The content listed below is grouped together based on sensor product lines to make it easier for you to find what you are looking for. Interested in the biometric sensor, or looking for a software example, then head down to the right section and see what KBAs or other relevant content has been created under those topics.
Each category has an associated index number and each individual KBA has its own index number within the category. The KBA's are prefixed with KBA_SENS_AABB where AA is the category index and BB is the KBA index within that category. The category index numbers are as follows:
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Note: Most of the biometric sensors' collaterals are only available NDA. Please contact the team through the technical support system for more information.
There is a perceived need to measure the UV-INDEX exposure to people in a manner analogous to the dosimeter worn by X-Ray technicians, but two basic problems interfere: The formal UV-Index measurement definition is not an “exposure” measurement and UV radiation is easily blocked from the dosimeter.
The formal UV-Index specification created by the UN's World Health Organization and World Meteorological Organization in 1994 provides a measurement of the UV hazard to skin in a geographical site. It evaluates the hazard to a person wondering around in this site with no attention to what task the person is doing. e.g.: walking, lying, swimming. It also designed to measure the hazard in a fixed manner, requiring a cosine response with respect to the vertical.
This UV index definition was not intended to be implemented by a wearable or any device not aimed vertically, and one can’t claim that such devices are measuring UV index unless at the very least it is aimed at zenith when it makes the measurement and has an unobstructed view of the sky.
What can be salvaged from the UV-Index definition and used by a “UV Dosimeters”, is the shape and sensitivity of the erythema curve. A UV-Index measuring device. such as the Si1133, can be worn on the wrist and be changing directions constantly, always accumulating exposure readings. The wearable’s MCU can be programmed to use a suitable integration algorithm to give UVIH (UV-Index Hours) readings which are weighted so that despite the location of the sensor (the wrist), a user in a UV-Index environment of 5 for one hour would get a reading of aproximately 5 UVIH.
There are some obvious statistical difficulties to overcome with this concept, but they are not insurmountable.
One problem with this approach in that there are many cases where most of the time the sensor is aimed in a constant direction. The wearer could be walking down a beach with the sun at 45 degrees and the device aimed away from the sun almost the entire time. This is overcome by putting a sensor on both the wearable face and the opposing band allowing normal hand movements to briefly expose the sensor. The sensor in this case would operate in a peak detection mode over short intervals of about a minute.
The Si72xx-WD-Kit includes demonstrations for wheel position sensing, wheel rotation counting, and display of the magnetic field data from sensors and small postage stamp sized evaluation boards. This demonstration uses the MCU and display from a pre-programmed EFM32 Happy Gecko STK. The source code for the demo is included with Simplicity Studio which can be downloaded from https://www.silabs.com/products/development-tools/software/simplicity-studio
The Si1133 and Si115x Sensor parts share a common die layout with the same photodiode array. The article points out where the various photodiodes and photodiode combinations are located and selected. This die is centered in the 2x2 mm clear QFN package that the parts come in. If the module is used the visible and IR photodiode array is centered in beneath the module circular opening.
Figure 1 Photo Diode Locations on the die
The figure below shows that at each level there are 12 individual squares that are connected as one named photodiode for each two squares. The colors shown here are strictly for illustration purposes. They do not imply a filter or sensitivity. The photodiodes are named the same way except with a b suffix on the bottom. Thus, at the top there are: D1a pair, D3a pair … D6a pair while at the bottom there are D1b pair, D3b pair … D6b pair.
The black corner photodiodes are covered in metal and do not measure light. They are used to automatically compensate for photodiode current leakage.
Figure 2 Light Travel in the Stacked Photodiodes
The following #define table shows all the photodiode selections available. The figures below illustrate some examples with different groups of PDs selected.
