Designing Superior Signal Paths for Portable Medical Devices

The challenge facing companies developing medical diagnostic equipment is to provide consumers with high-quality and affordable products. In terms of reducing medical costs and improving patient care services, it is most important to reduce the size of these medical devices and improve their accuracy. As the problem of aging population becomes more serious, the above needs are even more urgent. According to the InMedica report of IMS Research Company, the total sales of consumer medical devices are expected to exceed US$5 billion by 2011.

With the development and continuous improvement of the monitoring functions of medical devices, remote care providers can provide better diagnostic tools for home patients, emergency room paramedics and even hospitals in several important areas of human health. Monitoring instruments such as blood pressure meters, blood glucose meters, and defibrillators require clear analog signals for accurate measurements, otherwise they may be life-threatening. Designing excellent analog signal paths can help designers reduce interference from external noise, expand dynamic range and enhance accuracy. In addition, when it comes to component selection, designers must also carefully choose to meet the performance requirements of the final product.

High performance requirements in a small package

Previously, people generally believed that medical equipment in hospitals and clinics was more accurate than portable instruments used at home. However, new technological trends are rapidly changing this view. New portable medical devices are used not only by ordinary consumers but also by patients with deep technological savvy, so customers' needs are no longer limited to taking body temperature, doing electrocardiograms and measuring blood pressure. Customers need a full range of care and measurement functions.

In order to meet the urgent demand for 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 attract more users. In the field of developing home medical instruments, one factor is very important, which is the development time required from the initial design to the actual launch of the product. Shortening the time to market allows manufacturers' products to seize the market. Whether the development cycle can be shortened depends on whether the system designer's design is flexible enough and cost-effective.

Process technology affects system design

Although electrical specifications are the primary factor in designers' component selection, the process used to manufacture the integrated circuit is equally important. For example, a typical blood glucose meter usually requires an operational amplifier with very low input bias current, and most designers will choose a JFET amplifier. However, they should consider the issue of temperature before making a decision.

Since the JFET has a very low initial input bias, it is very susceptible to temperature changes, with the input bias approximately doubling for every 10°C rise. To calculate the input bias drift, use the following formula (reference 1).

Ib(T)Ib(T0) x 2(T-T0)/10

For example, a JFET input op amp (such as National Semiconductor's LF411) has an input bias current of 50pA at 25°C, while a better choice is National Semiconductor's LMP7731, a bipolar input op amp with an input bias current of 1.5nA. Using the above formula, we can quickly calculate that at 85°C, the LF411's input bias current becomes 3.2nA, more than twice that of the LMP7731.

Evaluation System Trade-offs

Speed, noise, and power consumption may be equally important for some designs. A low-noise device consumes more current, while a low-power device can only provide limited bandwidth. One way to overcome these problems is to use an anti-compensated amplifier in the appropriate application. In addition to the lower cost, the advantage of the anti-compensated amplifier is that it can provide a larger bandwidth without affecting power consumption.

The anti-compensated operational amplifier is best used in current-to-voltage conversion (transimpedance) circuits. In medical instrumentation, one of the most common applications is to measure the oxygen content in blood cells, called SPO2 or saturated or peripheral oxygen. Figure 1 shows the block diagram of the SPO2 module, where the anti-compensated amplifier (TIA) is used to convert the current from the photodiode into a voltage.

Figure 1 Typical block diagram of SPO2 module

Reduce design time using shortcuts

The most important parameter for medical instruments is noise, which can cause serious interference to the circuit itself and nearby equipment. Calculating noise is a tedious task, especially when you want to calculate the overall impact of the signal path on the signal-to-noise ratio, from power supplies, amplifiers, data converters to external components.

Generally speaking, medical instrument circuits tend to operate at lower frequencies, so designers of these systems are usually more concerned with noise within the 0.1 to 10 Hz frequency band, also known as peak-to-peak noise. Unfortunately, some data sheets do not provide time domain noise (peak-to-peak) values, but only provide typical graphs 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 deduce the peak-to-peak noise amount.

Suppose you want to use National Semiconductor's LMP7731 to estimate the amount of peak-to-peak (0.1 to 10 Hz) voltage noise. First, select a point in the frequency range within the specified frequency band, such as 1 Hz. The value when comparing the curves is 5.1 nV/√Hz (Figure 2). Then use the following formula to calculate the root mean square (RMS) value of the noise:

Formula 1: enrms="enf"√ln(10/0.1), where enf is the noise at 1Hz

Figure 2 Relationship between input voltage noise and frequency of LMP7731 Frequency, voltage noise

The above formula gives a total RMS noise of 10.9nV. To calculate the peak-to-peak noise, simply multiply this RMS value by 6.6, which gives 72.2nV. This is a pretty good estimate and is very close to the 78nV specification listed in the datasheet.

If the voltage noise density graph in the data sheet does not show the noise value at 1 Hz, you can use the following simple equation (Equation 2) to estimate the value at a certain frequency.

Formula 2: en = enb * √ (fce / f)

where enb is the broadband noise (usually a value at 1kHz), and fce is the 1/f corner point, and f is the frequency of interest, in our case 1Hz.

For example, the broadband noise of the National Semiconductor LMV851 at 10kHz is 10nV/√Hz. To calculate the RMS noise, first determine the value of the 1/f corner point (fce) from the graph. Using the voltage noise density plot in the datasheet, this will show that fce is approximately 300Hz. Then, using the above equation, we can calculate en=10*√(300/1)=173nV√Hz, which is the voltage noise at 1Hz. Finally, substituting this value into equation 1 and multiplying the result by 6.6, we can get a peak-to-peak noise of 2.4μV.

Another thing to consider is current noise. Generally speaking, if the impedance of the source is not very large (>100kΩ), you can ignore the current noise and still get a very close estimate, as in the example above. However, if the impedance of the source is very large, you must use the same technique to estimate the current noise and add the voltage and current noise in the form of root mean square values.

Determine the speed requirement

Just as the noise of the op amp is critical to the resolution of the ADC, bandwidth is equally important to maintaining the accuracy of the system. To limit the error to 1/2 least significant bit (LSB), a quick check is needed to determine whether the amplifier bandwidth is sufficient. In addition to using complex and general instructions, you can also use the resolution of the analog/digital converter to quickly calculate the result. The method is to use 1/2 (N/2) and multiply the result by the amplifier frequency at -3dB (Reference 2).

Using the shortcut above and a 14-bit ADC, this example yields feff = 0.007813*f-3dB. For the op amp in Figure 3 with a configurable gain of 10 (LMP7711), 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 a portable electrocardiograph

Monitoring devices and communication devices

Most newer medical diagnostic equipment has wireless communication capabilities. Modern electrocardiographs (EKG or ECG) can transmit patient data to a doctor's office or hospital within minutes via a personal digital assistant (PDA) or other computer peripheral device. Despite the benefits of wireless data transmission, such equipment may cause serious interference to medical devices, causing them to erroneously read.

In order to avoid this interference, filters must be used. However, adding filters will not only increase the size of the equipment, but also increase the cost of the design. A more cost-effective and quicker method is to use components (including filters) that can suppress radio frequency (RF) noise.

Conclusion

The current trend in the field of medical equipment is to provide consumers with higher value products, that is, home care instruments that are inexpensive and can quickly provide diagnostic results. As technology continues to advance, more medical devices will transmit data instantly from the patient's home to the doctor's office via a computer. In addition, as users demand more functions, the accuracy requirements for portable medical devices will be further improved to achieve more accurate diagnosis, all of which will rely on designers' continuous innovation, long-term development and commitment to comprehensive solutions.