Abstract

Speckle contrast optical spectroscopy (SCOS) measures absolute blood flow in deep tissue, by taking advantage of multi-distance (previously reported in the literature) or multi-exposure (reported here) approach. This method promises to use inexpensive detectors to obtain good signal-to-noise ratio, but it has not yet been implemented in a suitable manner for a mass production. Here we present a new, compact, low power consumption, 32 by 2 single photon avalanche diode (SPAD) array that has no readout noise, low dead time and has high sensitivity in low light conditions, such as in vivo measurements. To demonstrate the capability to measure blood flow in deep tissue, healthy volunteers were measured, showing no significant differences from the diffuse correlation spectroscopy. In the future, this array can be miniaturized to a low-cost, robust, battery operated wireless device paving the way for measuring blood flow in a wide-range of applications from sport injury recovery and training to, on-field concussion detection to wearables.

© 2017 Optical Society of America under the terms of the OSA Open Access Publishing Agreement

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  1. A. Zauner and J. P. Muizelaar, “Brain metabolism and cerebral blood flow,” Head Inj. 199789–99 (1997).
  2. A. Devor, S. Sakadžić, V. J. Srinivasan, M. A. Yaseen, K. Nizar, P. A. Saisan, P. Tian, A. M. Dale, S. A. Vinogradov, M. A. Franceschini, and et al., “Frontiers in optical imaging of cerebral blood flow and metabolism,” J. Cereb. Blood Flow Metab. 32, 1259–1276 (2012).
    [Crossref] [PubMed]
  3. T. Durduran, R. Choe, W. Baker, and A. G. Yodh, “Diffuse optics for tissue monitoring and tomography,” Rep. Prog. Phys. 73, 076701 (2010).
    [Crossref] [PubMed]
  4. V. Rajan, B. Varghese, T. G. van Leeuwen, and W. Steenbergen, “Review of methodological developments in laser doppler flowmetry,” Lasers Med. Sci. 24, 269–283 (2009).
    [Crossref]
  5. D. A. Boas and A. K. Dunn, “Laser speckle contrast imaging in biomedical optics,” J. Biomed. Opt. 15, 011109 (2010).
    [Crossref] [PubMed]
  6. J. D. Briers, “Laser doppler, speckle and related techniques for blood perfusion mapping and imaging,” Physiol. Meas. 22, R35 (2001).
    [Crossref]
  7. A. K. Dunn, H. Bolay, M. A. Moskowitz, and D. A. Boas, “Dynamic imaging of cerebral blood flow using laser speckle,” J. Cereb. Blood Flow Metab. 21, 195–201 (2001).
    [Crossref] [PubMed]
  8. A. K. Dunn, “Laser speckle contrast imaging of cerebral blood flow,” Ann. Biomed. Eng. 40, 367–377 (2012).
    [Crossref]
  9. A. B. Parthasarathy, S. Shams Kazmi, and A. K. Dunn, “Quantitative imaging of ischemic stroke through thinned skull in mice with multi exposure speckle imaging,” Biomed. Opt. Express 1, 246–259 (2010).
    [Crossref]
  10. S. M. S. Kazmi, A. B. Parthasarthy, N. E. Song, T. A. Jones, and A. K. Dunn, “Chronic imaging of cortical blood flow using multi-exposure speckle imaging,” J. Cereb. Blood Flow Metab. 33, 798–808 (2013).
    [Crossref] [PubMed]
  11. T. Dragojević, D. Bronzi, H. M. Varma, C. P. Valdes, C. Castellvi, F. Villa, A. Tosi, C. Justicia, F. Zappa, and T. Durduran, “High-speed multi-exposure laser speckle contrast imaging with a single-photon counting camera,” Biomed. Opt. Express 6, 2865–2876 (2015).
