Whether you are trying to drop some fat or build some muscle, it’s important to track progress. It’s easy enough to track your weight, but weight doesn’t tell the whole story. You might be burning fat but also building muscle, which can make it appear as though you aren’t losing weight at all. A more useful number is body fat percentage. Students from Cornell have developed their own version of an electrical body fat analyzer to help track body fat percentage.
Fat free body mass contains mostly water, whereas fat contains very little water. This means that if you were to pass an electrical current through a body, the overall bioelectrical impedance will vary depending on how much fat or water there is. This isn’t a perfect system, but it can give a rough approximation in a relatively easy way.
The students’ system places an electrode on one hand and another on the opposite foot. This provides the longest electrical path possible in the human body to allow for the most accurate measurement possible. An ATMega1284P is used to generate a 50kHz square wave signal. This signal is opto-isolated for user safety. Another stage of the circuit then uses this source signal to generate a 10ua current source at 50kHz. This is passed through a human body and fed back to the microcontroller for analysis.
The voltage reading is sent to a MATLAB script via serial. The user must also enter in their weight and age. The MATLAB script uses these numbers combined with the voltage reading to estimate the body fat percentage. In order to calibrate the system, the students measured the body fat of 12 of their peers using body fat calipers. They admit that their sample size is too small. All of the sample subjects are about 21 years old and have a similar body fat percentage. This means that their system is currently very accurate for people in this range, but likely less accurate for anyone else. Continue reading “DIY Electrical Body Fat Analyzer”
While most people are moving onto ARMs and other high-spec microcontrollers, [Dave Cheney] is bucking the trend. Don’t worry, it’s for a good reason – he’s continuing work on one of those vintage CPU/microcontroller mashups that implement an entire vintage system in two chips.
While toying around with the project, he found the microcontroller he was using, the ATMega1284p, was actually pretty cool. It has eight times the RAM as the ever-popular 328p, and twice as much RAM as the ATMega2560p found in the Arduino Mega. With 128k of Flash, 4k of EEPROM, 32 IOs, and eight analog inputs, it really starts to look like the chip the Arduino should have been built around. Of course historical choices don’t matter, because [Dave] can just make his own 1284p prototyping board.
The board is laid out in Fritzing with just a few parts including a crystal, a few caps, an ISP connector, and pins for a serial connector. Not much, but that’s all you need for a prototyping board.
The bootloader is handled by [Maniacbug]’s Mighty 1284 Arduino Support Package. This only supports Arduino 1.0, not the newer 1.5 versions, but now [Dave] has a great little prototyping board that can be put together from perfboard and bare components in a few hours. It’s also a great tool to continue the development of [Dave]’s Apple I replica.
It makes an Arduino look like a 555. A 364 Mhz, 32 bit processor. 8 MB RAM. GSM. Bluetooth. LCD controller. PWM. USB and dozens more. Smaller than a Zippo and thinner than corrugated cardboard. And here is the kicker: $3. So why isn’t everyone using it? They can’t.
Adoption would mandate tier after tier of hacks just to figure out what exact hardware is there. Try to buy one and find that suppliers close their doors to foreigners. Try to use one, and only hints of incomplete documentation will be found. Is the problem patents? No, not really.
[Bunnie] has dubbed the phenomenon “Gongkai”, a type of institutionalized, collaborative, infringementesque knowledge-exchange that occupies an IP equivalent of bartering. Not quite open source, not quite proprietary. Legally, this sharing is only grey-market on paper, but widespread and quasi-accepted in practice – even among the rights holders. [Bunnie] figures it is just the way business is done in the East and it is a way that is encouraging innovation by knocking down barriers to entry. Chinese startups can churn out gimmicky trash almost on whim, using hardware most of us could only dream about for a serious project.
