Sensors: A Key Ingredient in the Wearable Designs Recipe

Sensors are the secret sauce, the virtual unsung heroes of wearable designs. They are small, cheap, smart, highly accurate and, although they require very little power, amazingly powerful themselves. The recent popularity of wearable technology can be traced, at least in part, to the fact that the sensors used in wearables have plummeted in price—in some cases down to just a few dollars. Another sensor-related enabler is the impact of mobile phones on development of remote monitoring systems. Smart phones easily beat out traditional data loggers as they provide a ready-to-use platform and a means to transmit data remotely.

Now add to the recipe System-on-Chip (SoC) solutions: developments in microelectronics enabled researchers to create miniature circuits that combine sensing, front-end amplification, MCU functions, and RF transmission. Particularly important are advances in MEMS technology-based inertial sensors used in motor activity and other health monitoring systems. Finally, toss in sensor fusion—the combining of sensory data from disparate sources such that the resulting information is better than would be possible when these sources were used individually—and with all of these factors taken together it should not be a surprise that wearables have arrived.

Wearable apps

Wearable sensor-based systems today consist of three elements:

• Sensing and data collection hardware
• Communication hardware and software
• Data analysis techniques

Sensors have made their way onboard garments and can be seen “accessorizing” body parts such as ears, necks, wrists, and more. Examples of where they are used include:

• Ambient sensors monitor activity patterns, sleep quality, and bathroom elimination, providing alerts to caregivers when anomalies occur.
• Ear-worn, flexible, low-power heart-rate monitors can be unobtrusive. To date, however, remaining challenges include motion-artifact reduction to improve reliability.
• Biochemical sensors monitor chemical compounds in the atmosphere. They also can monitor people working in hazardous environments.
• Wearable sensor-based firefighter garments integrate CO sensors and also measure movement, external and body temperature, position, blood oxygen saturation, heart rate, and respiration rate.
• E-textile-based systems embedded into garments collect electrocardiographic and electromyography data by weaving electrodes into the fabric to ascertain movement-sensing changes in resistance.
• Activity monitors measure activity levels with an accelerometer or GPS or both. Common examples include Fitbit wristbands and trackers; when a step is taken, for instance, vibration is sensed and data is sent to a phone or computer. Other wearable devices can track sleep quality or monitor for falls.
• Wearables are being developed that cross the boundary from consumer electronics to regulated medical devices. Diagnostic devices measure temperature, heart rate, ECG, blood oxygen level, and heart-rate anomalies. Blood pressure from pulse-wave-transit time—how fast sound passes through the blood—can also be measured.
• Lab-on-a-chip system testing and diagnosis is fast, cheap, and easily accessible and is rapidly gaining market traction.
• The combination of wearable and ambient sensors is becoming more prevalent so that wearable sensors are augmented by information gathered using ambient sensors.

Notable parts

There are many sensors that lend themselves to use in wearables. Let’s now look at some notable examples.

The MPU-9150 by InvenSense is an integrated 9-axis MotionTracking device that combines a 3-axis MEMS gyroscope, a 3-axis MEMS accelerometer, a 3-axis MEMS magnetometer, and a Digital Motion Processor (DMP) hardware-accelerator engine. The supplier’s MotionFit SDK (Figure 1) is designed around the MPU-9150 and enables rapid commercialization of wearable sensor solutions for fitness, health, and sports applications. It delivers a sensor platform capable of tracking 10 degrees-of-freedom by combining the MPU-9150 with a Bosch pressure sensor based on piezo-resistive technology, a microcontroller, and a Bluetooth radio module. The sensors are interfaced via I²C serial digital interface to a Texas Instruments MSP430 MCU. A Bluetooth radio module that enables wireless connectivity is interfaced through the UART to the MCU. There is a serial flash that interfaces to the MCU using the SPI interface. Also included is a 110 mAh rechargeable battery and charger circuitry that can provide up to 4 hours of wireless streaming. A micro-USB connector provides a wired interface to the SDK, which is well suited for embedded applications, such as activity detection for fitness and sports performance, and medical applications such as rehab and outpatient monitoring.


