Scientists at the University of Washington (UW), have developed self-tracking 3D printed devices that can provide analytics without using batteries or electronics.
Jennifer Mankoff, Engineering Professor at the UW and part of the engineering team, said, “We’re interested in making accessible assistive technology with 3-D printing, but we have no easy way to know how people are using it.” Mankoff continued, “Could we come up with a circuitless solution that could be printed on consumer-grade, off-the-shelf printers and allow the device itself to collect information? That’s what we showed was possible in this paper.”
To develop these devices, the engineering team used a method called ambient backscatter. This method uses antennas and radio signals for data transmission without battery or power.
Self-tracking 3D printed devices
The engineering team had previously worked on developing 3D printed objects that can communicate via Wi-Fi without electronics. An example device is one which orders detergent online if the detergent bottle runs low. But such a device only monitored data in one direction.
This time the researchers wanted something more sophisticated. A device that could support bidirectional motion, and storage and retrieval of data outside wireless coverage.
A challenge was to figure out a method to monitor movement in both directions, such as the opening and closing of a pill bottle. How did the team solve the problem?
Engineering student and co-author of the paper, Vikram Iyer, explained, “this time we have two antennas, one on top and one on the bottom, that can be contacted by a switch attached to a gear. So opening a pill bottle cap moves the gear in one direction, which pushes the switch to contact one of the two antennas. And then closing the pill bottle cap turns the gear in the opposite direction, and the switch hits the other antenna.”
To decode the direction of the bottle cap, the teeth of the gears have a morse code like sequencing code. Forward motion sends a different message than backward motion.
According to the researchers, the same concepts can work with 3D printed prosthetics such as e-NABLE arms. To show this, the team integrated the bi-directional backscatter designs within existing CAD models, in particular, with a 3D printed e-NABLE prosthetic arm. The backscatter system developed by the team was able to record the opening and closing of the arm at 15° angle.
Currently, these devices are only prototypes to show that 3D printed objects can sense bidirectional movement and store data. The challenge is to shrink the system and embed them within fully developed usable 3D printed devices.
Professor Mankoff said, “this system will give us a higher-fidelity picture of what is going on,” she said. “For example, right now we don’t have a way of tracking if and how people are using e-NABLE hands.”
“Ultimately what I’d like to do with these data is predict whether or not people are going to abandon a device based on how they’re using it.”
e-NABLING with 3D printing
e-NABLE, an open source 3D prosthetic community has been very active globally. The organization received a $600,000 grant from Google to develop 6,000 3D printed prosthetics in 2 years.
The organization has worked to provide low-cost 3D printed prosthetics to amputees in war zones and earthquake-affected areas, such as Haiti.
As previously reported, e-NABLE also collaborated with Simplify3D, a 3D printing software developer. The collaboration provided 3D printed prosthetics to children.
The University of Washington research brings hopeful news for the e-NABLE community and the wearers of the e-NABLE prosthetics. The recent innovation may lead to better open source prosthetics.
The research paper is titled, Wireless Analytics for 3D Printed Objects, co-authored by Vikram Iyer, Justin Chan, Ian Culhane, Jennifer Mankoff, and Shyamnath Gollakota. The research findings will be presented on October 15 at the ACM Symposium on User Interface Software and Technology, Berlin.
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Featured image shows a 3D printed e-NABLE prosthetic hand. Image via Mark Stone/University of Washington
