Agreement in cerebrovascular reactivity assessed with diffuse correlation spectroscopy across experimental paradigms improves with short separation regression.

Significance: Cerebrovascular reactivity (CVR), i.e., the ability of cerebral vasculature to dilate or constrict in response to vasoactive stimuli, is a biomarker of vascular health. Exogenous administration of inhaled carbon dioxide, i.e., hypercapnia (HC), remains the "gold-standard" intervention to assess CVR. More tolerable paradigms that enable CVR quantification when HC is difficult/contraindicated have been proposed. However, because these paradigms feature mechanistic differences in action, an assessment of agreement of these more tolerable paradigms to HC is needed. Aim: We aim to determine the agreement of CVR assessed during HC, breath-hold (BH), and resting state (RS) paradigms. Approach: Healthy adults were subject to HC, BH, and RS paradigms. End tidal carbon dioxide (EtCO2) and cerebral blood flow (CBF, assessed with diffuse correlation spectroscopy) were monitored continuously. CVR (%/mmHg) was quantified via linear regression of CBF versus EtCO2 or via a general linear model (GLM) that was used to minimize the influence of systemic and extracerebral signal contributions. Results: Strong agreement ( CCC ≥ 0.69 ; R ≥ 0.76 ) among CVR paradigms was demonstrated when utilizing a GLM to regress out systemic/extracerebral signal contributions. Linear regression alone showed poor agreement across paradigms ( CCC ≤ 0.35 ; R ≤ 0.45 ). Conclusions: More tolerable experimental paradigms coupled with regression of systemic/extracerebral signal contributions may offer a viable alternative to HC for assessing CVR.

Artificial neural network-based estimation of the eyeball position using the magnetic contact lens sensing technique.

We have created an artificial neural network based approach for measuring eye movement using a magnetic contact lens sensing technique. The sensor array is based on using four magnetoresistive sensors. A two-layer feed-forward artificial neural network was used and an artificial eyeball model was made for the test. The neural network is trained with sample data obtained from nine spots. After training, we compared the position calculated from the developed system with the real one. The result shows that there is a good linear relationship between them. This indicates the developed system is capable of recording the position of the eyeball with a high degree of accuracy.

A wireless measurement system for three-dimensional ocular movement using the magnetic contact lens sensing technique.

A new and innovative method to measure the eye movement in a wireless manner was proposed. We verified the feasibility of our idea by fabrication and performance test of a prototype system. The prototype system consisted of a contact lens with a ring-shaped thin magnet, and eyeglasses frame-shaped PCB with analog/digital signal processing circuitry as well as four magnetoresistive sensors. This new method based on the magnetic contact lens sensing technique (MCLST) is expected to overcome all the disadvantages of the existing techniques.