Sb97789
.pdfreference's key specifications include a temperature coefficient less than 50ppm/°C, low drift over time, and good line and load regulation. A 10or 12-bit DAC is used to set the bias voltage for an electrochemical test strip and to set the LED current for an optical-reflectometry test strip. Sometimes a comparator is employed with electrochemical test strips to detect when blood has been applied to the test strip. This saves power while waiting for blood to be applied to the test strip, and ensures that the reaction site is fully saturated with blood. The ADC requirements vary depending on the type of meter, but most require ≥ 14-bit resolution and low noise for repeatable results. Sometimes 12-bit resolution is used when there is a programmable gain stage before the ADC to extend the dynamic range.
Temperature Measurement
Ideally, the temperature of the blood on the test strip should be measured, but usually the ambient temperature near the test strip is measured. Temperature measurement accuracy varies by test-strip type and chemistry, but is typically in the ±1°C to ±2°C range. This measurement can be accomplished with stand-alone temperaturesensor ICs, or with a remote thermistor or PN junction together with an ADC. Using a thermistor in a half-bridge configuration driven by the same reference as the ADC provides more accurate results because this design eliminates any voltage-reference errors. Remote or internal PN junctions can be measured with highly precise integrated analog front-ends (AFEs).
Electrochemical Test-Strip Configurations
Most test strips are proprietary and vary by meter manufacturer. The variations include the reagent formulation, the number of electrodes, the number of channels, and biasing method of the reagent. The simplest configuration is a selfbiased test strip which has two electrodes with current measured at the working electrode and the common electrode grounded. There can be multiple channels on a single test strip; the additional channels are used for a reference measurement, initial blood detection, or to ensure that the blood has saturated the reaction site.
An alternate configuration actively drives both electrodes and measures at the common electrode.
Another more advanced design is a counter configuration. Here there are three electrodes with current measured at the working electrode and a force-sense circuit drives the common and reference electrodes. There is an important advantage to this configuration: the bias voltage at the reaction site on the test strip is set and maintained more accurately throughout the measurement. The disadvantage of this design is its additional complexity and the larger headroom required to allow the
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force-sense amplifier to swing negative to maintain the bias voltage during current flow.
Integrated AFE
Maxim's precision AFEs integrate all the functionality discussed in the previous sections, and are designed for the specifications and performance required in blood glucose meters. The AFEs are also suitable for similar applications such as coagulation and cholesterol meters.
Display and Backlighting
Most blood glucose meters use a simple liquid-crystal display (LCD) with about 100 segments that can be driven with an LCD driver integrated in the microcontroller. Some meters feature a more complicated dot-matrix LCD which usually requires using a module with the glass, bias voltages, and drivers assembled together. The dot-matrix display also requires additional memory to store the messages to be displayed. There are also color displays that require additional and higher voltages than both the segment or dot-matrix LCDs. Backlighting can be added by using one or two white LEDs (WLEDs) or an electroluminescent source.
Data Interface
The ability to upload test results to a computer has existed for many years, but utilization of this data interface has been low. Initially to keep the cost of the meter down, the incremental cost for this functionality was designed into a proprietary cable. Today meters are moving from proprietary data interfaces to industrystandard interfaces such as USB and Bluetooth®. The added cost of these open interfaces is now moving into the meters, a movement driven, in part, by the Continua Health Alliance® and the push to conveniently upload patient data to your health-care provider.
Audio
Audible indicators range from simple buzzers to more advanced talking meters for the vision impaired. A simple buzzer can be driven by one or two microcontroller port pins with pulse-width modulation (PWM) capability. More advanced voice indicators and even voice recording for test result notes can be achieved by adding an audio codec along with speaker and microphone amplifiers.
Power and Battery Management
Meters with simple displays can run directly off of a single lithium coin cell or two alkaline AAA primary batteries. To maximize battery life, this meter requires electronics capable of running from 3.6V down to 2.2V for the lithium coin cell or 1.8V for the alkaline AAAs. If the electronics require a higher or regulated
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supply voltage, then a step-up switching regulator can be used. Powering down the switching regulator during sleep mode and running directly off the batteries extends battery life, as long as the sleep circuitry can run from the lower battery voltages. Adding a backlit or a more advanced display will require higher and sometimes additional voltages. A more advanced power-management scheme may be required at this point. Rechargeable batteries such as single-cell lithium ion (Li+) can be used by adding a battery charger and fuel-gauge circuitry. Charging with USB is certainly a convenient option for the user, if USB is available in the meter. If the battery is removable, then authentication may be required for safety and aftermarket control.