Figure 1: The InvenSense MotionFit SDK stack is designed to enable rapid commercialization of wearable sensor solutions for fitness, health, and sports applications.

The MPU-9150’s 9-axis MotionFusion feature package combines acceleration and rotational motion plus heading information into a single data stream and has a small footprint. For precision tracking of both fast and slow motions, the part features a user-programmable gyroscope full-scale range of ±250, ±500, ±1000, and ±2000 °/sec (dps), a user-programmable accelerometer full-scale range of ±2 g, ±4 g, ±8 g, and ±16 g, and a magnetometer full-scale range of ±1200 μT.

The solution is a multi-chip module (MCM) consisting of two dies integrated into a single LGA package. One houses the 3-axis gyroscope and the 3-axis accelerometer. The other die houses a 3-axis magnetometer from Asahi Kasei Microdevices. An evaluation kit (designated MPU-9150EVB, Figure 2) is available to help engineers jump-start projects.


Figure 2: The MPU-9150 Evaluation Board by InvenSense.

Also worth considering for wearables application is the InvenSense MPU-6500 (Figure 3) 6-axis Motion Tracking device, which combines a 3-axis gyroscope, 3-axis accelerometer, and a Digital Motion Processor (DMP) into a small 3 mm x 3 mm x 0.9 mm package. It features a 4096-byte FIFO that lowers traffic and reduces power consumption, allowing the system processor to burst read sensor data and then go into a low-power mode.

The MPU-6500 directly accepts input from external I²C devices. MPU 6500, with its 6-axis integration, on-chip DMP, and run-time calibration firmware, not only enables manufacturers to eliminate costly and complex selection, qualification, and system level integration of discrete devices, it guarantees optimal motion performance for consumers. It interfaces with multiple non-inertial digital sensors, such as pressure sensors, on its auxiliary I²C port.


Figure 3: Block diagram of the InvenSense MPU-6500.

Factory-calibrated initial sensitivity of both sensors reduces production-line calibration requirements. Other features include on-chip 16-bit ADCs, programmable digital filters, a precision clock with 1% drift from -40°C to 85°C, an embedded temperature sensor, and programmable interrupts. The device also features I²C and SPI serial interfaces, a V_DD operating range of 1.71 V to 3.6 V, and a separate digital IO supply, V_DDIO from 1.71 V to 3.6 V. For applications requiring faster communications, the sensor and interrupt registers may be read using SPI at 20 MHz.

InvenSense has driven the package size down with CMOS-MEMS fabrication to a 24-pin QFN, making the MPU-6500 ideal for wearable sensors for health, fitness, and sports.

While conventional UV sensors combine UV-sensitive photodiodes with an external microcontroller, ADC and signal-processing firmware the Si1132-A10-GMR sensor from Silicon Labs (Figure 4) integrates all of these elements plus a digital I²C control interface in a small 2 mm x 2 mm clear QFN package. This low-power sensor enables long battery life with standby less than 500 nA and an average power of as little as 1.2 µA with once-per-second real-time UV Index measurements. The Silicon Labs UV Index and ambient-light sensor enables fitness wrist/arm bands, smart watches, and smartphones to measure UV sun exposure. Consumers can benefit by receiving a warning when their current UV exposure is unhealthy or to determine their cumulative UV exposure during exercise. This measurement is critical for people with an elevated risk of sunburn or anyone who is concerned about their sun exposure.


Figure 4: Block diagram of the Si1132-A10-GMR UV and ambient light sensor from Silicon Labs.

The wearable future

Wearables are potentially a huge market. As the technology improves, there will be greater interconnection of the physical sensors and more use of sensor fusion. Another driver will be increased use of the IEEE 802.15.4a standard based on Ultra-wide-band (UWB) impulse radio, creating a myriad of opportunities for even more low-power, low-cost, and high-data-rate sensor network wearable applications.

For more information on the parts discussed in this article, use the links provided to access product information pages on the DigiKey website.