Ever tire of having to constantly learn how to operate new devices? Want to complete tasks by simply following your usual activities of daily living? Have an elderly loved one who wants to stay independent but can’t handle any additional tasks? If so, Translational Reality may be the solution. At a minimum, it can change your mind about learning, training and working with new devices.

Translational Reality  is a real-time, closed loop system in which a user operates a familiar first device and, in so doing, both monitors and controls a second device. User feedback is appropriate to the first device, but reflects the operation of the second device.

The Pain

I’ve spent a good portion of my life learning to do new things – from mowing the lawn and driving a car to operating an oscilloscope. And, over time, as the various devices evolved, I have had to devote additional time to learning each version. Given that there is so much to learn and so little time, there must be a better way to master a musical instrument, a martial art, or how to operate a piece of machinery than by practicing and training for thousands of hours. And although the technology is conceptually appealing, I’m just not quite ready for the brain-jacks used in the Matrix.

A frustrating aspect of learning to do something new is that the integration of motor skills lags behind cognition. For example, I’ve recently taken up the piano. From playing the guitar, I understand the concepts of sharps and flats, keys, octaves, and other music theory. Even so, without some sort of technological assistance, Beethoven’s Moonlight Sonata is years away. And that’s OK, because I enjoy the learning process. However, there are many skills – mainly work related – that I don’t enjoy learning and relearning. I’m counting on the proposition that an old dog can at least perform new tricks – perhaps without even knowing it, given a bit of technological wizardry.

Solution

There’s plenty of technological wizardry to go around, from smart devices and the Internet of Things (IoT) to simulation, virtual and augmented reality. Certain extensions of these technologies, in the form of a Translational Reality interface, can enable a user skilled in the operation of one device to indirectly operate another device that may not be known to them. The other device could be anything from an updated version of a spectrum analyzer to a CNC controller.

Let’s explore the basic principles of a Translational Reality interface, using a light level to audio level translation. Translational Reality is a closed loop, real-time interface. In this example, the operator interacts with the lamp by adjusting the dimmer knob and observing the resulting illumination. Let’s say turning the knob clockwise increases illumination and a counterclockwise turn decreases illumination.

However, unlike the behavior of an ordinary lamp, the dimmer setting doesn’t directly control the light output. Instead, the desired illumination setting is communicated to signal processor, which could be embedded in the lamp. After processing, which could include translating, scaling, and other manipulation, the signal is communicated to the remote audio device as a volume control value. In this way, the operator controls the volume of the audio device by adjusting the dimmer knob on the lamp. And, by the way, there’s no cheating – the user can’t hear the remote audio device.

Now, completing the loop back to the lamp, a microphone in the room picks up the audio from the remote audio device. Alternatively, the audio is picked up directly from the remote device. The signal is processed and communicated to the dimmer circuitry, thereby determining the level of illumination. The signal processing depends on the relationship of the two devices. For example, rotating the dimmer switch clockwise could decrease or increase the volume of the audio generated by the audio device in either a linear or log manner.

If the devices are smart– each have an embedded processor, and perhaps web connectivity, then communications can be handled over the web. Alternatively, the processor(s) could be external to the ordinary devices.