Electrostatic Discharge
All meters must pass 61000-4-2 electrostatic discharge (ESD) requirements. Using electronics with built-in ESD protection or adding ESD line protectors to exposed traces can help meet this requirement.
Functional Scalability
Once the core meter design is complete using a precision, integrated AFE, the goal is not to redesign that portion of the meter when another feature is needed later. Instead, standard parts with a singular function targeted for portable medical devices can be used to add a feature with minimal disruption. That minimal disruption translates into lower risk, easier FDA approvals, and faster time to market. It also means that more meters will be available with the features that patients want and need. Blood glucose testing will be more frequent with the predictable result of increased compliance to acceptable glucose levels and better individual health.
Дополнительные задания к тексту:
1.Выпишите сокращения из текста статьи. Что они означают?
2.Подготовьте глоссарий терминов и значимых слов для обсуждения по теме: «Значение использования глюкометра и перспективы развития их производства».
3.Оцените значение глюкометра с точки зрения развития медицины. Выявите недостатки и предложите варианты их устранения.
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Тема 4. Фонокардиограф
Прочитайте отрывок из научной статьи, переведите на русский язык, выпишите профессионализмы и термины. Разделите материал статьи на смысловые части (введение, основные положения работы, аргументы, научная новизна, выводы), выпишите ключевые слова, составьте аннотацию. Перескажите основное содержание статьи.
Wireless laptop-based phonocardiograp hand diagnosis
Auscultation is used to evaluate heart health, and can indicate when it’s needed to refer a patient to a cardiologist. Advanced phonocardiograph (PCG) signal processing algorithms are developed to assist the physician in the initial diagnosis but they are primarily designed and demonstrated with research quality equipment. Therefore, there is a need to demonstrate the applicability of those techniques with consumer grade instrument. Furthermore, routine monitoring would benefit from a wireless PCG sensor that allows continuous monitoring of cardiac signals of patients in physical activity, e.g., treadmill or weight exercise. In this work, a lowcost portable and wireless healthcare monitoring system based on PCG signal is implemented to validate and evaluate the most advanced algorithms. Off-the-shelf electronics and a notebook PC are used with MATLAB codes to record and analyze PCG signals which are collected with a notebook computer in tethered and wireless mode. Physiological parameters based on the S1 and S2 signals and MATLAB codes are demonstrated. While the prototype is based on MATLAB, the later is not an absolute requirement.
Phonocardiogram
The electrocardiogram (ECG) is a popular method for checking anomalies of cardiorespiratory function over many decades, and it works by keeping track of electrical heart activity. However, heart defects may be caused by structural abnormalities and therefore are more likely to produce vibromechanical indicators aside from electrical ones. As an example, heart auscultation is more useful than ECG for characterizing murmurs and other abnormal heart sounds. Heart sounds convey important physiological and pathological information. Heart murmurs caused by turbulent blood flow and anomalous valve opening or closing, can be noticeably detected by trained ears when adequate sensors are used. While auscultation is useful, detection of cardiac signatures via auscultation demands extensive physician’s experience, whether with an analog acoustic or electronic stethoscope. It is desirable to equip primary care physicians who do not have extensive auscul-
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tation skills with a diagnostic tool so they screen patients for referable conditions. On the other hand, an accurate detection of the cardiac cycle can improve the diagnosis with quantitative details useful for specialists. To meet that goal, many techniques of quantifying the cardiac cycle with improved accuracy have been explored. Examples of approach include improving detection of the cycle and reducing of noise. One of the useful cardiac reserve indicators is the diastole to systole ratio that evaluates the adequacy of the volume of blood reaching the heart during diastole. Autonomous detection and classification of cardiac reserve has been proposed. Inotropic agents belong to a class of drugs that affect the contraction of the heart muscle. At present, ECG is commonly used to test many cardiac agents, however it cannot be used for cardiac inotropic agents. Long term monitoring of the mentioned cardiac indicators may be more accessible with the use of a wireless and portable PCG system. It may also be beneficial for general users, patients and front line care givers to perform auscultation at home and to continuously monitor sporadic symptoms that may not be detected during periodical medical visits. In other words, patients can collect persistent long term data for the physicians. Furthermore, the convenience of a sensor not tethered to the recording PC allows continuous monitoring the patient in many relevant scenarios, such as treadmill or weight lifting exercises. Therefore, an automated and wireless system to detect and characterize heart sounds is explored in this paper. Variance of PCG quality, whether due to electronic specifications of the sensor, the placement of the stethoscope on the chest and additional noise introduced by the wireless operation are seen as major challenges on the sensor side. On the signal processing side, we would like to show that the advanced PCG algorithms reported in the literature can be implemented on a modest computing platform. The goal of the paper is to report the implementation of a simple wireless PCG sensor designed to operate with a notebook or tablet computer, and the value of signal processing in minimizing the effects of the varying electronic performance, ambient noise and stethoscope’s placement. The group of users targeted by this sensor consists of primary care physicians and care givers. Therefore, key requirements are robustness of the processing algorithms, immunity to the mentioned variances, informative indicators and a rudimentary classification of heart sounds to assist users in choosing the next action.