    [Crossref]
  12. S. Sun, B. R. Hayes-Gill, D. He, Y. Zhu, and S. P. Morgan, “Multi-exposure laser speckle contrast imaging using a high frame rate cmos sensor with a field programmable gate array,” Opt. Lett. 40, 4587–4590 (2015).
    [Crossref] [PubMed]
  13. D. A. Boas, L. Campbell, and A. G. Yodh, “Scattering and imaging with diffusing temporal field correlations,” Phys. Rev. Lett. 75, 1855 (1995).
    [Crossref] [PubMed]
  14. D. A. Boas, “Diffuse photon probes of structural and dynamical properties of turbid media: theory and biomedical applications,” Ph.D. thesis, Citeseer (1996).
  15. G. Dietsche, M. Ninck, C. Ortolf, J. Li, F. Jaillon, and T. Gisler, “Fiber-based multispeckle detection for time-resolved diffusing-wave spectroscopy: characterization and application to blood flow detection in deep tissue,” Appl. Opt. 46, 8506–8514 (2007).
    [Crossref] [PubMed]
  16. C. P. Valdes, H. M. Varma, A. K. Kristoffersen, T. Dragojević, J. P. Culver, and T. Durduran, “Speckle contrast optical spectroscopy, a non-invasive, diffuse optical method for measuring microvascular blood flow in tissue,” Biomed. Opt. Express 5, 2769–2784 (2014).
    [Crossref] [PubMed]
  17. R. Bi, J. Dong, and K. Lee, “Multi-channel deep tissue flowmetry based on temporal diffuse speckle contrast analysis,” Opt. Express 21, 22854–22861 (2013).
    [Crossref] [PubMed]
  18. R. Bi, J. Dong, and K. Lee, “Deep tissue flowmetry based on diffuse speckle contrast analysis,” Opt. Lett. 38, 1401–1403 (2013).
    [Crossref] [PubMed]
  19. V. Quaresima and M. Ferrari, “Functional near-infrared spectroscopy (fnirs) for assessing cerebral cortex function during human behavior in natural/social situations: A concise review,” Organ. Res. Meth. 201610944 (2016).
    [Crossref]
  20. H. Atsumori, M. Kiguchi, A. Obata, H. Sato, T. Katura, T. Funane, and A. Maki, “Development of wearable optical topography system for mapping the prefrontal cortex activation,” Rev. Sci. Instrum. 80, 043704 (2009).
    [Crossref] [PubMed]
  21. S. K. Piper, A. Krueger, S. P. Koch, J. Mehnert, C. Habermehl, J. Steinbrink, H. Obrig, and C. H. Schmitz, “A wearable multi-channel fnirs system for brain imaging in freely moving subjects,” Neuroimage 85, 64–71 (2014).
    [Crossref]
  22. P. Pinti, C. Aichelburg, F. Lind, S. Power, E. Swingler, A. Merla, A. Hamilton, S. Gilbert, P. Burgess, and I. Tachtsidis, “Using fiberless, wearable fnirs to monitor brain activity in real-world cognitive tasks,” J. Vis. Exp. (2015).
    [Crossref] [PubMed]
  23. N. Takeuchi, T. Mori, Y. Suzukamo, N. Tanaka, and S.-I. Izumi, “Parallel processing of cognitive and physical demands in left and right prefrontal cortices during smartphone use while walking,” BMC Neurosci. 17, 9 (2016).
    [Crossref] [PubMed]
  24. D. Boas and M. Franceschini, “Haemoglobin oxygen saturation as a biomarker: the problem and a solution,” Philos. Trans. Royal Soc. As. 3694407–4424 (2011).
    [Crossref]
  25. D. Tamborini, M. Buttafava, A. Ruggeri, and F. Zappa, “Compact, low-power and fully reconfigurable 10 ps resolution, 160 range, time-resolved single-photon counting system,” IEEE Sens. J. 16, 3827–3833 (2016).
