Watts new in wearables


Welcome to the Consumer Electronics Show! I’m excited to be heading back to one of the world’s biggest tech bonanzas, and this time to have a print companion that proves I actually cover the technology there and don’t just show up to play with cool new toys.

At CES 2015, were all the rage. In fact, most of the Sands Expo & Convention Center at The Venetian was dedicated to fitness trackers, health monitors, and early iterations of the smart watch, among other wearable tech, leading to high expectations for this new niche of personal computing devices over the ensuing year.

However, as 2015 progressed, that excitement was tempered. With the flop of Google Glass and a decidedly underwhelming reception for Apple’s iWatch, the market sputtered and all of a sudden we began to raise a sobering question: Are we solving problems that don’t exist? So far, the answer seems to be “yes.”

Take the smart watch, for example. Not to diminish the pioneering achievements of Apple and Samsung as the nature of technological evolution means we have to have the Motorola brick before we can fire up our iPhone 6s, but the problem with current smart watches is that they are extremely limited versions of the smartphones they tether to just a few inches away. In large part these restrictions are the result of limitations onboard the wearable platform itself, where more advanced sensor applications such as voice recognition, indoor navigation, and new forms of medical or environmental monitoring require increasingly complex algorithms, which in turn demand more MIPS (or millions of instructions per second of processor performance). Of course, the more MIPS executed, the more power used by a wearable’s system-on-chip (), meaning less time between charges for systems that currently only have an average battery life of “18 hours after an overnight charge,” like the Apple Watch.[1]

With energy harvesting still in its early stages (as discussed in my March 2015 column inn ), this means that power consumption must be addressed at the SoC and algorithm levels. One way to achieve this is through with certain cores optimized for and dedicated to sensor , while others are reserved for general-purpose tasks. For example, the QuickLogic EOS3 sensor processing platform includes an ARM Cortex-M4 MCU, front-end sensor manager, and microDSP-like Flexible Fusion Engine (FFE), the latter of which handles the bulk of algorithm processing to free up the ARM core for a solution the company says provides 70 percent more compute performance at one-third the power of a typical Cortex-M4-based MCU (quicklogic.com/eos). One of several reasons this is possible is that the specialized FFE doesn’t move data between a register and the memory, which consumes 40 percent of the power on load/store MCU architectures like ARM. Using a similar technology leveraging QuickLogic’s FFE and optimized SenseMe algorithms, fitness wearable vendor Runtastic (recently acquired by ) was able to achieve an average power consumption of 75 µW on its Moment watch, extending the battery life of a coin cell to six months.

Figure 1 | The QuickLogic EOS3 sensor processing platform includes a Flexible Fusion Engine (FFE) capable of processing algorithms at as low as 12.5 µW/Dhrystone MIPS.

Watching for wearable innovation at CES 2016

For those interested, QuickLogic will have a presence at the MEMS Industry Group booth located in the Venetian (booth number 70536) and meeting suite MP25660 in the South Hall of the Las Vegas Convention Center (LVCC). As for myself, I’ll be zigzagging the LVCC and surrounding area January 6-8. Drop me a line at blewis@opensystemsmedia.com to talk wearables, smart home, automotive, or other tech.

1. Apple. “General Battery Information.” November 9, 2015. http://www.apple.com/watch/battery.html.