So often, we use control devices for electronics that involve our fingers directly grasping, touching, or moving another object or surface. It’s less common for us to use interfaces that detect the motion of our bodies directly. Flex sensors are one way to do that, and it’s exactly what [WillpowerStudios] aims to do with Finger Bend.
The construction of the sensor is simple, using piezoresistive fabric which changes its resistance when deformed. By sewing this into a sheath that can be placed on the finger, and wiring it up with conductive threads, it can be used to detect the flexion of the wearer’s digits by sampling the resistance with an analog to digital converter on any garden variety microcontroller. Expanding the technique to a full hand is as simple as creating a Finger Bend per digit and wiring up each one to its own ADC channel. If you want to get really fancy, you could even scan through them at speed with a multiplexer.
It’s similar to the technology used in Nintendo’s infamous Power Glove, and while it’s never caught on in the mainstream, it may have applications yet. Video after the break
Continue reading “Finger Bend Is A Textile Flex Sensor You Can Sew At Home”
Hackaday editors Elliot Williams and Mike Szczys recap a week of hacks. A telescope mirror that can change shape and a helicopter without a swashplate lead the charge for fascinating engineering. These are closely followed by a vibratory wind generator that has no blades to spin. The Open Source Hardware Association announced a new spec this week to remove “Master” and “Slave” terminology from SPI pin names. The Segway is no more. And a bit of bravery and rock solid soldering skills can resurrect that Macbook that has one dead GPU.
Take a look at the links below if you want to follow along, and as always, tell us what you think about this episode in the comments!
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Continue reading “Hackaday Podcast 074: Stuttering Swashplate, Bending Mirrors, Chasing Curves, And Farewell To Segway”
If you’ve spent any serious time in libraries, you’ve probably noticed that they attract people who want or need to be alone without being isolated. In this space, a kind of silent community is formed. This phenomenon was the inspiration [MoonAnchor23] needed to build a network of connected house plants for a course on physical interaction and realization. But you won’t find these plants unleashing their dry wit on twitter. They only talk to each other and to nearby humans.
No living plants were harmed during this project—the leaves likely wouldn’t let much light through, anyway. The plants are each equipped with a strip of addressable RGB LEDs and a flex sensor controlled by an Arduino Uno. Both are hot glued to the undersides of the leaves and hidden with green tape. By default, the plants are set to give ambient light. But if someone strokes the leaf with the flex sensor, it sends a secret message to the other plant that induces light patterns.
Right now, the plants communicate over Bluetooth using an OpenFrameworks server on a local PC. Eventually, the plan is use a master-slave configuration so the plants can be farther apart. Stroke that mouse button to see a brief demo video after the break. [MoonAnchor23] also built LED mushroom clusters out of silicone and cling wrap using a structural soldering method by [DIY Perks] that’s also after the break. These work similarly but use force-sensing resistors instead of flex-sensing.
Networking several plants together could get expensive pretty quickly, but DIY flex sensors would help keep the BOM costs down. Continue reading “Interactive Plant Lamps For Quiet Spaces”
Back problems are some of the most common injuries among office workers and other jobs of a white-collar nature. These are injuries that develop over a long period of time and are often caused by poor posture or bad ergonomics. Some of the electrical engineering students at Cornell recognized this problem and used their senior design project to address this issue. [Rohit Jha], [Amanda Pustis], and [Erissa Irani] designed and built a posture correcting device that alerts the wearer whenever their spine isn’t in the ideal position.
The device fits into a tight-fitting shirt. The sensor itself is a flex sensor from Sparkfun which can detect deflections. This data is then read by a PIC32 microcontroller. Feedback for the wearer is done by a vibration motor and a TFT display with a push button. Of course, they didn’t just wire everything up and call it a day; there was a lot of biology research that went into this. The students worked to determine the most ideal posture for a typical person, the best place to put the sensor, and the best type of feedback to send out for a comfortable user experience.
We’re always excited to see the senior design projects from university students. They often push the boundaries of conventional thinking, and that’s exactly the skill that next generation of engineers will need. Be sure to check out the video of the project below, and if you want to see more of this semester’s other projects, we have you covered there too. Continue reading “Cornell Students Have Your Back”
Adjusting the volume dial on a sound system, sensing your finger position on a touch screen, and knowing when someone’s in the car are just a few examples of where you encounter variable resistors in everyday life. The ability to change resistance means the ability to interact, and that’s why variable resistance devices are found in so many things.
The principles are the same, but there are so many ways to split a volt. Let’s take a look at what goes into rotary pots, rheostats, membrane potentiometers, resistive touchscreens, force sensitive resistors, as well as flex and stretch sensors.
Continue reading “Resistance In Motion: What You Should Know About Variable Resistors”
Normally, strain sensors are limited in their flexibility by the underlying substrate. This lead researchers at the University of Manitoba to an off-the-wall solution: mixing carbon nanotubes into a chewing-gum base. You can watch their demo video below the break.
The procedure, documented with good scientific rigor, is to have a graduate student chew a couple sticks of Doublemint for half an hour, and then wash the gum in ethanol and dry it out overnight. Carbon nanotubes are then added, and the gum is repeatedly stretched and folded, like you would with pizza dough, to align the ‘tubes. After that, just hook up electrodes and measure the resistance as you bend it.
The obvious advantage of a gum sensor is that it’s slightly sticky and very stretchy. The team says it works when stretched up to five times its resting length. Try that with your Power Glove.
We’ve seen a couple different DIY flex sensor solutions around these parts, one based on compressing black conductive foam and another using anti-static bags, but the high-tech, low-tech mixture of nanotubes and Wrigley’s is a new one.
Continue reading “Chewing Gum Plus Carbon Nanotubes”
A team of Cornell students recently built a prototype electronic glove that can detect sign language and speak the characters out loud. The glove is designed to work with a variety of hand sizes, but currently only fits on the right hand.
The glove uses several different sensors to detect hand motion and position. Perhaps the most obvious are the flex sensors that cover each finger. These sensors can detect how each finger is bent by changing the resistance according to the degree of the bend. The glove also contains an MPU-6050 3-axis accelerometer and gyroscope. This sensor can detect the hand’s orientation as well as rotational movement.
While the more high-tech sensors are used to detect most characters, there are a few letters that are similar enough to trick the system. Specifically, they had trouble with the letters R, U, and V. To get around this, the students strategically placed copper tape in several locations on the fingers. When two pieces of tape come together, it closes a circuit and acts as a momentary switch.
The sensor data is collected by an ATmega1284p microcontroller and is then compiled into a packet. This packet gets sent to a PC which then does the heavy processing. The system uses a machine learning algorithm. The user can train the it by gesturing for each letter of the alphabet multiple times. The system will collect all of this data and store it into a data set that can then be used for detection.
This is a great project to take on. If you need more inspiration there’s a lot to be found, including another Cornell project that speaks the letters you sign, as well as this one which straps all needed parts to your forearm.
Continue reading “Electronic Glove Detects Sign Language”