The development and continuous improvement of medical device monitoring functions enables remote care providers to provide better diagnostic tools for home patients, emergency room ambulancemen and hospitals in several important areas of human health. Blood pressure monitors such as blood glucose meters and defibrillators require clear analog signals for accurate measurements, otherwise they may be life-threatening. Designing an excellent analog signal path helps designers reduce interference from external noise, extend dynamic range, and enhance accuracy. In addition, in terms of component selection, designers must also choose carefully to meet the performance needs of the final product.
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High performance requirements in small packages
Previously, it was generally believed that medical equipment in hospitals and clinics was more accurate than portable instruments used at home. However, new technology trends are rapidly reversing these points. The new portable medical device users are not only ordinary consumers, but also patients with deep understanding of technology, so the customer's needs are no longer limited to body temperature, ECG and blood pressure measurement. What customers need is a full range of care and measurement functions.
In order to meet the urgent needs of home medical diagnostic instruments, equipment suppliers are relying on advanced inventory management and innovative design to enhance market competitiveness and equip products with more functions to win more users. In the field of developing home medical instruments, one factor is very important, which is the development time required for the product to be put into the market from the initial design. Shortening the time to market can allow manufacturers' products to seize the market. The ability to shorten the development cycle depends on whether the design of the system designer is flexible and cost-effective.
Process technology affects system design
While electrical specifications are a major factor in the designer's choice of components, the process used to fabricate integrated circuits is equally important. For example, a typical blood glucose meter typically requires an op amp with a very low input bias current, and most designers will choose a JFET amplifier. However, they should consider the temperature issue before making a decision.
Because the JFET has a very low initial input bias, it is susceptible to temperature variations, and the input bias is approximately doubled for every 10 °C rise. To calculate the drift of the input offset, use the following equation (Reference 1).
Ib(T)Ib(T0) x 2(T-T0)/10
For example, a JFET input op amp (such as National's LF411) has an input bias current of 50pA at 25 °C, and a better choice is National's LMP7731, a bipolar input operational amplifier. Its input bias current is 1.5nA. From the above equation, we can quickly calculate that the input bias current of the LF411 becomes 3.2nA at 85 °C, which is more than twice that of the LMP7731.
Evaluation system
Speed, noise, and power consumption may be equally important for some designs. A low-noise device consumes more current, while a low-power device provides only limited bandwidth. One way to overcome these problems is to use a counter-compensating amplifier in a suitable application. Compared with the unity gain stability and high speed, the advantage of the counter-compensation amplifier is that it can provide a larger bandwidth without affecting the power consumption, in addition to the lower cost.
The inverse compensation op amp is best suited for use in current-to-voltage conversion (transimpedance) circuits. One of the most common applications in medical devices is the measurement of oxygen in blood cells, called SPO2 or saturated or peripheral oxygen. Figure 1 shows a block diagram of the SPO2 module in which a counter-compensation amplifier (TIA) is used to convert the current from the photodiode into a voltage.
Figure 1 Typical block diagram of the SPO2 module
Shorten design time with shortcuts
The most important parameter of a medical instrument is noise, which can cause serious interference to the circuit itself and nearby devices. Calculating noise is a tedious task, especially if you want to calculate the overall effect of the signal path on the signal-to-noise ratio from the power supply, amplifier, data converter, and external components.
In general, medical instrument circuits tend to operate at lower frequencies, so designers of these systems are generally more concerned with noise in the 0.1 to 10 Hz band, also known as peak-to-peak noise. Unfortunately, some data sheets do not provide values ​​for time domain noise (peak to peak), but only provide a typical graph of voltage or current noise density. In addition to waiting for the circuit supplier to provide measurement data, there is a quick way to help figure out the peak-to-peak noise.
Suppose you intend to use National Semiconductor's LMP7731 to estimate the peak-to-peak (0.1 to 10 Hz) noise. First, select a point in the frequency range within the specified frequency band, for example, 1 Hz. Is 5.1nV/√Hz (Figure 2), then use the following equation to calculate the root mean square (RMS) of the noise:
Equation 1: enrms="enf"√ln(10/0.1), where enf is noise at 1Hz
Figure 2 LMP7731 input voltage noise and frequency relationship frequency, voltage noise
From the above equation, the total root mean square noise of 10.9nV can be obtained. To calculate the peak-to-peak noise, simply multiply this mean square value by 6.6, and you can get 72.2nV. The result of this estimate is quite good, and it is very close to the 78nV specification listed in the datasheet.
If the voltage noise density map in the datasheet does not represent the noise value at 1 Hz, then you can use the following simple equation (Expression 2) to estimate the value at a certain frequency.
Equation 2: en=enb*√(fce/f)
Where enb is broadband noise (usually the value at 1 kHz), and fce is the 1/f inflection point, as f is the frequency of interest, in our case 1 Hz.
As an example, National Semiconductor's LMV851 has a broadband noise of 10nV/√Hz at 10kHz. In order to calculate the root mean square noise, first determine the value of the 1/f inflection point (fce) from the graph. Use the voltage noise density map in the datasheet so that fce is found to be approximately equal to 300 Hz. Then, using the above formula, we can calculate en=10*√(300/1)=173nV√Hz, and this is the voltage noise at 1Hz. Finally, we substitute this value into Equation 1 and multiply the result by 6.6. , you can get the peak-to-peak noise of 2.4μV.
Another thing to consider is current noise. In general, if the impedance of the power supply is not very large (>100kΩ), you can still get a very close estimate without considering the current noise, just like the example above. However, if the impedance of the power supply is large, the same technique must be used to estimate the current noise and add the voltage and current noise as root mean square values.
Speed ​​decision
Just as the noise of an op amp is extremely important to the resolution of an ADC , bandwidth is equally important to maintain system accuracy. In order to limit the error to 1/2 least significant bit (LSB), a quick check is needed to determine if the bandwidth of the amplifier is sufficient. In addition to using complex and ubiquitous guidance, you can use the resolution of the analog/digital converter to quickly calculate the results. The method is to use 1/2 (N/2) and multiply the result by the amplifier frequency (see 2).
With the above shortcut and a 14-bit ADC, this example yields feff = 0.007813*f-3dB. For the op amp (LMP7711) with a configurable gain of 10 in Figure 3, the frequency at -3dB is 1.7MHz. Thus, the maximum bandwidth (at 1/2 LSB error) is equal to 0.007813*1.7E6=13.3kHz.
Figure 3 Block diagram of the portable electrocardiograph
Monitor device and communication device
Most newer medical diagnostic instruments have wireless communication capabilities. Modern electrocardiographs (EKG or ECG) can transmit patient data to a doctor's office or hospital within minutes via a personal electronic PDA or other computer peripheral. Aside from the benefits of wireless data transmission, such devices can cause serious interference with medical devices, causing errors in their readings.
In order to avoid this interference, a filter must be used. However, adding a filter not only increases the size of the device, but also increases the cost of the design. A more cost-effective and quick way to use components (including filters) that can suppress radio frequency ( RF ) noise.
Conclusion
The trend in today's medical device field is to provide consumers with higher value products, that is, home care instruments that are inexpensive and provide rapid diagnostic results. As technology continues to advance, more medical devices will be used to instantly transfer data from the patient's home to the doctor's office. In addition, as users demand more features, the accuracy requirements for portable medical devices will be further enhanced to achieve more accurate diagnostics, all of which will rely on designers' constant innovation, long-term development, and comprehensive solutions. committed to.
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