Our eyes are constantly switching between near, middle distance, and tasks at far to process the visual information around us – from digital devices to the natural environment and everything in between. So how are the visual needs of modern users of progressive lens design wearers met?
Our near vision requirements have changed dramatically over the past 20 years. Today, modern lifestyles result in people’s eyes moving 100,000 times a day to process all the visual information they are exposed to.1
An overwhelming quantity of information confronts the visual system during daily tasks, such as multitasking in motion and switching attention between concurrent visual and cognitive tasks and goals.
A recent quantitative study identified some of the main challenges faced by progressive additional lens (PAL) wearers:2
- Checking notifications all day long and quickly switching gaze from smartphone to the environment,
- Walking down the stairs and alternating their gaze between the stairs and smartphone, and
- Using two computer screens and switching gaze from the keyboard to the first screen and then the second screen.
Maintaining sharp vision while moving requires additional attention. PAL wearers must take a millisecond to adjust their focus on elusive targets, slow down or even stop moving to regain the sharpness in their vision.
We have the impression that we can efficiently manage this enormous volume of sensory data. However, it is an illusion. According to the bottleneck theory of attention, attention can be allocated to only one task or goal at a time (Figure 1).3
Thus, multitasking is a myth; instead, attention switches between tasks and targets. Stimuli arrive at a bottleneck where only one item can be processed at a time.3 But we don’t switch from a task to another instantaneously, there is a task switching delay. This is the time needed to move our attention from one task to another. The challenge is to make this delay as short as possible.
In a rich visual world, not only does the visual attention system have to filter what is relevant from what is not but also, in situations where several tasks are performed simultaneously, it must divide its resources over several goals and frequently switch from one task to another.
THE TASK SWITCHING DELAY
These very complex attention mechanisms require processing time and effort, and therefore, multitasking demands come with a performance cost. This is important when undertaking modern everyday multitasking situations, such as walking and messaging on a phone or driving while using a digital navigation system, which requires fast visual attention switches and where a loss in performance could have repercussions. The faster we can switch from one task to another with the shortest delay, the better and safer it is for us.
To undertake multiple tasks simultaneously, we must skilfully switch both our gaze and attention back and forth. To do this, we must be able to move our eyes quickly and efficiently between the various targets and objects supporting the different tasks. This is dependent on the specific structure of our retina and the execution of coordinated movements of our eyes.
Cone photoreceptors in the human eye are responsible for producing colour and fine details. They are not evenly distributed across the retina, with a sharp peak in density at the fovea, close to the centre of the retina (Figure 2). The fovea covers about 2° of visual angle. Only in this tiny part of the visual field can we achieve high acuity. We move our fovea to objects we want to process by making very precise, rapid eye movements, allowing our vision to function with high acuity despite our small fovea.
CONSIDERING VISUAL BEHAVIOUR IN LENS DESIGN
As the highest level of acuity is only available in 2° of the central visual field, we must shift our gaze at regular intervals. Typically, this occurs three or four times every second, bringing objects of interest onto the fovea and making them available for the attentional system to be processed.6 This succession of saccades and fixations builds the representation of the surrounding visual environment.5,6
In this highly complex environment, it is crucial to perform accurate ocular navigation and place our fovea as precisely and quickly as possible on all the relevant targets to ensure rapid reaction times. This is especially important when the observer is on the move.
To keep up with these dynamic vision needs, and high-speed processes, we need to offer people new solutions that are adapted to their lifestyles. For today’s presbyopes, progressive lenses need to allow efficient ocular navigation when going from one object to another and at the same time provide optimal binocular vision.
This is where the visual behaviour of the wearer becomes a key parameter to consider in the design of the lens. Visual behaviour defines the combinations of head and eye movements of a given wearer. Every individual’s visual behaviour is unique.
By modelling object positions in a 3D environment and placing a wearer with its specific visual behaviour in this environment, it is possible to define the exact object positions relative to each wearer’s head, according to their behaviour.
The key to creating a lens design that matches the wearer’s natural behaviour (head-gaze coordination) for each object they look at is to position the vision zones on the lens as precisely as possible.
VARIABILITY OF VISUAL BEHAVIOURS AMONG WEARERS
Figure 3. NVB pseudo-reading task.
The near vision behaviour (NVB) measurement aims to determine the parameters of the reader’s habitual near vision postural behaviour, despite the fact the wearer’s vision is not corrected during the measurement. It does so by recording their eyes and head movements while performing a pseudo-reading task (grid of dots that enables the reader to predict the landing position of their next saccade) (Figure 3).
More specifically, four distinct parameters are measured. Three are related to the wearer’s posture: angle of downgaze, lateral offset, and reading distance (Figure 4).
NVB enables the practitioner to tailor the position of near vision, on a progressive lens design, to the wearer’s behaviour during a near vision task and to optimise the shape of the near vision zone.
Thanks to NVB, the personalisation technology launched with Varilux X series, a lot of data has been collected about visual and postural behaviour. Analysis of more than 160,000 orders of Varilux X series lenses with NVB data shows the impact of the prescription (ametropia and addition) on the postural behaviour of wearers.
The analysis of means (ANOM) method7 is used to assess differences in wearer postural behaviour according to ametropia and addition. The ANOM technique was developed for comparing group means to see if any one of them differs significantly from the overall mean. Considering groups of wearers with different input parameters (ametropia, addition), the following charts (Figure 5) show that some have behaviours that are significantly different from the overall mean.