Our goal is to demonstrate that useful physiological parameters can be derived from heart sounds and presented to care givers for screening purposes.
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Many medical algorithm development works are reported without implementation details. That makes it difficult to estimate the effort requires to transition research knowledge to commercial realization. In this paper, we will make an effort to trace the lineage of the open source codes, describe the modifications in sufficient detail to aid the readers in reproducing results and duplicating the prototype. While the sensor we built is not optimum for mass production, there will be sufficient technical specifications for anyone interested in such an endeavor.
The detection of the heart sounds S1 and S2 is accomplished with a beat finding technique developed for the music industry. The specific beat tracking technique is based on dynamic programming. In the first step of the detection algorithm, audio signal is converted to its onset strength envelope (ose). The ose is calculated as the sum of the difference between the spectra of the current and the previous waveform segments. The ose therefore represents the instantaneous overall change in spectral content (distribution of energy at different frequencies). To calculate the ose, a window of N data points is advanced in equal steps until the window reaches the end of the waveform. The number of data points N in each window corresponds to 1/8 s for the selected audio sampling frequency. The step is only half the size of the window so there is overlap between consecutive windows. The window is analyzed to calculate the spectral content or the energy contained in 20 frequency bins.
A comparison of wired and wireless amplitudes shows that the voltage of the wireless signal is lower but the signal-to-noise ratios (quality) are comparable.
Data collection starts first with strapping the microphone over the heart of the examinee, secondly the examiner putting on the headphones to monitor the recording and to ensure that the signal strength is sufficiently high but not too close to saturation level, and thirdly the examiner commanding the MATLAB program to record heart sounds and display the PCG signal. A frequently used record length of 50 s, recording 55 to 100 heartbeats, is sufficiently long to warrant that the timings of the first and second heart sounds are statistically significant for a relatively constant heart rate or when the subject is at rest.
Sometimes, records of 200 s or longer are collected to study the change of heart rate in the recovery phase after physical exercise. In those cases, the objective is to monitor the gradual decrease of heart rate in the recovery phase. In this proof- of-concept study, the PCG signal was recorded to show that useful physiological indicators can be acquired. The study is not intended to validate the tool’s clinical readiness. With the intended scope, the numbers of subjects (five) and samples
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(26) are deemed sufficient. Since the objective is only to capture the timing of the S1 and S2 sequences and not to diagnose particular aspects of the hemodynamic response, auscultation placement is straightforward and doesn’t require cardiologist’s expertise. For our purpose, placing the stethoscope near the heart’s apex typically results in a strong signal to noise ratio which is the most important factor in capturing the heartbeat sequence timings. The stethoscope microphone is connected to the 3transmitter unit and the receiver is connected to the laptop to record heart sounds. A pair of headphones is also connected to another port in the laptop configured to monitor the audio. Ideally, the microphone only senses the heart sounds of the subject and not ambient noise. Thus, data collection is best in a quiet room, with the subject sitting completely still, and the chest strap adjusted so that the microphone is directly over the heart. However, the processing techniques we use are effective in alleviating the effects of extraneous noises.
When needed, the subject may wear the wireless microphone and jog on a treadmill while data is being collected. The data taker, listening through the headphones, can help with the adjustment of the microphone gain and placement of the sensor over the heart.
In a typical data collections of audio data are collected using the MATLAB audio recorder built-in function, at a rate 32.000 samples per second. The entire record consists of 1.600.000 values. Since the sampling rate is much higher that the highest frequency found in actual heart sounds, signal with frequency higher than 1000 Hz is filtered out. The beat tracking script made available at the LabROSA internet site was designed to extract a single dominant beat, not two beat sequences as in the case of heart sounds. We modified the codes to extract both heart sounds by running the algorithm in two passes. After the first pass, the signal that corresponds to the first detected sequence of heart sounds is removed and the pruned signal is processed again to detect the second sequence, as described in «Segmentation Techniques».
