Body Sensors Going Wireless, Smart and Low Power
Capturing posture, gesture and motion of the human body is proving useful in a variety of fields such as sports training or physical medicine and rehabilitation. But how to collect the data without resorting to cumbersome paraphernalia? A network of wireless sensors also known as Body Area network (BAN) is a promising alternative. However, power consumption remains very much an issue. Developed by a group of French researchers, Zyggie is an innovative BAN platform that leverages distributed computation as well as radio communication distance measurement in order to reach a much higher level of energy efficiency.
Estimating body motion is something scientists have been doing for well over two decades now, using a variety of techniques ranging from multiple infrared cameras systems to so-called ‘motion capture suits’ fitted with wired inertial sensors. Each approach comes with its own advantages. Nevertheless, none of them would claim to be a paragon of practicality.
“That's why we opted for wireless sensors, ” says Olivier Sentieys, head of Cairn, a research team specializing in comuting architectures for energy efficient systems-on-chip. The group has partnered with two other labs —Lab-STICC and IETR— in BoWi, a French research projectdedicated to designing a cutting edge Body Area Network that would accurately estimate gesture and motion while complying at the very same time with drastic power consumption constraints.
Zyggie is the experimental BAN platform born of this effort. It takes the form of several wireless sensor nodes that can be strapped to different parts of the human body. Nested in each device are three inertial sensors : an accelerometer, a gyrometer and a magnetometer. These are usually referred to as IMUs (Inertial Measurement Units). In addition, comes an embedded processor as well as a low-power radio module meant to communicate the data to a coordinator element that can be connected to a computer or a smartphone.
But the two chief innovations lie somewhere else. “First of all, we use radio-transmission to measure the distance between nodes in order to improve the accuracy of the 3D localization and to avoid the drift of IMU sensors. This distance could be inferred from the velocity of the signal propagation or the strength of the received signal. We opted for the latter method. Granted it is not very accurate but it is still sufficient for ascertaining the distance in our context. ”
The second novelty deals with data fusion and distributed computation. “Each of our nodes is able to combine sensor data with signal strength information, compute its position with respect to neighbors, and eventually only send the result. Computing locally instead of transmitting the raw data to a centralized unit is a very rewarding strategy for dramatically decreasing energy consumption.
” In the future, this low-power architecture might also pave the way to the replacement of the battery by some on-body energy harvesting alternative.
Started in 2012, the BoWi project is already well under way. “We have a prototype up and running. Most of our experiments will be over by the end of this year. A lot of metrics should be available by that time. But it already appears that this technology has reached such a level of maturity that it is just one step away from becoming a product. ”
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BoWI is a project sponsored by CominLabs, an IT laboratory born from the French Government's “Investissements d'Avenir” program for the creation of laboratories of excellence (Labex). CominLabs is located in the regions of Brittany and Pays de la Loire. The scientists involved in BoWI are members of Inria, CNRS, Université Rennes 1, UBS, Insa Rennes and Telecom Bretagne.