vibrations and the TAR represents the acoustical changes brought about by the collapsing upper airways. The performance of the proposed method was evaluated using the technique of K-fold cross validation, on a clinical database consisting of overnight snoring sounds of 41 subjects. The method achieved 89.3% sensitivity with 92.3% specificity (the area under the ROC curve was 0.96). These results establish the feasibility of developing a snore-based OSAHS community-screening device, which does not require any contact measurements