Innovative optical non-contact measurement of respiratory function using photometric stereo

Pulmonary functional testing is very common and widely used in today's clinical environment for testing lung function. The contact based nature of a Spirometer can cause breathing awareness that alters the breathing pattern, affects the amount of air inhaled and exhaled and has hygiene implications. Spirometry also requires a high degree of compliance from the patient, as they have to breathe through a hand held mouth piece. To solve these issues a non-contact computer vision based system was developed for Pulmonary Functional Testing. This employs an improved photometric stereo method that was developed to recover local 3D surface orientation to enable calculation of breathing volumes. Although Photometric Stereo offers an attractive technique for acquiring 3D data using low-cost equipment, inherent limitations in the methodology have served to limit its practical application, particularly in measurement or metrology tasks. Traditional Photometric Stereo assumes that lighting directions at every pixel are the same, which is not usually the case in real applications and especially where the size of object being observed is comparable to the working distance. Such imperfections of the illumination may make the subsequent reconstruction procedures used to obtain the 3D shape of the scene, prone to low frequency geometric distortion and systematic error (bias). Also, the 3D reconstruction of the object results in a geometric shape with an unknown scale. To overcome these problems a novel method of estimating the distance of the object from the camera was developed, which employs Photometric Stereo images without using other additional imaging modality. The method firstly identifies the Lambertian Diffused Maxima regions to calculate the object's distance from the camera, from which the corrected per-pixel light vector is derived and the absolute dimensions of the object can be subsequently estimated. We also propose a new calibration process to allow a dynamic (as an object moves in the field of view) calculation of light vectors for each pixel with little additional computational cost. Experiments performed on synthetic as well as real data demonstrate that the proposed approach offers improved performance, achieving a reduction in the estimated surface normal error by up to 45% as well as the mean height error of reconstructed surface of up to 6 mm. In addition, compared with traditional photometric stereo, the proposed method reduces the mean angular and height error so that it is low, constant and independent of the position of the object placement within a normal working range. A high (0.98) correlation between breathing volume calculated from Photometric Stereo and Spirometer data was observed. This breathing volume is then converted to absolute amount of air by using distance information obtained by Lambertian Diffused Maxima Region. The unique and novel feature of this system is that it views the patients from both front and back and creates a 3D structure of the whole torso. By observing the 3D structure of the torso over time, the amount of air inhaled and exhaled can be estimated

An improved photometric stereo through distance estimation and light vector optimization from diffused maxima region

© 2013 Elsevier B.V. All rights reserved. Although photometric stereo offers an attractive technique for acquiring 3D data using low-cost equipment, inherent limitations in the methodology have served to limit its practical application, particularly in measurement or metrology tasks. Here we address this issue. Traditional photometric stereo assumes that lighting directions at every pixel are the same, which is not usually the case in real applications, and especially where the size of object being observed is comparable to the working distance. Such imperfections of the illumination may make the subsequent reconstruction procedures used to obtain the 3D shape of the scene prone to low frequency geometric distortion and systematic error (bias). Also, the 3D reconstruction of the object results in a geometric shape with an unknown scale. To overcome these problems a novel method of estimating the distance of the object from the camera is developed, which employs photometric stereo images without using other additional imaging modality. The method firstly identifies Lambertian diffused maxima region to calculate the object distance from the camera, from which the corrected per-pixel light vector is able to be derived and the absolute dimensions of the object can be subsequently estimated. We also propose a new calibration process to allow a dynamic(as an object moves in the field of view) calculation of light vectors for each pixel with little additional computation cost. Experiments performed on synthetic as well as real data demonstrates that the proposed approach offers improved performance, achieving a reduction in the estimated surface normal error of up to 45% as well as mean height error of reconstructed surface of up to 6 mm. In addition, when compared to traditional photometric stereo, the proposed method reduces the mean angular and height error so that it is low, constant and independent of the position of the object placement within a normal working range

Study On the Uniformity Aluminum Nitrate Thin Film On 2-Inch Silicon Substrate Prepared by RF Magnetron Sputtering

Aluminum nitrate (AlN) has attracted the researcher's interest due to its unique properties in the semiconductor material and other high-performance devices. This results in numerous techniques to investigate the uniformity of AlN thin film. The deposition in this study is carried out on an AlN on a 2-inch silicon substrate using a magnetron sputtering technique. The RF magnetron sputtering can also produce better film quality and deposit a wide variety of insulators, metals, alloys and composites. In this study, the AlN film was deposited using the RF magnetron sputtering by using three different parameters for the growth of the AlN on the 2-inch Si substrate for uniformity analysis. The uniformity of AlN thin film includes analyses of  the structural, thickness, topology and surface morphology by using the characterization of X-ray diffraction (XRD), atomic force microscopy (AFM), surface profiler and field emission scanning electron microscopy (FE-SEM). Based on the result from three parameters that have been done, parameter one shows the best results. For the crystalline structure results, the peak (100) AlN indicates the highly textured phases similar to a single crystal, and the cross-section result in FE-SEM shows the homogenous thickness