#define ADCCONFIG_ADC_MUX_D1a_D4a_minus_DARK 0x0D // (D1a+D4a) - (D5a+D6a)
#define ADCCONFIG_ADC_MUX_D1a_minus_DARK 0x0B // (D1a - D5a)
#define ADCCONFIG_ADC_MUX_L_IR 0x02 // (D1b + D2b + D3b + D4b) - 2*(D5b + D6b)
#define ADCCONFIG_ADC_MUX_M_IR 0x01 // (D1b + D2b) - (D5b + D6b)
#define ADCCONFIG_ADC_MUX_S_IR 0x00 // D1b(w) - D5
#define ADCCONFIG_ADC_MUX_UV_SHALLOW_minus_DARK 0x18 // UV shallow - UV shallow-dark
Table 1 Si1133/53 photodiode selections: ADCMUX[4:0] field of ADCCONFIGx register
Figure 3 The RED area shown in this figure is the one active with the ADC mux field set to 0x00
Figure 4 The RED area shown in this figure is the one active with the ADC mux field set to 0x02
Figure 5 The RED area shown in this figure is the one active with the ADC mux field set to 0x01
Photodiodes used in the Si1133/4x/5x sensors are arranged in a 3D stack, one set shallow and one set deep. The figure below shows that at each of the two levels level there are 12 individual squares that are connected as one named photodiode for each two squares. The colors shown here are strictly for illustration purposes. They do not imply a filter or sensitivity. The photodiodes are named the same way except with a “b” suffix on the bottom instead of “a”. Thus, at the top there are: D1a pair, D3a pair … D6a pair while at the bottom there are D1b pair, D3b pair … D6b pair.
The black corner photodiodes are covered in metal and do not measure light. They are used to compensate for photodiode current leakage.
Figure 1 Light Travel in the Stacked Photodiodes
As a result of this arrangement, the spectral response of the shallow and deep photodiodes is different. The shallow photodiodes are about 4X less sensitive in the green but about 20 times less sensitive in the IR which is can be an advantage in some applications (e.g. Ambient light sensing or ALS that suffer from IR interference.
The resultant response curves for both shallow and deep photodiodes are shown in the figure above. The deep one is much more sensitive with a peak at about 800 nm while the shallow one is less sensitive with a peak in the blue.
The advantage of the less sensitive one is the relative response of IR region where it suppresses relative IR response by a large factor this can be seen in the figure below that show that comparing 550 nm (green) response to the 900 nm IR response the shallow PDs suppress 900 nm IR by a factor of 7.5 while the deep PDs accentuate the 900 nm IR by a factor of 2.
The shallow PD is more effective for visible light sensing (ALS) since IR response is a major problem. Th reduced overall sensitivity is usually acceptable especially with si1133/5x parts since they have good dark current compensation and can reach ~0.01 lux with the deep PD and ~0.1 lux with the shallow PDs. Note that the older Si114x part does not have the dark current compensation and is limited to higher light levels.
What’s the major difference between Si114x and Si115x proximity sensor? As an existing Si114x customer, is there any guidance to migrate to Si115x?
Both Si114x and Si115x optical sensors can be used to measure proximity and ambient light. However, Si114x has dedicated PS and ALS tasks while Si115x provides 6 configurable channels with the flexibility of setting multiple PS or ALS measurements in any order as users would like to.
In general, Si115x has a few improvements over Si114x.
On the other hand, Si114x has one feature that’s missing on Si115x: interrupt when a set number of consecutive samples exceeding the threshold. On Si115x, if the host configures the sensor to interrupt on a certain threshold, the sensor will generate the interrupt as soon as 1 sample exceeds that threshold.
Although the basic principle of operation is the same for Si114x and Si115x, the host interface, including the I2C registers and parameter registers, are quite different. Existing customers moving from Si114x to Si115x will have to re-write the host software. We’d always recommend customers to check out the example project we have on Si115x/33 OPT EXP board first. The demo provides the driver code as well as initialization example code for Si115x. Using that as a starting point and then follow the register table definition in the datasheet, customers should be able to do the migration without much difficulty. If customers run into issues or have questions porting the code, they’re welcome to create technical support tickets in our system.
System Integration Considerations for Optical Heart Rate Sensing Designs
Designing and implementing an optical heart rate monitoring (HRM) system, also known as photoplethysmography (PPG), is a complex, multidisciplinary project. Design factors include human ergonomics, signal processing and filtering, optical and mechanical design, low-noise signal receiving circuits and low-noise current pulse creation.