    [Crossref]
  26. D. Bronzi, S. Tisa, F. Villa, S. Bellisai, A. Tosi, and F. Zappa, “Fast sensing and quenching of cmos spads for minimal afterpulsing effects,” IEEE Photon. Technol. Lett. 25, 776–779 (2013).
    [Crossref]
  27. C. Scarcella, A. Tosi, F. Villa, S. Tisa, and F. Zappa, “Low-noise low-jitter 32-pixels cmos single-photon avalanche diodes array for single-photon counting from 300 nm to 900 nm,” Rev. Sci. Instrum. 84, 123112 (2013).
    [Crossref]
  28. R. Bandyopadhyay, A. Gittings, S. Suh, P. Dixon, and D. Durian, “Speckle-visibility spectroscopy: A tool to study time-varying dynamics,” Rev. Sci. Instrum. 76, 093110 (2005).
    [Crossref]
  29. D. A. Boas, S. Sakadžić, J. Selb, P. Farzam, M. A. Franceschini, and S. A. Carp, “Establishing the diffuse correlation spectroscopy signal relationship with blood flow,” Neurophotonics 3, 031412 (2016).
    [Crossref] [PubMed]
  30. H. W. Duchna, C. Guilleminault, R. A. Stoohs, J. L. Faul, H. Moreno, B. B. Hoffman, and T. F. Blaschke, “Vascular reactivity in obstructive sleep apnea syndrome,” Am. J. Respir. Crit. Care Med. 161, 187–191 (2000).
    [Crossref] [PubMed]
  31. A. H. van Beek, H. M. de Wit, O. Rikkert, G. Marcel, and J. A. Claassen, “Incorrect performance of the breath hold method in the old underestimates cerebrovascular reactivity and goes unnoticed without concomitant blood pressure and end-tidal co2 registration,” J. Neuroimaging 21, 340–347 (2011).
    [Crossref] [PubMed]
  32. D. Giavarina, “Understanding bland altman analysis,” Biochem. Med. 25, 141–151 (2015).
    [Crossref]
  33. G. Yu, T. Durduran, G. Lech, C. Zhou, B. Chance, E. R. Mohler, and A. G. Yodh, “Time-dependent blood flow and oxygenation in human skeletal muscles measured with noninvasive near-infrared diffuse optical spectroscopies,” J. Biomed. Opt. 10, 024027 (2005).
    [Crossref] [PubMed]
  34. Z. B. Rodgers, S. E. Leinwand, B. T. Keenan, L. G. Kini, R. J. Schwab, and F. W. Wehrli, “Cerebral metabolic rate of oxygen in obstructive sleep apnea at rest and in response to breath-hold challenge,” J. Cereb. Blood Flow Metab. 36, 755–767 (2016).
    [Crossref]
  35. Z. B. Rodgers, V. Jain, E. K. Englund, M. C. Langham, and F. W. Wehrli, “High temporal resolution mri quantification of global cerebral metabolic rate of oxygen consumption in response to apneic challenge,” J. Cereb. Blood Flow Metab. 33, 1514–1522 (2013).
    [Crossref] [PubMed]
  36. M. Kameyama, M. Fukuda, T. Uehara, and M. Mikuni, “Sex and age dependencies of cerebral blood volume changes during cognitive activation: a multichannel near-infrared spectroscopy study,” Neuroimage 22, 1715–1721 (2004).
    [Crossref] [PubMed]
  37. B. Walsh, F. Tian, J. Tourville, M. Yücel, T. Kuczek, and A. Bostian, “Hemodynamics of speech production: An fnirs investigation of children who stutter,” Sci. Rep. 74034 (2017).
    [Crossref]
  38. D. Bronzi, F. Villa, S. Tisa, A. Tosi, F. Zappa, D. Durini, S. Weyers, and W. Brockherde, “100 000 frames/s 64 × 32 single-photon detector array for 2-d imaging and 3-d ranging,” IEEE J. Sel. Top. Quantum Electron. 20, 354–363 (2014).
    [Crossref]

