You’ll Be Shocked At This Way To Improve Your Video Game High Score

What if you could play video games perfectly? Would you be one of the greats, raking in millions of dollars simply by playing competitive Fortnite? That’s what Twitch does. Twitch plays video games for you. The irony of this name should not be lost on you.

For his Hackaday Prize entry, [Peter] built a device that shocks you into playing a computer game perfectly. These experiments began with a transcutaneous electrical nerve stimulator (TENS), or basically a device that makes you… twitch. This device, however, is connected to four buttons, representing up, down, left, and right. This is a video game controller, that will make your muscles contract automatically. See where this is going?

To play a video game perfectly, you need a video game. For that, [Peter] chose the classic Snake game. The computer runs the game, and figures out if the next move will be up, down, left, or right. This bit of information is then sent to the TENS device, forcing the player to move the snake up, down, left, or right. The computer can’t directly control the snake, it merely has the human in the loop. The human becomes part of the program.

We’re getting into weird cyberpunk territory here, and it’s awesome. Is the human directly responsible for winning the game? What are the philosophical ramifications? What episode of Star Trek was this from? It’s a great entry for the Hackaday Prize – cyberpunk and a neat video (available below) all wrapped up into one package.

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Medium Machine Mediates Microcontroller Messages

Connecting computers to human brains is currently limited to the scope of science fiction and a few cutting-edge laboratories. Tapping into some nerves farther from our central wetware is possible and [Peter Buczkowski] shows us his stylish machine for implanting a pattern into our brains without actively having to memorize anything.

His Medium Machine leverages a TENS unit to activate forearm muscles in a pattern programmed into an Arduino. Users place their forearm across two aluminum electrodes mounted on a tasteful wooden platform and extend a single finger over a button. Electrical impulses trigger the muscles which press the button. That’s all. After repeating the pattern a few times, the users should be able to recite it back on command even if they aren’t aware of what it means. If this sounds like some [Johnny Mnemonic] memory cache, you are absolutely correct. This project draws inspiration from the [William Gibson] novel which became a [Keanu Reeves] movie.

Users can be programmed with a Morse code message or the secret knock to open an attic library or play a little tune. How about learning a piano song?

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Neural Network Zaps You to Take Better Photographs

It’s ridiculously easy to take a bad photograph. Your brain is a far better Photoshop than Photoshop, and the amount of editing it does on the scenes your eyes capture often results in marked and disappointing differences between what you saw and what you shot.

Taking your brain out of the photography loop is the goal of [Peter Buczkowski]’s “prosthetic photographer.” The idea is to use a neural network to constantly analyze a scene until maximal aesthetic value is achieved, at which point the user unconsciously takes the photograph.

But the human-computer interface is the interesting bit — the device uses a transcutaneous electrical nerve stimulator (TENS) wired to electrodes in the handgrip to involuntarily contract the user’s finger muscles and squeeze the trigger. (Editor’s Note: This project is about as sci-fi as it gets — the computer brain is pulling the strings of the meat puppet. Whoah.)

Meanwhile, back in reality, it’s not too strange a project. A Raspberry Pi watches the scene through a Pi Cam and uses a TensorFlow neural net trained against a set of high-quality photos to determine when to trip the shutter. The video below shows it in action, and [Peter]’s blog has some of the photos taken with it.

We’re not sure this is exactly the next “must have” camera accessory, and it probably won’t help with snapshots and selfies, but it’s an interesting take on the human-device interface. And if you’re thinking about the possibilities of a neural net inside your camera to prompt you when to take a picture, you might want to check out our primer on TensorFlow to get started.

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Building a Transcutaneous Electrical Nerve Stimulation Device in a Weekend

Transcutaneous electrical nerve stimulation (TENS) is a technique that applies electrical current to nerves and muscles for the relief of pain. Before you ask, yes, some of these devices are FDA approved for various ailments. [Eric], [Conor], [Jacob], [lnr0626] and [rdrdrdrd] were down at HackDFW this weekend and built a TENS device from parts in their scrap bin.

A semi-decent TENS machine can cost somewhere between $70 and $200, but the team here have reduced the cost tremendously simply by separating the futzing analog/contact pad part from the signal generation part of the project. The signal generation actually happens on an Android phone, with settings to ‘relieve pain’, ‘relax’, ‘pulse’, and ‘random’. These signals are generated as audio and sent out over the headphone port. From there, the signal is amplified and sent to the neat skin-contact pads.

After prototyping their circuit, the team actually etched a circuit board for the final phase of the hackathon. Demo video below.

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