The chart displays each group mean (red point), the overall mean (green line), and the decision limits (orange lines). If a point falls outside the decision limits, then evidence exists that the group mean, represented by that point, is significantly different from the overall mean. The width of decision limits depends on the sample size.
A prescription has a multifactorial impact on postural behaviour, in particular on angle of downgaze and reading distance. In the given example, we can observe that:
- The angle of downgaze is lower for myopes than for hyperopes, and
- Reading distance decreases between addition 1.75 and 2.75.
LENS DESIGN SOLUTION
Statistical analysis has demonstrated that wearers with different input parameters have different visual behaviours. However, the relationship between these parameters is complex and non-linear. Deriving a model from this data is therefore not straightforward.
Artificial intelligence (AI) is, by definition, the capacity of computers to simulate intelligent behaviour. A specific branch of AI called machine learning relies on data to create ‘intelligent’ models. The parametric models are automatically tuned – through iterative adjustments – to match the given data. This approach has been applied to the wearer behavioural data to generate a predictive visual behaviour profile model.
The resulting model is a piece of software that takes, as input, a wearer’s order parameters (mainly ametropia and addition) and determines the wearer’s visual behaviour (downgaze and reading distance). This is known as behavioural artificial intelligence. The predicted values are used during lens optimisation to adjust the positioning of vision zones (intermediate and near).
Downgaze influences the vertical positioning of the vision zones. The greater the downgaze, the lower the vision zones are positioned. The goal is to design a lens that matches the wearer’s natural visual behaviour.
Reading distance influences the lateral positioning of the intermediate and near vision zones. The shorter the reading distance, the more the intermediate and near vision zones shift to the nasal side. The goal is to design a lens that matches the wearer’s natural convergence.
As a result, the position of the vision zones varies from one wearer to another. A key feature of this approach is that it does not require any specific measurement to provide individualised lenses. Behavioural artificial intelligence replaces the measurement.
This technology is applied as part of the Varilux XR series progressive lens. This lens is designed to answer modern wearer’s needs by providing individualised positioning of the intermediate and near vision zones.
Modern lifestyles, especially the use of digital devices at different viewing distances, places specific requirements on vision, particularly when the spectacle wearer is moving. Modern progressive lenses must provide highly accurate positioning of vision zones to facilitate the wearer’s ocular navigation.
Analysis of exclusive data has shown that the visual behaviour of wearers depends on their ametropia and addition. This knowledge is used to individualise the positioning of vision zones. Such an improvement in lens optimisation is made possible by using behavioural artificial intelligence to predict a wearer’s visual behaviour based on their visual characteristics.
Varilux XR Series in a Nutshell
Varilux XR series is the latest generation of the Varilux progressive addition lens. It combines key technologies:
Nanoptix technology absorbs peripheral distortion to offer stabilised vision and minimise swim.
XTend technology modulates variation in the addition to extend the volume of clear vision within arm’s reach.
The new XR-motion technology, based on behavioural artificial intelligence, optimises binocular vision on the two lenses to allow instant sharpness, even when moving.
Varilux, Varilux XR series, Nanoptix and Xtend are all registered trademarks of Essilor.
Disclosure: The authors are employed by Essilor.
Meena Kaur Puar BSc (Hons) MCOptom FBCLA FBDO is an optometrist and dispensing optician. In her current role, she works as a Medical Advisor at EssilorLuxottica with a focus in thepresbyopia category.
With more than 15 years’ experience in education and within the optical business, Meena has been developing education programs for eye care professionals and pharmacists.
Valérie Jolivet MSc is a data analyst at the Essilor Center of Innovation and Technology Europe. She holds a Master of Science degree in statistics. She worked for five years in the pharmaceutical industry as a bio-statistician before joining Essilor International in 1995. After working as Quality Engineer, she joined the Consumer Experience department in Research and Development from 2008 to 2019. She now works on topics related to presbyopia.
Sébastien Fricker MSc is the Design Manager at the Essilor Center of Innovation and Technology Europe. He graduated as a Physics Engineer from Ecole Polytechnique (Palaiseau, France) in 2000 and obtained a masters in electrical engineering from the University of Michigan (Ann Arbor, USA) in 2002. He worked for 10 years in research and development in the optical metrology industry. Sébastien joined Essilor in 2012, and works on ophthalmic lens design methods and lens performance modelling.
- Schiller, P.H., Tehovnik, E.J., Neural mechanisms underlying target selection with saccadic eye movements, Progress in Brain Research, Elsevier, Volume 149, 2005, p157–171.
- Essilor, Varilux XR series Consumer Expectations and Behaviors with Progressive Lenses – Third Independent Party – BR/FR/ IT/UK/US – Q1 2022 (n=4062) progressive lenses wearers.
- Broadbent, D., (1958). Perception and communication. London: Pergamon Press.
- Mustafi, D., Engel, A.H., Palczewski, K., Structure of cone photoreceptors. Progress in Retinal and Eye Research, 28, 289–302 (2009).
- Gegenfurtner, K.R. The interaction between vision and eye movements. Perception. 2016;45(12):1333–1357.
- Findlay, J. M., Gilchrist, I. D. Active Vision: The Psychology of Looking and Seeing. Oxford University Press. Online Ed. 2003.
- Nelson, L.S., (1983), Exact critical values for use with the analysis of means, Journal of Quality Technology, 15, 40–44.