2017 (1)

B. Walsh, F. Tian, J. Tourville, M. Yücel, T. Kuczek, and A. Bostian, “Hemodynamics of speech production: An fnirs investigation of children who stutter,” Sci. Rep. 74034 (2017).
[Crossref]

2016 (5)

V. Quaresima and M. Ferrari, “Functional near-infrared spectroscopy (fnirs) for assessing cerebral cortex function during human behavior in natural/social situations: A concise review,” Organ. Res. Meth. 201610944 (2016).
[Crossref]

N. Takeuchi, T. Mori, Y. Suzukamo, N. Tanaka, and S.-I. Izumi, “Parallel processing of cognitive and physical demands in left and right prefrontal cortices during smartphone use while walking,” BMC Neurosci. 17, 9 (2016).
[Crossref] [PubMed]

D. Tamborini, M. Buttafava, A. Ruggeri, and F. Zappa, “Compact, low-power and fully reconfigurable 10 ps resolution, 160 range, time-resolved single-photon counting system,” IEEE Sens. J. 16, 3827–3833 (2016).
[Crossref]

D. A. Boas, S. Sakadžić, J. Selb, P. Farzam, M. A. Franceschini, and S. A. Carp, “Establishing the diffuse correlation spectroscopy signal relationship with blood flow,” Neurophotonics 3, 031412 (2016).
[Crossref] [PubMed]

Z. B. Rodgers, S. E. Leinwand, B. T. Keenan, L. G. Kini, R. J. Schwab, and F. W. Wehrli, “Cerebral metabolic rate of oxygen in obstructive sleep apnea at rest and in response to breath-hold challenge,” J. Cereb. Blood Flow Metab. 36, 755–767 (2016).
[Crossref]

2015 (3)

2014 (3)

C. P. Valdes, H. M. Varma, A. K. Kristoffersen, T. Dragojević, J. P. Culver, and T. Durduran, “Speckle contrast optical spectroscopy, a non-invasive, diffuse optical method for measuring microvascular blood flow in tissue,” Biomed. Opt. Express 5, 2769–2784 (2014).
[Crossref] [PubMed]

D. Bronzi, F. Villa, S. Tisa, A. Tosi, F. Zappa, D. Durini, S. Weyers, and W. Brockherde, “100 000 frames/s 64 × 32 single-photon detector array for 2-d imaging and 3-d ranging,” IEEE J. Sel. Top. Quantum Electron. 20, 354–363 (2014).
[Crossref]

S. K. Piper, A. Krueger, S. P. Koch, J. Mehnert, C. Habermehl, J. Steinbrink, H. Obrig, and C. H. Schmitz, “A wearable multi-channel fnirs system for brain imaging in freely moving subjects,” Neuroimage 85, 64–71 (2014).
[Crossref]

2013 (6)

Z. B. Rodgers, V. Jain, E. K. Englund, M. C. Langham, and F. W. Wehrli, “High temporal resolution mri quantification of global cerebral metabolic rate of oxygen consumption in response to apneic challenge,” J. Cereb. Blood Flow Metab. 33, 1514–1522 (2013).
[Crossref] [PubMed]

D. Bronzi, S. Tisa, F. Villa, S. Bellisai, A. Tosi, and F. Zappa, “Fast sensing and quenching of cmos spads for minimal afterpulsing effects,” IEEE Photon. Technol. Lett. 25, 776–779 (2013).
[Crossref]

C. Scarcella, A. Tosi, F. Villa, S. Tisa, and F. Zappa, “Low-noise low-jitter 32-pixels cmos single-photon avalanche diodes array for single-photon counting from 300 nm to 900 nm,” Rev. Sci. Instrum. 84, 123112 (2013).
[Crossref]

S. M. S. Kazmi, A. B. Parthasarthy, N. E. Song, T. A. Jones, and A. K. Dunn, “Chronic imaging of cortical blood flow using multi-exposure speckle imaging,” J. Cereb. Blood Flow Metab. 33, 798–808 (2013).
[Crossref] [PubMed]

R. Bi, J. Dong, and K. Lee, “Deep tissue flowmetry based on diffuse speckle contrast analysis,” Opt. Lett. 38, 1401–1403 (2013).
[Crossref] [PubMed]

R. Bi, J. Dong, and K. Lee, “Multi-channel deep tissue flowmetry based on temporal diffuse speckle contrast analysis,” Opt. Express 21, 22854–22861 (2013).
[Crossref] [PubMed]

2012 (2)