Comparison of Open Versus Percutaneous Transpedicular Screw Fixation in Thoracolumbar Fractures

meantime to return to work following percutaneous transpedicular fixation versus open pedicle screw fixation. We evaluated the average time required to return to work following percutaneous transpedicular fixation versus open pedicle screw fixation in traumatic lumbar spine injury. Material and Methods:  A randomized controlled trial included 60 patients. At study entry baseline demographics (age, gender, & duration of injury) were recorded. 30 patients were in the percutaneous transpedicular fixation group (A), while 30 patients were in the open pedicle screw fixation group (B). All the patients were followed every month time taken to return to work (TTRW) was noted on a proforma. Results:  Mean time taken by patients to return to work after surgery in Group A was 2.9 days, while in group B it was 5.1 days in group B. The difference between the two groups was significant (p-value 0.001). Within Group A, male and female genders showed a significant difference (p-value 0.032) in the TTRW after surgery. However, Group B did not show a similar difference between male and female patients. Duration of procedure had a significant effect on the TTRW (p-value 0.001). Conclusion:  We found ‘ time is taken to return to work’ was 2.93 ± 0.82 in group A and 5.10 ± 0.71 in group B (P-value 0.001). There was a significant difference in both groups. Percutaneous transpedicular fixation is a fast, safe and effective method as compared to other methods

Capital structure decisions and determinants: an empirical study in Iran

The present study is aimed to investigate the determinants of capital structure of Iranian firms listed on Tehran Stock Exchange for the period between 2001 and 2010. A panel data set of 123 (1230 observation) companies for the 10 years period is collected from published annual reports of companies from Tehran Stock Exchange. The study explores the traditional financial theories (Trade-off theory and Pecking order theory) to investigate the determinants of capital structure. The variables of size, profit, growth, tangibility, and risk factors are included to represent the potential influence of traditional theories. The study analyzes the impact of the financial factors on the debt and equity structure of the Iranian firms.The results indicate that the size and risk are positively related to capital structure. In addition, profitability, growth and tangibility are negatively related to capital structure. The result of firm size is consistent with the trade-off theory and result of profitability is consistent with the pecking order theory

Data Protection and Privacy of the Internet of Healthcare Things (IoHTs)

The Internet of Things (IoT) is an emerging field consisting of Internet-based globally connected network architecture. A subset of IoT is the Internet of Healthcare Things (IoHT) that consists of smart healthcare devices having significant importance in monitoring, processing, storing, and transmitting sensitive information. It is experiencing novel challenges regarding data privacy protection. This article discusses different components of IoHT and categorizes various healthcare devices based on their functionality and deployment. This article highlights the possible points and reasons for data leakage, such as conflicts in laws, the use of sub-standard devices, lack of awareness, and the non-availability of dedicated local law enforcement agencies. This article draws attention to the escalating demand for a suitable regulatory framework and analyzes compliance problems of IoHT devices concerning healthcare data privacy and protection regulations. Furthermore, the article provides some recommendations to improve the security and privacy of IoHT implementation

Radiologic assessment of cervical canal stenosis using kang mri grading system: Do clinical symptoms correlate with imaging findings?

Introduction: Magnetic resonance imaging (MRI) is widely used in the evaluation of cervical canal stenosis and spinal cord compression. Kang et al. formulated a new MRI grading system for assessing canal stenosis which takes cord signal change into account. The purpose of the study was to determine the agreement between Kang\u27s grading system and neurological symptoms.Methods: A cross-sectional study was conducted at Aga Khan University Hospital between April 2014 and December 2015. Patients meeting inclusion criteria were enrolled. T2 sagittal and T2 axial MRI images were acquired and reported by a consultant neuroradiologist, in accordance with the MRI grading system suggested by Kang et al. Neurologic clinical symptoms were acquired by the history taken by the principal investigator. More than one neurologic symptoms and Kang MRI grade 2 or 3 were taken as positive evidence of cord compression resulting from canal stenosis.Results: Amongst 126 subjects, 54% were females. Mean age of patients was 50.3 ± 14.3 years (range 19-83 years). Average disease duration was 4.61 ± 3.73 (range 1-24 months). In the majority of the patients, the findings were found at the C5-C6 level. 65.1% of patients were identified positive for cervical canal stenosis by Kang grading system. Most common neurological symptoms were pain (99%) and numbness (56%). Cohen’s Kappa was run to evaluate the agreement between neurological symptoms and Kang grading system. There was a strong agreement between the two methods, K = 0.81 (95% CI 0.70-0.92), p \u3c 0.001.Conclusion: There was a substantial agreement between Kang\u27s grading system and the presence of clinical symptoms. The agreement was greatest in females, older patients, and those with longer duration of symptoms

Accelerating Retinal Fundus Image Classification Using Artificial Neural Networks (ANNs) and Reconfigurable Hardware (FPGA)

Diabetic Retinopathy (DR) and Glaucoma are common eye diseases that affect a blood vessel in the retina and are one of the leading causes of vision loss around the world. Glaucoma is a common eye condition where the optic nerve that connects the eye to the brain becomes damaged. Whereas, DR is a complication of diabetes caused by high blood sugar levels damaging the back of the eye In order to produce an accurate and early diagnosis, an extremely high number of retinal images needs to be processed. Given the required computational complexity of image processing algorithms and the need for high-performance architectures, this paper proposes and demonstrates the use of fully parallel Field Programmable Gate Arrays (FPGAs) to overcome the burden of real-time computing in conventional software architectures. The experimental results achieved through software implementation were validated on an FPGA device. The results show a remarkable improvement in terms of computational speed and power consumption. This paper presents various pre-processing methods to analyse fundus images which can serve as a diagnostic tool for detection of glaucoma and diabetic retinopathy. In the proposed adaptive thresholding based pre-processing method, features were selected by calculating the area of the segmented optic disk which were further classified by using feedforward Neural Network (NN). The analysis is carried out using feature extraction through existing methodologies such as adaptive thresholding, histogram, and wavelet transform. Results obtained through these methods were quantified to obtain optimum performance in terms of classification accuracy. The proposed hardware implementation outperforms existing methods and offers a significant improvement in terms of computational speed and power consumption