The basics of designing wearable electronics with microcontrollers

Vairamuthu Ramasamy, Chethan Gowda, and Sivaguru Noopuran, Cypress Semiconductor

June 17, 2014

Vairamuthu Ramasamy, Chethan Gowda, and Sivaguru Noopuran, Cypress SemiconductorJune 17, 2014

‘Wearable’ devices are miniature electronic devices worn on the body, often integrated with or designed to replace existing accessories such as a watch. This market segment is booming, enabled by Internet of Things technology. Thus the need for smaller, more intuitive devices is rapidly increasing. Some of the current trends are smart watches, smart glasses, and sports and fitness activity trackers. In addition to the consumer market, the medical industry is creating a demand for devices that monitor physical conditions and functions.

The most important electronic component in wearable devices is the microcontroller. As these MCUs need to be small and at the same time perform more functions, integration becomes another important factor. In this article, we look at

  • The different requirements for a wearable electronic system
  • How the market can be segmented based on these requirements
  • Different components in a typical wearable device
  • How MCUs can address these requirements

Requirements of wearable devices
Aesthetics: The wearable device needs to be stylish and blend with existing fashion accessories such as ornaments, watches, and glasses. Aesthetics are so important that top semiconductor companies such as Intel are partnering with the fashion industry to make these devices fashionable.

Capacitive touch sensing is a key technology that helps to improve the aesthetics. Capacitive UI need to work on a variety of form factors including curved surfaces, be tolerant of liquids, and be able to sense under thick overlays. Cypress’ CapSense and TrueTouch technologies make such requirements realizable.

Size: As we saw earlier, these devices must be small so that they can easily fit on to a wearable. Nevertheless, at the same time they must integrate more features in the same space. Technologies such as System-on-Chip (SoC) and chip scale packages (CSP) help to shrink the size. For example, Cypress offers PSoC (Programmable System-on-Chip) devices in multiple packaging options including WLCSP.

Water tolerance: Wearable devices are going to be everywhere the human body can go. Therefore it is important to design these devices to be tolerant of the environmental conditions such as water droplets, moisture, and sweat.

Power consumption: Since wearable devices are battery powered, reducing the power consumption of these devices poses unique challenges. Wearable devices, unlike other mobile devices, are required to be always on and always connected because most of these are monitoring devices. For example, a smart watch needs to always show the time and be connected to a mobile phone through a wireless link such as Bluetooth in order to receive alerts; a pedometer is required to continuously count the steps and report it to a mobile phone app; and similarly a heart rate monitor needs to be always monitoring and reporting. Yet battery capacity is inherently limited due to the requirement to reduce the overall size

Therefore these devices need to operate at ultra-low power to conserve the battery life. This requirement drives special needs in MCU and firmware algorithms. 32-bit ARM architecture is a popular CPU technology for wearable devices as it provides best performance and energy efficiency. Also wireless technologies such as ANT+, Bluetooth Low Energy (BLE) are designed to consume low power.

Wireless communication: Wireless connectivity is important for wearable devices as they need to interact with one or more other devices. Depending on the type and features offered, the device is required to support different wireless protocols such as Wi-Fi, ANT+, Bluetooth Low Energy (BLE), and IEEE 802.15.4 based proprietary protocol. Some devices are required to support multiple protocols. For example, a wrist watch communicates with a heart rate monitoring chest strap using a proprietary wireless protocol and also it communicates to a running application in a mobile phone using BLE.

Selecting the right app processor or microcontroller
The selection of the main processor is driven by the type and features of the device. Except for advanced infotainment devices which requires an application processor, MCUs can address most of the types of wearable devices. Also the latest MCUs integrate most of the functions in a single chip. This is important in reducing the overall size of a wearable device and BOM cost.

For example, an ARM cortex-M controller ( can power a simple wrist band but a smart watch requires an application processor in order to run a complex operating system such as Android.

As explained earlier, 32-bit ARM processors are popular in wearable devices as they provide the best computing performance and energy efficiency. Modern controllers such as the PSoC integrate sophisticated analog and programmable digital functionality in a single chip, along with an ARM cortex-M core, utilizing the power of the ARM architecture.

Some advanced devices have a separate co-processor to offload the processing of sensor data from the main processor. This is required when the device has loads of sensor data that needs to be analyzed together in real time, requiring constant CPU attention. This function is called ‘sensor hub’ or ‘sensor fusion’. Figure 1 illustrates the role of a sensor hub in a wearable system.

Figure 1: Role of sensor hub in a wearable system

Operating System: Depending on the features offered, a wearable device may or may not need a specific operating system. For example, a simple wrist watch that monitors temperature, measures movement using a 3-axis accelerometer, and displays time on a monochromatic segment LCD display can run with a lightweight RTOS, whereas a smart watch that is designed to be an extension of your mobile phone needs to run an advanced operating system such as Android. At the same time, sensor hubs require special firmware with context aware algorithms.

< Previous
Page 1 of 2
Next >

Loading comments...