Dataset Information

Development of an Eye Model With a Physiological Blink Mechanism.

ABSTRACT:

Purpose

To develop an eye model with a physiological blink mechanism.

Methods

All parts of the eye model were designed using computer-aided design software. The eyelid consisted of a unique 3D printed structure containing teeth to physically secure a flexible membrane. Both the eyeball and eyelid membrane were synthesized using polyvinyl alcohol (PVA). Four molecular weights of PVA (89-98, 85-124, 130, and 146-186 kDa) were tested at a range of concentrations between 5% and 30% weight/volume. The wettability and water content of these materials were compared with the bovine cornea and sclera. The model was connected to a microfluidic pump, which delivers artificial tear solution (ATS) to the eyelid. A corneal topographer was used to evaluate the tear break-up and tear film regeneration.

Results

The eyelid flexes and slides across the eyeball during each blink, which ensures direct contact between the two surfaces. When loaded with an ATS, this mechanism evenly spreads the solution over the eyeball to generate an artificial tear film. The artificial tear film in this eye model had a tear break-up time (TBUT) of 5.13 ± 0.09 seconds at 1.4 ?L/min flow rate, 6 blinks/min, and <25% humidity.

Conclusions

This model simulates a physiological blink actuation and an artificial tear film layer. Future studies will examine variations in flow rates and ATS composition to simulate clinical values of TBUT.

Translational relevance

The eye model could be used to study in vitro TBUT, tear deposition, and simple drug delivery.

SUBMITTER: Phan CM

PROVIDER: S-EPMC6727780 | biostudies-literature | 2019 Sep

REPOSITORIES: biostudies-literature

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Publications

Development of an Eye Model With a Physiological Blink Mechanism.

Phan Chau-Min CM Walther Hendri H Qiao Ha H Shinde Ra R Jones Lyndo L

Translational vision science & technology 20190903 5

<h4>Purpose</h4>To develop an eye model with a physiological blink mechanism.<h4>Methods</h4>All parts of the eye model were designed using computer-aided design software. The eyelid consisted of a unique 3D printed structure containing teeth to physically secure a flexible membrane. Both the eyeball and eyelid membrane were synthesized using polyvinyl alcohol (PVA). Four molecular weights of PVA (89-98, 85-124, 130, and 146-186 kDa) were tested at a range of concentrations between 5% and 30% we ...[more]

PMID: 31534830

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Project description:Study objectivesDrowsiness leads to 20% of fatal road crashes, while inability to assess drowsiness has hampered drowsiness interventions. This study examined the accuracy of eye-blink parameters for detecting drowsiness related driving impairment in real time.MethodsTwelve participants undertook two sessions of 2-hour track-driving in an instrumented vehicle following a normal night's sleep or 32 to 34 hours of extended wake in a randomized crossover design. Eye-blink parameters and lane excursion events were monitored continuously.ResultsSleep deprivation increased the rates of out-of-lane driving events and early drive terminations. Episodes of prolonged eyelid closures, blink duration, the ratio of amplitude to velocity of eyelid closure, and John's Drowsiness Score (JDS, a composite score) were also increased following sleep deprivation. A time-on-task (drive duration) effect was evident for out-of-lane events rate and most eye-blink parameters after sleep deprivation. The JDS demonstrated the strongest association with the odds of out-of-lane events in the same minute, whereas measures of blink duration and prolonged eye closure were stronger indicators of risk for out-of-lane events over longer periods of 5 minutes and 15 minutes, respectively. Eye-blink parameters also achieved moderate accuracies (specificities from 70.12% to 84.15% at a sensitivity of 50%) for detecting out-of-lane events in the same minute, with stronger associations over longer timeframes of 5 minutes to 15 minutes.ConclusionsEyelid closure parameters are useful tools for monitoring and predicting drowsiness-related driving impairment (out-of-lane events) that could be utilized for monitoring drowsiness and assessing the efficacy of drowsiness interventions.Clinical trial registrationThis study is registered with the Australian New Zealand Clinical Trial Registry (ANCTR), http://www.anzctr.org.au/TrialSearch.aspx ACTRN12612000102875.CitationShekari Soleimanloo S, Wilkinson VE, Cori JM,Westlake J, Stevens B, Downey LA, Shiferaw BA, Rajaratnam SMW, Howard ME. Eye-blink parameters detect on-road track-driving impairment following severe sleep deprivation. J Clin Sleep Med. 2019;15(9):1271-1284.

Dataset Information

Development of an Eye Model With a Physiological Blink Mechanism.

Purpose

Methods

Results

Conclusions

Translational relevance

Publications

Development of an Eye Model With a Physiological Blink Mechanism.

Similar Datasets

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