Blink-sensing glasses: A flexible iontronic sensing wearable for continuous blink monitoring

Abstract

Blink reflex has long been considered closely related to physiological states, from which abundant information on ocular health and activities can be revealed. In this study, a smart glasses wearable has been developed, incorporating a flexible and sensitive pressure sensor, to monitor blink patterns by continuously detecting ocular muscular movements, referred to as blink-sensing glasses. By applying the emerging flexible iontronic sensing (FITS) sensor with the sensitivity of 340 pF/mmHg, the skin pressure variations induced by movements of the orbicularis oculi muscles can be monitored in real time. The blink-sensing glasses can successfully capture blink patterns with a high accuracy of 96.3% and have been used to differentiate the blink features from both dry-eye subjects and healthy controls. This device can be potentially used as a new clinical and research monitoring tool for continuous eye blink analysis, while providing patients with high comfortableness in long-term ambulatory and home settings.

Keywords: Biodevices; Bioelectronics; Sensor.

Graphical abstract

Figure 1

Measurement principle (A) Anatomical structure of the eye muscles, with the orbicularis oculi muscle (highlighted in blue) (ii) and the levator superioris muscle (i) (highlighted in red), both of which control the blink movements. The red dot indicates the inner canthus angle (iii). (B) The section parallel to the nose pad. (iv) The sensor placement position and (v) the maxilla.

Figure 2

Iontronic sensing design Illustration of the FITS sensing structure (A) along with its equivalent circuit diagram shown in (B).

Figure 3

Characterization of the sensor performance Characterization of the sensitivities of the FITS sensor under various geometric parameters. (A) Device sensitivities versus the diameters of the sensing chamber (4 mm, 6 mm, 8 mm, and 10 mm). (B) Device sensitivities versus the heights of the sensing chamber (100 μm, 50 μm, and 30 μm). (C) Device sensitivities versus the sensing membrane thicknesses (100 μm, 75 μm, and 50 μm).

Figure 4

Optimization of the sensing location Validation of the sensing locations within the blue grids, from which the corresponding signal waveforms have been measured (Note: the red dot indicates the inner canthus angle of eye as the anatomical reference).

Figure 5

Blink-sensing glasses (A) The blink-sensing glasses system on a health volunteer, along with (B) the illustration of its hardware building blocks.

Figure 6

Blink-detection algorithm 1 (A) Flowchart of the blink-detection algorithm, and plots of (B) the original pressure waveform of S₀, which contains multiple blink activities with a 20-s window, (C) the pre-processed signals of S₂ following the morphological and Butterworth filters, with (D) the detected blink features, i.e., the peak, the start, and the endpoints, using the template matching method.

Figure 7

Blink-detection algorithm 2 (A) Eye aperture height change curve (red) and pressure change curve (blue) normalized at the same scale. (B) Correlation between the blink rate calculated by pressure signal and the blink rate calculated by video. (C) Bland Altman plot of blink rate that the blink-sensing glasses extract and that from the video. The horizontal and vertical axes are the mean and difference values of blink rates that the blink-sensing glasses measure and that from the video, respectively.

Figure 8

A demonstration of dry-eye analysis. Statistical chart of blink features including average blink rate, average maximum blink interval, and average blink duration, comparing between dye-eye patients and healthy subjects.