Keyboards vs. Brain-Computer Interfaces

Hi! Today we’re going to be comparing the usability of various household devices (Microwave, TV remote, keyboard, etc.) against those of research devices (like eye trackers and brain-computer interfaces).

Information Transfer Rate and Bits/Min

To do this, we’ll be investigating each device’s information transfer rate (ITR), or how fast the user can communicate with the device. We have some intuitive sense of this — obviously the keyboard allows for faster and more varied input than the TV remote. It’d be easy to compare the speeds if they had the same number of buttons, but since they don’t, we have to define some common metric to measure information input speed. This will be calculated in units of bits per minute.

Inspiration

While reading about the information transfer rate of tech still in development (eye tracking, brain-computer interfaces, etc.), I wanted to see how far they were from being practical e.g. in comparison to normal devices we use today. Since most researchers will standardize their results into units of bits per minute, I figured I could just calculate the bits/min of household devices and compare the two.

List of Common Input Devices

Here’s the compiled table as a TL;DR:

Table of common input devices and how many bits/min their interfaces allow
Table of information transfer rates of all common devices

Thermostat: 209 bits/min

TV Remote: 453 bits/min

Microwave: 564 bits/min

Game Controller: 4,482 bits/min

They control nuclear submarines with these!

Touchscreen: 2,744 bits/min

The Apple iPhone 11, most sold phone in 2019.
Icons from the navigation bar on Instagram. Green box is 100 by 75 pixels. Note how it’s rectangular in the x-axis. It’s much easier to press very wide, short buttons than very tall, skinny buttons on a smartphone, which I didn’t realize before.

Touchscreen (Stylus): 2,852 bits/min

Though not many smartphones these days have a stylus anymore, it does allow much more pinpoint clicks while allowing the same speed and gestures that using a finger does. I’m going to use the same speeds for taps, holds, drags, but will not count swipes or pinches since they are only possible with fingers.

Touchscreen (Keyboard): 2,491 bits/min

Picture of the iPhone keyboard, with diction key highlighted. I didn’t want to find another picture so I reused this one

Mouse/trackpad + Screen: 2,864 bits/min

Macbook Air
Smaller of the “smallest reliable click size” bounding boxes. This is from the Chrome toolbar, and has size 30x30 pixels.
Picture of the first mouse

Keyboard: 5,125 bits/min

Physical keyboard, reduced because it doesn’t have the numpad on the right.

Physical Keyboard Total Bits/min: 5,125

Table of information transfer rates of all research devices

List of Experimental Input Devices

These are research devices that are still working out the kinks, and don’t work incredibly reliably yet. I’m including voice control because it’s a biometric device instead of a button input like the earlier ones, and doesn’t work for everyone’s voice yet.

Voice Control (Diction): 4,835 bits/min

Voice control or diction button on an iPhone keyboard

Bits/min: 4,835

Fingerprint/Face recognition

This is probably a special class of “input”, but I thought it’d be cool to include.

Fingerprints: 1,196 bits/min

NIST says fingerprint scanners only give false positives 0.01% of the time. Assuming this is consistent, the fingerprint scanner reliably can differentiate you and 700,000 others from everyone else on earth, which is 10,000 other groups of 700,000 people. I’ll say that’s 10,000 inputs. My phone takes around 1 second to scan, but sometimes fails, so I’ll say it operates at 1.5/sec.

Fingerprint Scanner Bits/min: 1,196

Face: 617 bits/min

Also from NIST, the best face recognition has a false positive rate of 0.08%, which is much higher than the fingerprint scanner. You’ll be reliably recognized along with 5,600,000 others by the best face recognition, which is 1/1250 groups. It is much faster than a fingerprint scanner though, at least on the iPhone.

Face Recognition Bits/min: 617

Eye tracking: 584 bits/min

Screenshot of someone using a Tobii Eye Tracker. The big blob is the predicted gaze location, which takes up about 10% of the screen

Eye Tracker Bits/min: 417 clicking, 584 blinking

Brain-computer interfaces (EEG): 199 bits/min

There’s a few different ways to detect what someone’s thinking of. I’ll go over both the P300 and SSVEP.

P300

The P300 is a signal that arises when your expectation of what you’re seeing is different from what you expect it to be. These BCIs work by flashing a grid of objects (letters, labeled buttons) and removing one object each time. If you ever don’t see the one you’re trying to select, then your brain emits a P300. It needs a lot of averaging across many trials to be done reliably though, and it’s a very unintuitive way to select things.

A flowchart of SSVEP brain signal processing

SSVEP

The SSVEP is a signal that is also evoked by visual stimulus, but in this case it’s caused by repeated flashes of light. It can be reliably detected for flickering between 10 and 20Hz. To use the SSVEP as input, you create an LED display or use a monitor with many buttons on it which are each flashing at a different frequency. Then, you look at the buttons for a short window of time. The frequency spectrum of the recorded EEG signal will have a peak at the frequency of the button you were focusing on, and the computer will know which one you want to select.

BCI Bits/min: 199

Discussion

The computer (trackpad + screen + keyboard) has undoubtedly the highest input rate of any device, clocking in at 7,989 bits/min. It seems that bits/min comes more from an interface which registers button presses quickly than one that offers many simultaneously available options, since the log term quickly drives that down.

Credits

Adapted from original blog post here: https://andykong.org/blog/interfacespeeds/

Hi! I’m Andy. I try to make things that haven’t been made before. Check out my personal projects at https://andykong.org/

Get the Medium app

A button that says 'Download on the App Store', and if clicked it will lead you to the iOS App store
A button that says 'Get it on, Google Play', and if clicked it will lead you to the Google Play store