Abstract
This paper presents an energy-efficient design and evaluation of a novel portable device for the automatic correction of presbyopia in human eyes driven by the use of opto-electronic lenses and based on the dynamic pupil response of the subject. Due to the wearable nature of the proposed Dynamic Auto–Accommodation Glasses, in addition to the real-time requirement, an energy-efficient implementation is critical for the success of the device. In this work, the binocular pupil tracking of a subject, followed by the calculation of the eyes’ vergence, and the control of a pair of opto-electronic lenses are implemented and evaluated on several hardware platforms, including two mobile GPU/SoCs, a high-end FPGA, a low-cost FPGA, and a desktop GPU (as a reference point). The pupil tracking algorithm has been parallelized, applying different platform-specific optimizations for each case, to design a fast yet energy-efficient wearable. The hardware platforms have been evaluated to determine which one is the most appropriate for the presbyopia correction task. The experimental results show that the most energy-efficient platform is a mobile GPU (Samsung Exynos 8890) capable of processing frames at 0.016 Joules/frame, still allowing real-time processing (24 frames/sec).
Highlights
Nowadays, there are many devices fitting in the category of wearables that are designed to target many different purposes such as monitoring/analyzing body signals or sensing ambient data in real time to provide immediate feedback to the user
This paper proposes the energy-efficient design and evaluation of a novel wearable device for the automatic correction of presbyopia, which is the reduction of the accommodation range of the human eye that disables us to focus near objects
Presbyopia is the reduction of the accommodation range of the human eye as a result of aging that disallows the capacity to focus near objects
Summary
There are many devices fitting in the category of wearables that are designed to target many different purposes such as monitoring/analyzing body signals or sensing ambient data in real time to provide immediate feedback to the user (e.g., heart rate monitoring, diabetes control, etc). This paper proposes the energy-efficient design and evaluation of a novel wearable device for the automatic correction of presbyopia, which is the reduction of the accommodation range of the human eye that disables us to focus near objects. This is accomplished by using a pair of opto-electronic lenses which are driven by the dynamic pupil response of the subject’s eyes (the subject is the person wearing the glasses). Presbyopia is the reduction of the accommodation range of the human eye as a result of aging that disallows the capacity to focus near objects. Another study by Heys et al [12] described a massive increase in the stiffness of the nucleus of the eye’s lens, which might be an important factor in presbyopia
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