Using the timing relationship between the S1 and S2 sounds, we proceeded to identify S1. The S1 and S2 beats are subsequently paired up and the beat intervals (T11) and the systolic intervals (T12) are calculated. The beats which are not detected because of noise and their potentially unpaired beats are not analyzed. Note that the instantaneous heart rate can be estimated in real time by calculating the inverse of T11. Two additional diagnostic parameters, heart sound temporal width T1 and T2, are calculated directly from the Shannon energy envelope (see). Note that they are not derived from the ose. The heart sound is composed of several fre-
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quencies, all measurable by the PCG and should be included in the see though not all are within the human audio spectrum. The see which is calculated from acoustic energy in all frequencies may be different from the humanly perceived heart sound. We would like to hypothesize that the see is an unbiased representation of the mechanical sound. Therefore, T1 and T2 extracted from the see envelope are representative of the mechanical sound made by the heart. The program displays the four diagnostic parameters and indicates the range of nominal values. The physiological parameters are useful for primary care physicians in screening referable patients and for specialists to infer preliminary diagnosis. It’s conceivable that the primary care physician may select to send forward the information generated by this system.
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Тема 5. Реографический метод
Прочитайте текст, посвященный реографии. Переведите его и ответьте на следующие вопросы.
1.В чем заключается основной принцип работы реографа?
2.Что вы знаете об использовании реографа?
3.В чем преимущества и недостатки его использования?
4.Подумайте, как можно было бы усовершенствовать прибор?
5.Что подразумевается под реографическим методом исследования?
Rheography
Rheography is a method used to study the filling of a part of the body with blood by graphically recording the fluctuations in the resistance of that part of the body. It is used in physiology and medicine.
Rheography is based on the fact that when an alternating current of sonic or ultrasonic frequency (16 – 300 kilohertz) passes through a part of the body, the organic fluids (chiefly blood in the large blood vessels) act as conductors. This makes it possible to determine the condition of the blood circulation in a particular region of the body or in an organ, for example, in an extremity or in the brain, heart, liver, or lungs.
Among all the structures of the body blood has the highest electrical conductivity. This means that during systolic contraction of the heart when the blood flows into nearby bodies electrical conductivity of these parts of the body will be high and the moment of cardiac muscle relaxation (diastole), opposite – low. Based on the testimony rheograph output curve of pulse oscillation, called rheogram.
Rheogram looks sinusoid with a steeper rise characterizing arterial blood flow and smooth descent, which, in turn, is a reflection of venous flow. To thoroughly analyze the state of blood flow during reography necessary to remove a lot of curves. An experienced diagnostician will pay attention to the regularity of the curve and its shape, presence and amount of additional curves in a downward phase. In addition to the external characteristics of the curves, the doctor decides to several mathematical problems: special formulas calculated rheographic index, for which a certain interval, when going beyond which one can judge the presence of pathology, and a few other parameters (amplitude-frequency rate, the rate of venous outflow, pulse wave propagation time).
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Rheography – non-invasive method that is harmless to the body. The skin and tissues are not damaged, as transmitted through them, an electric current is so small magnitude and frequency that is just not able to do any significant damage.
Besides this method has a high sensitivity.
Rheogram analysis and the Stroke Volume
During the isometric phase, the beginning of which coincides with the Q wave of the electrocardiogram, at the time of displacement of the valvular plane of the heart, there occurs a drop in the curve corresponding to sucking in of blood into the heart from the great veins. At the beginning of the ejection period, that is with the opening of the semilunar valves, a steep ascent appears, which breaks off sharply from the rest. The steep ascent corresponds to the rapid filling of the arteries near the heart. In the further course of this phase of systole there occurs a preponderance of outflow of blood into the periphery over the further expulsion of blood from the heart. Accordingly the curve sinks after the first third of the ejection period somewhat more sluggishly. The second heart sound indicates the end of systole. With the valves all closed, the congestion of blood awaiting entry into the ventricles produces rheocardiograpically a new ascent of the curve. The continuing diastolic ascent of the curve falls in the rapid filling phase of the ventricles and is explicable by increasing filling of the venae cave in this period. This phenomenon may be attributed to increased pressure on vein walls as a result of increased circulation rate.
AD5934
The AD5934 output voltage and measurement frequency are fully programmable and the communication is provided by an I2C interface. An application of the AD5934 in biological diagnostics research has been reported by many authors. The AD5934 was used in the blood coagulation detection, biosensor applications, general bioimpedance measurements, and was also used in technical object monitoring.
Designers of impedance meters dedicated for biological objects should not forget about the requirements that have to be met. Besides, a measurement system should offer a wide frequency range, high degree of integration, portability and accuracy. AD5934 absolute corresponds to this condition. The designed, fabricated and tested device enables measurements in the frequency range from 1 Hz to 100 kHz and in the range of impedance from 1 Ω to 10 MΩ.
Application of a method of rheography on a chip of AD5934 is the blood resistance research for detection of a virus. When a known strain of a virus is added
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