Continue reading “Reverse-Engineering a Superior Chinese Product”
[Eberhard] needed to flash several hundred ATMegas for a project he was working on. This was a problem, but the task did have a few things going for it that made automation easy. The boards the ‘Megas were soldered to weren’t depanelized yet, and he had a neat and weird bed of nails programming connector. There was also a CNC machine close by. This sounds like the ideal situation for automation, and it turns out the setup was pretty easy.
The boards in question were for FPV/radio control telemetry adapter and thankfully the assembly house didn’t depanelize the 40 PCBs on each board before shipping them out. A very cool ATMega flashing tool handled the electrical connections between the computer and the microcontroller, but a real, live human being was still required to move this flashing tool from one chip to the next, upload the firmware, and repeat the process all over again.
The solution came by putting a few metal pins in the bed of a CNC mill, 3D print an adapter for the flashing tool, and writing a little code to move the flashing tool from one chip to the next. An extremely simple app takes care of moving the programmer to an unflashed chip, uploading the firmware, and continuing on to the next chip.
There’s still some work to be done that would basically tie together the Gcode and AVRdude commands into a single interface, but even now a complete panel of 40 PCBs can be programmed in a little over 10 minutes. You can check out a video of that below.
Continue reading “Flashing Chips With A CNC”
The Apple I, [Woz]’s original, had about sixty chips on a single board. Most of these chips were logic glue or hilariously ancient DRAMs. The real work was done by the 6502, the 6821 PIA, and the Signetics video chip. It’s a simple computer, really, and following the now popular tradition of two-chip computers, [Dave] built a replica of the Apple I using a 6502 and an ATMega.
The ATMega in this project takes care of everything – the 4k of RAM, the few bytes of ROM, the IO, and even the clock. With the 6502 you can have a little bit of fun with the clock; because the 6502 reads data off the bus a few nanoseconds off the falling edge of the clock and writes on the rising edge, [Dave] played around with the duty cycle of the clock to give the ATMega a bit more time to do its thing. With a 50% duty cycle, the 16Mhz ‘Mega has about eight cycles to decode an address and read or write some data. By making the low part of a clock cycle longer, he has about 45 cycles on the ‘Mega to do all the work. All of this was inspired by a fantastic tutorial on the 6502 clock.
Right now [Dave] has some hex values displaying on a small LCD, while the real I/O is handled by a serial connection to a computer. It’s retro enough, and a future update will include a faux cassette interface, possibly using an SD card for storage.
A team of Cornell students have designed and built their own electronic boxing trainer system. The product of their work is a game similar to Whack-A-Mole. There are five square pads organized roughly into the shape of a human torso and head. Each pad will light up based on a pre-programmed pattern. When the pad lights up, it’s the player’s job to punch it! The game keeps track of the player’s accuracy as well as their reaction time.
The team was trying to keep their budget under $100, which meant that off the shelf components would be too costly. To remedy this, they designed their own force sensors. The sensors are basically a sandwich of a few different materials. In the center is a 10″ by 10″ square of ESD foam. Pressed against it is a 1/2″ thick sheet of insulating foam rubber. This foam rubber sheet has 1/4″ slits cut into it, resulting in something that looks like jail bars. Sandwiching these two pieces of foam is fine aluminum window screen. Copper wire is fixed the screen using conductive glue. Finally, the whole thing is sandwiched between flattened pieces of corrugated cardboard to protect the screen.
The sensors are mounted flat against a wall. When a user punches a sensor, it compresses. This compression causes the resistance between the two pieces of aluminum screen to change. The resistance can be measured to detect a hit. The students found that if the sensor is hit harder, more surface area becomes compressed. This results in a greater change in resistance and can then be measured as a more powerful hit. Unfortunately it would need to be calibrated depending on what is hitting the sensor, since the size of the hitter can throw off calibration.
Each sensor pad is surrounded by a strip of LEDs. The LEDs light up to indicate which pad the user is supposed to hit. Everything is controlled by an ATMEGA 1284p microcontroller. This is the latest in a string of student projects to come out of Cornell. Make sure to watch the demonstration video below. Continue reading “Boxing Trainer Uses DIY Force Sensors”
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”