Osteoporosis Screening: Applied Methods and Technological Trends.

Bones are continuously remodeled (resorbed and regenerated) to allow fracture healing and skeleton adaptation to stress. When excessive resorption occurs, bone microstructure is deteriorated, leading to osteoporosis. At early stages, osteoporosis usually has no symptoms; most people are diagnosed when a fracture occurs due to disease severity. To prevent fractures, technologies have been developed to identify high risk population eligible to treatment. Fracture risk has been assessed by analyzing the interaction of different energy stimulus with bone tissues as well as by statistical models that evaluate multiple clinical risk factors. The most applied methods are Dual-energy X-ray Absorptiometry and Fracture Risk Assessment tool. As they present some limitations, other technologies have been proposed for such purpose. A survey of the currently applied and emerging methods is here presented in order to provide a scenario of the technological challenges and trends to diagnose osteoporosis.

Blind Equalization of Lung Crackle Sounds to Compensate Chest Attenuation.

Diseased lungs generate adventitious sounds that propagate through the thorax, reaching the surface where they may be heard or recorded. The attenuation imposed to the lung sounds by the thorax depends on the physical characteristics of each patient, hampering the analysis of quantitative indexes measured to assist the diagnosis of cardiorespiratory disorders. This work proposes the application of a blind equalizer (eigenvector algorithm - EVA) to reduce the effects of thorax attenuation on indexes measured from crackle sounds. Computer simulated crackles (acquired on the posterior chest wall after being applied to volunteer's mouth) and actual crackles belonging to a database were equalized. Quantitative indexes were measured from crackles before and after equalization. Comparison of indexes measured from simulated crackles reveals that the equalizer improves the results due to attenuation compensation and removal of Gaussian noise. Effects of equalization on indexes measured from actual crackles were qualitatively assessed. Results point out that blind equalization of crackles recorded on the thorax provides more consistent quantitative indexes to assist the diagnosis of different cardiorespiratory diseases.

Respiratory Waveform Estimation From Multiple Accelerometers: An Optimal Sensor Number and Placement Analysis.

Respiratory patterns are commonly measured to monitor and diagnose cardiovascular, metabolic, and sleep disorders. Electronic devices such as masks used to record respiratory waveforms usually require medical staff support and obstruct the patients' breathing, causing discomfort. New techniques are being investigated to overcome such limitations. An emerging approach involves accelerometers to estimate the respiratory waveform based on chest motion. However, most of the existing techniques employ a single accelerometer placed on an arbitrary thorax position. The present work investigates the use and optimal placement of multiple accelerometers located on the thorax and the abdomen. The study population is composed of 30 healthy volunteers in three different postures. By means of a custom-made microcontrolled system, data are acquired from an array of ten accelerometers located on predefined positions and a pneumotachograph used as reference. The best sensor locations are identified by optimal linear reconstruction of the reference waveform from the accelerometer data in the minimum mean square error sense. The analysis shows that right-hand side locations contribute more often to optimal respiratory waveform estimates, a sound finding given that the right lung has a larger volume than the left lung. In addition, we show that the respiratory waveform can be blindly extracted from the recorded accelerometer data by means of independent component analysis. In conclusion, linear processing of multiple accelerometers in optimal positions can successfully recover respiratory information in clinical settings, where the use of masks may be contraindicated.

Instantaneous frequency based index to characterize respiratory crackles.

BACKGROUND: Crackle is a lung sound widely employed by health staff to identify respiratory diseases. The two-cycle duration (2CD) is a quantitative index pointed out by the American Thoracic Society and the European Respiratory Society to classify respiratory crackles as fine or coarse. However, this index, measured in the time domain, is highly affected by noise and filters of recording systems. Such factors hamper the analysis of data reported by different research groups. This work proposes a new index based on the instantaneous frequency of crackles estimated by means of discrete-time pseudo Wigner-Ville distribution. METHOD: Comparisons between 2CD and the proposed index were carried out for simulated and actual crackles. Normal breathing sounds were added to simulated crackles; the resulting signals were then applied to a band-pass filter that mimics those belonging to lung sound acquisition systems. Thus, the impact of noise and filtering on these two indices was assessed for simulated crackles. Kruskal-Wallis and Dunn's tests as well as Gaussian mixture model (GMM) were applied to the two indices measured from 382 actual crackles belonging to open databases. RESULTS: The proposed index is much less susceptible to waveform distortions due to noise and filtering when compared to the 2CD. Thus, the statistical analyses allow the identification of two classes of crackles from actual databases; the same does not occur when using 2CD. CONCLUSIONS: The new proposed index has the potential to contribute for a better characterization of crackles generated by different respiratory diseases, assisting their diagnosis during clinical exams.