Wearable manufacturers are increasingly adding HRM capabilities to their health and fitness products. Integration is helping to drive down the cost of sensors used in HRM applications. Many HRM sensors now combine discrete components such as analog front ends (AFE), photodetectors and light-emitting diodes (LEDs) into highly integrated modules. These modules enable a simpler implementation that reduces the cost and complexity of adding HRM to wearable products.
Wearable form factors are steadily changing too. While chest straps have effectively served the health and fitness market for years, HRM is now migrating to wrist-based wearables. Advances in optical sensing technology and high-performance, low-power processors have enabled the wrist-based form factor to be viable for many designs. HRM algorithms also have reached a level of sophistication to be acceptable in wrist form factors. Other new wearable sensing form factors and locations are emerging, such as headbands, sport and fitness clothing, and earbuds. However, the majority of wearable biometric sensing will be done on the wrist.
No two HRM applications are alike. System developers must consider many design tradeoffs: end-user comfort, sensing accuracy, system cost, power consumption, sunlight rejection, how to deal with many skin types, motion rejection, development time and physical size. All of these design considerations impact system integration choices, whether to use highly integrated module-based solutions or architectures incorporating more discrete components.
Figure 1 shows the fundamentals of measuring heart rate signals, which depend on the heart rate pressure wave being optically extracted from tissue. Figure 1 shows the travel path of the light entering the skin. The expansion and contraction of the capillaries, caused by the heart rate pressure wave, modulates the light signal injected into the tissue by the green LEDs. The received signal is greatly attenuated by the travel through the skin and is picked up by a photodiode and sent to the electronic subsystem for processing. The amplitude modulation due to the pulse is detected (filtering out motion noise), analyzed and displayed.
Figure 1. Principles of operation for optical heart rate monitoring.
A fundamental approach to HRM system design uses a custom-programmed, off-the-shelf microcontroller (MCU) that controls the pulsing of external LED drivers and simultaneously reads the current output of a discrete photodiode. Note that the current output of the photodiode must be converted to voltage to drive most analog-to-digital (A/D) blocks. The Figure 2 schematic shows the outline of such a system. Note that the I-to-V converter creates a voltage equal to VREF at 0 photodiode current, and the voltage decreases with increasing current.
The current pulses generally used in heart rate systems are between 2 mA and 300 mA depending on the color of the subject’s skin and the intensity of sunlight with which the desired signal needs to compete. The infrared (IR) radiation in sunlight passes through skin tissue with little attenuation, unlike the desired green LED light, and can swamp the desired signal unless the green light is very strong or unless an expensive IR blocking filter is added. Generally speaking, the intensity of the green LED light where it enters the skin is between 0.1x and 3x the intensity of sunlight. Due to heavy attenuation by the tissue, the signal that arrives at the photodiode is quite weak and generates just enough current to allow for a reasonable signal-to-noise ratio (SNR) (70 to 100 dB) due to shot noise even in the presence of perfect, noise-free op amps and A/D converters. The shot noise is due to the finite number of electrons received for every reading that occurs at 25 Hz. The photodiode sizes used in the design are between 0.1 mm2 and 7 mm2. However, above 1 mm there are diminishing returns due to the effect of sunlight.
Figure 2. The basic electronics required to capture optical heart rate.
The difficult and costly function blocks to implement in an optical heart rate system design, as shown in Figure 2, are the fast, high-current V-to-I converters that drive the LED, a current to voltage converter for the photodiode and a reliable algorithm in the MCU that sequences the pulses under host control. A low-noise (75 - 100 dB SNR) 300 mA LED driver that can be set to very low currents down to 2 mA while still creating very narrow light pulses down to 10 µs is an expensive block to achieve with discrete op amps.
The narrow pulses of light down to 10 µs shown in Figure 2 allow the system to tolerate motion and sunlight. Typically two fast light measurements are made for each 25 Hz sample. One measurement is taken with the LEDs turned off and one with the LEDs turned on. The calculated difference removes the effect of ambient light and gives the desired raw optical signal measurement that is, most importantly, insensitive to flickering background light.
