RESUMO
BACKGROUND: Osteoporosis is a condition characterized by low bone mineral density, which typically leads to fractures and reduced quality of life. Currently, diagnostic devices used to assess this condition (e.g., dual-energy X-ray absorptiometry) are very costly, making it infeasible to meet the demand for testing in most countries. Therefore, we proposed a preclinical validation of a prototype called Osseus in an attempt to enhance osteoporosis screening tests and alleviate their costs. Osseus is a device developed to assist bone mineral density classification. It integrates a microcontroller into other peripheral devices to measure the attenuation at the middle phalanx of the middle finger, with two antennas operating at the 2.45 GHz frequency. RESULTS: We conducted tests with plaster, poultry, and porcine bones. A comparison of the measurements of the original and mechanically altered samples demonstrated that the device can handle the complexity of the tissues within the bone structure and characterize its microarchitecture. CONCLUSIONS: Osseus is a device that has been preliminarily validated. Ionising radiation needed for DXA tests is replaced by non-ionising microwave electromagnetic radiation. Osseus enables early detection of osteoporosis, reduces costs, and optimizes high-complexity testing referrals. There is a lack of validation studies with the reference/gold standard that are currently under development.
Assuntos
Micro-Ondas , Osteoporose , Absorciometria de Fóton/métodos , Densidade Óssea , Humanos , Minerais , Osteoporose/diagnóstico por imagem , Projetos Piloto , Qualidade de VidaRESUMO
BACKGROUND: Effective and timely detection is vital for mitigating the severe impacts of Sexually Transmitted Infections (STI), including syphilis and HIV. Cyclic Voltammetry (CV) sensors have shown promise as diagnostic tools for these STI, offering a pathway towards cost-effective solutions in primary health care settings. OBJECTIVE: This study aims to pioneer the use of Fourier Descriptors (FDs) in analyzing CV curves as 2D closed contours, targeting the simultaneous detection of syphilis and HIV. METHODS: Raw CV signals are filtered, resampled, and transformed into 2D closed contours for FD extraction. Essential shape characteristics are captured through selected coefficients. A complementary geometrical analysis further extracts features like curve areas and principal axes lengths from CV curves. A Mahalanobis Distance Classifier is employed for differentiation between patient and control groups. RESULTS: The evaluation of the proposed method revealed promising results with classification performance metrics such as Accuracy and F1-Score consistently achieving values rounded to 0.95 for syphilis and 0.90 for HIV. These results underscore the potential efficacy of the proposed approach in differentiating between patient and control samples for STI detection. CONCLUSION: By integrating principles from biosensors, signal processing, image processing, machine learning, and medical diagnostics, this study presents a comprehensive approach to enhance the detection of both syphilis and HIV. This setts the stage for advanced and accessible STI diagnostic solutions.
Assuntos
Infecções por HIV , Sífilis , Humanos , Sífilis/diagnóstico , Infecções por HIV/diagnóstico , Análise de Fourier , Técnicas Eletroquímicas/métodos , Processamento de Sinais Assistido por ComputadorRESUMO
Osteoporosis is a disease characterized by impairment of bone microarchitecture that causes high socioeconomic impacts in the world because of fractures and hospitalizations. Although dual-energy X-ray absorptiometry (DXA) is the gold standard for diagnosing the disease, access to DXA in developing countries is still limited due to its high cost, being present only in specialized hospitals. In this paper, we analyze the performance of Osseus, a low-cost portable device based on electromagnetic waves that measures the attenuation of the signal that crosses the medial phalanx of a patient's middle finger and was developed for osteoporosis screening. The analysis is carried out by predicting changes in bone mineral density using Osseus measurements and additional common risk factors used as input features to a set of supervised classification models, while the results from DXA are taken as target (real) values during the training of the machine learning algorithms. The dataset consisted of 505 patients who underwent osteoporosis screening with both devices (DXA and Osseus), of whom 21.8% were healthy and 78.2% had low bone mineral density or osteoporosis. A cross-validation with k-fold = 5 was considered in model training, while 20% of the whole dataset was used for testing. The obtained performance of the best model (Random Forest) presented a sensitivity of 0.853, a specificity of 0.879, and an F1 of 0.859. Since the Random Forest (RF) algorithm allows some interpretability of its results (through the impurity check), we were able to identify the most important variables in the classification of osteoporosis. The results showed that the most important variables were age, body mass index, and the signal attenuation provided by Osseus. The RF model, when used together with Osseus measurements, is effective in screening patients and facilitates the early diagnosis of osteoporosis. The main advantages of such early screening are the reduction of costs associated with exams, surgeries, treatments, and hospitalizations, as well as improved quality of life for patients.
Assuntos
Osteoporose , Qualidade de Vida , Humanos , Densidade Óssea , Osteoporose/diagnóstico por imagem , Absorciometria de Fóton/métodos , Programas de Rastreamento , Aprendizado de Máquina , Radiação EletromagnéticaRESUMO
The improvement of laboratory diagnosis is a critical step for the reduction of syphilis cases around the world. In this paper, we present the development of an impedance-based method for detecting T. pallidum antigens and antibodies as an auxiliary tool for syphilis laboratory diagnosis. We evaluate the voltammetric signal obtained after incubation in carbon or gold nanoparticle-modified carbon electrodes in the presence or absence of Poly-L-Lysine. Our results indicate that the signal obtained from the electrodes was sufficient to distinguish between infected and non-infected samples immediately (T0') or 15 min (T15') after incubation, indicating its potential use as a point-of-care method as a screening strategy.
Assuntos
Nanopartículas Metálicas , Sífilis , Humanos , Treponema pallidum , Ouro , Anticorpos Antibacterianos , Sífilis/diagnóstico , CarbonoRESUMO
Applications on electromagnetic waves in the field of biotelemetry have increased in the latest years, being used to prevent, diagnose, and treatment of several diseases. In this context, biotelemetry allows minimally invasive monitoring of the physiologic, improving comfort and patient care and significantly reducing hospital costs. Aiming to assist the mineral bone density classification, through a radio frequency signal (RF), for a later diagnosis of osteoporosis, Osseus was proposed in 2018. This equipment is a combination of the application of techniques and concepts of several areas such as software, electrical, electronic, computational, and biomedical engineering, developed at a low cost, with easy access to the population, and non-invasive. However, when placed on evaluation, potential improvements were identified to increase the stability of Osseus operation. It is proposed the implementation of improvements in the antennas used by Osseus, aiming its miniaturization, improvement in the reception of the RF signal, and better stability of the equipment's operation. Then, two antennas were built, one of which was used as a project for the second, which is an array. The array showed significant improvements in the radiation parameters relevant to the application, being a candidate to replace the antennas currently in use at Osseus.