An automatic gain control circuit to improve ECG acquisition

Abstract Introduction Long-term electrocardiogram (ECG) recordings are widely employed to assist the diagnosis of cardiac and sleep disorders. However, variability of ECG amplitude during the recordings hampers the detection of QRS complexes by algorithms. This work presents a simple electronic circuit to automatically normalize the ECG amplitude, improving its sampling by analog to digital converters (ADCs). Methods The proposed circuit consists of an analog divider that normalizes the ECG amplitude using its absolute peak value as reference. The reference value is obtained by means of a full-wave rectifier and a peak voltage detector. The circuit and tasks of its different stages are described. Results Example of the circuit performance for a bradycardia ECG signal (40bpm) is presented; the signal has its amplitude suddenly halved, and later, restored. The signal is automatically normalized after 5 heart beats for the amplitude drop. For the amplitude increase, the signal is promptly normalized. Conclusion The proposed circuit adjusts the ECG amplitude to the input voltage range of ADC, avoiding signal to noise ratio degradation of the sampled waveform in order to allow a better performance of processing algorithms.

Validation of the inverse pulse wave transit time series as surrogate of systolic blood pressure in MVAR modeling.

Short-term cardiovascular regulation mediated by the sympathetic and parasympathetic branches of the autonomic nervous system has been investigated by multivariate autoregressive (MVAR) modeling, providing insightful analysis. MVAR models employ, as inputs, heart rate (HR), systolic blood pressure (SBP) and respiratory waveforms. ECG (from which HR series is obtained) and respiratory flow waveform (RFW) can be easily sampled from the patients. Nevertheless, the available methods for acquisition of beat-to-beat SBP measurements during exams hamper the wider use of MVAR models in clinical research. Recent studies show an inverse correlation between pulse wave transit time (PWTT) series and SBP fluctuations. PWTT is the time interval between the ECG R-wave peak and photoplethysmography waveform (PPG) base point within the same cardiac cycle. This study investigates the feasibility of using inverse PWTT (IPWTT) series as an alternative input to SBP for MVAR modeling of the cardiovascular regulation. For that, HR, RFW, and IPWTT series acquired from volunteers during postural changes and autonomic blockade were used as input of MVAR models. Obtained results show that IPWTT series can be used as input of MVAR models, replacing SBP measurements in order to overcome practical difficulties related to the continuous sampling of the SBP during clinical exams.

Characterization of crackles from patients with fibrosis, heart failure and pneumonia.

The spectral analysis of crackles sounds has been carried out based on the assumption that they are stationary signals, and the majority of the work on the crackles was accomplished before the publication of the Computerized Respiratory Sound Analysis (CORSA) guidelines. This works characterizes crackles acquired from patients with fibrosis, heart failure, and pneumonia, breathing at a constant rate, with a system developed according to the CORSA guidelines. Their maximum frequency was obtained by applying discrete pseudo Wigner-Ville distribution, suitable for non-stationary signals, and an objective method to estimate the maximum frequency, the modified geometric method. The effects of the breathing rate and the tidal volume on the spectra of the crackles were also investigated. The role of the high-pass filter cutoff frequency of the acquisition system on the characteristics of the acquired crackles was also assessed in this present study. Higher high-pass filter cutoff frequency allows for higher amplification which modifies the maximum frequency and the 2CD index. It is shown that the crackles acquired according to the CORSA guidelines have higher frequencies and shorter 2CD indexes than those previously reported, highlighting the need for the standardization and detailed report of the acquisition setup when quantifying lung sounds. The results pointed out that the maximum frequency and the 2CD indexes may allow crackles generated by fibrosis to be distinguished from the ones generated by the heart failure and pneumonia. It is not possible, however, by means of these two indexes, to differentiate between pneumonia and heart failure crackles.

Equipamento para avaliação de funcionalidade de incubadoras para recém-nascidos / Equipment to evaluation of newbor incubators functionality

A incubadora neonatal é um equipamento médico-assistencial usado para a manutenção da vida de recém-nascidos prematuros. Sua função é proporcionar um ambiente termoneutro que é obtido através do controle da temperatura e da umidade relativa do ar em níveis adequados. Isto permite que o bebê mantenha a temperatura corporal normal a baixas taxas metabólicas. Este ambiente contibui para um desenvolvimento rápido e com uma menor incidência de doenças. No presente trabalho, descreve-se um aparelho eletrônico constuído para testar incubadoras, que verifica as características do ambiente por elas proporcionado ao recém-nascido. O protótipo desenvolvido mede, no interior da incubadora, a temperatura do ar em cinco pontos diferentes, a umidade relativa, o nível sonoro e verifica o estado da velocidade do fluxo de ar. O equipamento pode funcionar no modo de coleta, onde armazena as grandezas citadas a cada minuto, permitindo uma transferência posterior dos dados para um microcomputador PC, ou no modo de teste, onde realiza testes baseados na norma NBR IEC 601-2-19. Neste último, o aparelho instrui o operador através de mensagens no visor e avisos sonoros quando ajustes devem ser feitos nos controles da incubadora, ou quando algum problema é detectado. Os resultados de testes realizados no modo de coleta, em algumas incubadoras, são apresentados.