  Infrared light scattering methods have been developed and employed to
non-invasively monitor human cerebral blood flow (CBF). However, the number of
reflected photons that interact with the brain is low when detecting blood flow
in deep tissue. To tackle this photon-starved problem, we present and
demonstrate the idea of interferometric speckle visibility spectroscopy (ISVS).
In ISVS, an interferometric detection scheme is used to boost the weak signal
light. The blood flow dynamics are inferred from the speckle statistics of a
single frame speckle pattern. We experimentally demonstrated the improvement of
measurement fidelity by introducing interferometric detection when the signal
photon number is insufficient. We apply the ISVS system to monitor the human
CBF in situations where the light intensity is $\sim$100-fold less than that in
common diffuse correlation spectroscopy (DCS) implementations. Due to the large
number of pixels ($\sim 2\times 10^5$) used to capture light in the ISVS
system, we are able to collect a similar number of photons within one exposure
time as in normal DCS implementations. Our system operates at a sampling rate
of 100 Hz. At the exposure time of 2 ms, the average signal photon electron
number is $\sim$0.95 count/pixel, yielding a single pixel interferometric
measurement signal-to-noise ratio (SNR) of $\sim$0.97. The total $\sim 2\times
10^5$ pixels provide an expected overall SNR of 436. We successfully
demonstrate that the ISVS system is able to monitor the human brain pulsatile
blood flow, as well as the blood flow change when a human subject is doing a
breath holding task.
