Skip to main content

What Is Healthy Human-Computer Interaction?

Written by: The Wiley Network
Published on: Jul 5, 2021

Human Computer Interaction
Image credit: Odua Images/Shutterstock

This article is brought to you by The Wiley Network where you can explore resources for Researchers, Educators and Professionals, including support for the Covid-19 crisis.

In a podcast episode (which you can listen to here), James Bowen, CEO of Experimental Simulations, spoke with Simon Morris and Tara Akhavan, CEO and CTO of IRYstec, about the need for healthy machine-human interaction and how to take an interdisciplinary approach to producing a measurable human health improvement when using computer displays.

Here are some highlights from that discussion.*


What are some of the issues that you’re running up against to try and convince people to change their behaviors and the way that we think about the way that humans and computers interact?

We have to consider how our eye behaves and works and combine the physiology of the eye with processing computer vision processing algorithms to address a range of issues that we’re facing today with this role that displays play in our lives.

We spend eight hours, if not more, in front of displays—laptop, mobile phones in particular, tablets, etc. And there are all sorts of side effects that aren’t good from a health standpoint. Eye strain, eye fatigue, headaches. But also, in general, we don’t view these devices like we used to, just in a living room. We view them where the environment changes and the display really needs to be smart enough to adapt to the environment and the ambient light in which you’re viewing them.


When looking at the visual aspect of human-machine interaction, have you managed to come up with the metrics or assessment or evaluation techniques that give us that sense that the science is giving us the ability to see actual improvements in human-computer interaction?

Yes, absolutely. There are so many available metrics, but most of them are controlled quality metrics in control kind of conditions. For example, when you want to look at an image quality in a very controlled lighting condition.

The challenge with us evangelizing what we’re doing today, which is perceptual aspects of displays, is that there are not so many metrics. So when we introduce these kinds of products, we need to introduce a system for them as well. And that is what makes our life a bit harder.

[The research world is coming] up with different ways of bringing subjects and users as the main people who are supposed to rank a technology and feel comfortable with it. So we do a lot of subjective testing and provide that to our users as the metrics.


Can you give us a sense of the science disciplines that are mixed/merged together to form this system of knowledge that you have, as well as a sense of how to combine various sciences? What is your methodology to take various elements from different sciences and bring it into a composite knowledge base that is turned into a technology?

It’s not easy. I’ll name some of the scientific fields we need. We need physiologists, psychologists, image processing experts, computer vision, display quality, and digital signal processing.

Those are the fields and expertise that we need in-house. And the moment you get two or three very knowledgeable people in different fields, it’s easy to motivate the others because, in the research world, it’s also very much of interest to work with researchers from different fields that usually in academia you don’t get a chance to work with.


So, you’ve got the qualitative and quantitative in there. How does this science and technology combined lead to an improvement in interaction? How do we measure something that’s more subjective, such as determining whether this has created a better environment for the person or something that is more or less harmful?

It’s a challenge when it’s interdisciplinary, and it’s challenging to measure or have a metric for any interdisciplinary field.

When we’re talking about image processing, we can go back to the standard metrics, which are out there. But when we’re trying to combine these two, it becomes a bit complicated.

We try to collaborate with all the experts in this field and come up with new metrics. One of the things that we do to measure the perceiving of images is a lot of subjective tests. Psychologists or physiologists are studying the eye’s behavior in different lighting conditions. They used to run a lot of subjective tests.

We do pair-wise comparison. With 50, 60, 100 subjects, we ask them to compare a display running our technology against the display which is not running our technology to see which one is more visible. And from the results, we can come up with how effective it is.

But when it becomes something in the health domain, like less eye fatigue or healthier interaction for the user, it becomes more complicated. And there are two ways we can prove this. One is to rely on the 50, 60 years of research on interactions with different types of screens. And then by proving the fact that the IRYstec can increase the perceived quality of the image, we can kind of marry those skills together.


What are some takeaways for listeners or items they can act on?

Number one is, I think, looking for the industry to be addressing these issues. Seek out technologies like IRYstec and sort of demanding that they appear. Ultimately, it’s the consumer that really dictates to a large degree what the industry does, certainly in terms of mobile phones/smartphones, but even in cars.

Seek out displays that are healthier and better for you.

For the researchers or entrepreneurs who are listening to this, come up with technologies which are not only cool technologies, but things which are healthier and would help interactions with technologies for future generations.

*Responses are edited and adapted for written clarity. For full responses, please listen to the podcast episode here.