The short duration of the optical pulses both allows and requires a relatively strong light pulse. It is essential to stay brighter than the sunlight signal, which may be present and not allow the PPG signal carrier to be dwarfed by the sunlight signal. If the sunlight signal is larger than the PPG carrier, then although it may be removed by subtraction, the signal can be so large that external modulation such as swinging an arm in and out of shadow can create difficult-to-remove artifacts. As a result, systems that use low-current LED drivers and large photodiodes to compensate suffer severely from motion artifacts in bright light situations
Much of the desired HRM sensing functionality is available pre-designed and integrated into a single device. Packing most of this functionality into one piece of silicon results in a relatively small 3 mm x 3 mm package that can even integrate the photodiode (PD) itself.
Figure 3 shows an example of a schematic with an Si118x optical sensor from Silicon Labs. This HRM design is relatively easy to implement. The engineer just needs to focus on the optical portion of the design, which includes optical blocking between the parts on the board and coupling the system to the skin.
Figure 3. An integrated heart rate sensor requiring only external LEDs.
While the approach shown in Figure 3 results in a high-performance HRM solution, it is not as small or power efficient as some designers would like. To achieve an even smaller solution, the LED die and the control silicon must be integrated into a single package that incorporates all essential functions including the optical blocking and the lenses that improve the LED output. Figure 4 illustrates this more integrated approach, based on a Silicon Labs Si117x optical sensor.
No external LEDs are required for this HRM design. The LEDs and photodiode are all internal to the module, which can be installed right below the optical ports at the back of a wearable product such as a smartwatch. This advantageous approach enables a shorter distance between the LEDs and the photodiode than is possible with a discrete design. The reduced distance allows operation at extremely low power due to lower optical losses traversing the skin.
Integrating the LEDs also addresses the issue of light leakage between the LEDs and the photodiode. As a result, the designer does not have to add optical blocking to the printed circuit board (PCB). The alternative to this approach is to handle the blocking with plastic or foam inserts and special copper layers on the PCB.
Figure 4. A highly integrated HRM sensor module incorporating all essential components.
There is one more part of an HRM design that the developer does not necessarily need to create: the HRM algorithm. This software block residing on the host processor is quite complex due to the signal corruption that occurs during exercise and motion in general. End-user motion often creates its own signal that spoofs the actual heart rate signal and is sometimes falsely recognized as the heart rate beat.
If a wearable developer or manufacturer does not have the resources to develop the algorithm, third-party vendors provide this software on a licensed basis. Silicon Labs also offers a heart rate algorithm for its Si117x/8x optical sensors that can be compiled to run on most host processors.
It is up to the designer to decide how much integration is right for the HRM application. The developer can simplify the design process and speed time to market by opting for a highly integrated module-based approach using a licensed algorithm. Developers with in-depth optical sensing expertise, time and resources may opt to use separate components (sensors, photodiodes, lenses, etc.) and do their own system integration, and even create their own HRM algorithm. Ultimately, when it comes to HRM system design, the developer has a choice of doing it all or purchasing it all.
Si1153 RevB parts (Si1153-AB00-GM, Si1153-AB09-GM, Si1153-AB9X-GM) are launched in September 2018.
Comparing to Si1153 RevA parts, the major change is in interrupt modes. Si1153 RevA parts only support interrupt on every sample and whenever the sample is larger than a set threshold, while Si1153 RevB parts support multiple interrupt modes listed below. The host can configure ADCPOSTx registers to set different interrupt modes.
Mode 1: Interrupt on every sample.
Mode 2. Interrupt whenever the sample is larger/smaller than a set threshold.
Mode 3. Interrupt whenever the sample enters/exits the set threshold window.
Si1153 RevB is pin compatible with Rev A and fully backwards compatible in terms of software programming. Existing customers can easily switch to RevB parts without any changes. New customers can make use of the new interrupt mode in certain applications to reduce power consumption.
The Si1133/5x Optical Sensor EXP board now has an example project running on EFM32PG12 MCU to demonstrate our latest Si1153 for proximity/ambient light sensing and Si1133 for UV sensing. The example project will require an EFM32™ Pearl Gecko PG12 Starter Kit(SLSTK3402A) to plug in the Si1133/5x Optical Sensor EXP board through the 20pin expansion header.
The source code of the example project is provided in the attachment.
We also have a nice video describing all the features included in the demo. Please make sure to check it out before getting started.
This is a list of links to for some of the most common questions regarding the use of humidity sensors.