A. K. Dunn, “Laser speckle contrast imaging of cerebral blood flow,” Ann. Biomed. Eng. 40, 367–377 (2012).
[Crossref]

A. Devor, S. Sakadžić, V. J. Srinivasan, M. A. Yaseen, K. Nizar, P. A. Saisan, P. Tian, A. M. Dale, S. A. Vinogradov, M. A. Franceschini, and et al., “Frontiers in optical imaging of cerebral blood flow and metabolism,” J. Cereb. Blood Flow Metab. 32, 1259–1276 (2012).
[Crossref] [PubMed]

2011 (2)

D. Boas and M. Franceschini, “Haemoglobin oxygen saturation as a biomarker: the problem and a solution,” Philos. Trans. Royal Soc. As. 3694407–4424 (2011).
[Crossref]

A. H. van Beek, H. M. de Wit, O. Rikkert, G. Marcel, and J. A. Claassen, “Incorrect performance of the breath hold method in the old underestimates cerebrovascular reactivity and goes unnoticed without concomitant blood pressure and end-tidal co2 registration,” J. Neuroimaging 21, 340–347 (2011).
[Crossref] [PubMed]

2010 (3)

T. Durduran, R. Choe, W. Baker, and A. G. Yodh, “Diffuse optics for tissue monitoring and tomography,” Rep. Prog. Phys. 73, 076701 (2010).
[Crossref] [PubMed]

D. A. Boas and A. K. Dunn, “Laser speckle contrast imaging in biomedical optics,” J. Biomed. Opt. 15, 011109 (2010).
[Crossref] [PubMed]

A. B. Parthasarathy, S. Shams Kazmi, and A. K. Dunn, “Quantitative imaging of ischemic stroke through thinned skull in mice with multi exposure speckle imaging,” Biomed. Opt. Express 1, 246–259 (2010).
[Crossref]

2009 (2)

V. Rajan, B. Varghese, T. G. van Leeuwen, and W. Steenbergen, “Review of methodological developments in laser doppler flowmetry,” Lasers Med. Sci. 24, 269–283 (2009).
[Crossref]

H. Atsumori, M. Kiguchi, A. Obata, H. Sato, T. Katura, T. Funane, and A. Maki, “Development of wearable optical topography system for mapping the prefrontal cortex activation,” Rev. Sci. Instrum. 80, 043704 (2009).
[Crossref] [PubMed]

2007 (1)

2005 (2)

R. Bandyopadhyay, A. Gittings, S. Suh, P. Dixon, and D. Durian, “Speckle-visibility spectroscopy: A tool to study time-varying dynamics,” Rev. Sci. Instrum. 76, 093110 (2005).
[Crossref]

G. Yu, T. Durduran, G. Lech, C. Zhou, B. Chance, E. R. Mohler, and A. G. Yodh, “Time-dependent blood flow and oxygenation in human skeletal muscles measured with noninvasive near-infrared diffuse optical spectroscopies,” J. Biomed. Opt. 10, 024027 (2005).
[Crossref] [PubMed]

2004 (1)

M. Kameyama, M. Fukuda, T. Uehara, and M. Mikuni, “Sex and age dependencies of cerebral blood volume changes during cognitive activation: a multichannel near-infrared spectroscopy study,” Neuroimage 22, 1715–1721 (2004).
[Crossref] [PubMed]

2001 (2)

J. D. Briers, “Laser doppler, speckle and related techniques for blood perfusion mapping and imaging,” Physiol. Meas. 22, R35 (2001).
[Crossref]

A. K. Dunn, H. Bolay, M. A. Moskowitz, and D. A. Boas, “Dynamic imaging of cerebral blood flow using laser speckle,” J. Cereb. Blood Flow Metab. 21, 195–201 (2001).
[Crossref] [PubMed]

2000 (1)

H. W. Duchna, C. Guilleminault, R. A. Stoohs, J. L. Faul, H. Moreno, B. B. Hoffman, and T. F. Blaschke, “Vascular reactivity in obstructive sleep apnea syndrome,” Am. J. Respir. Crit. Care Med. 161, 187–191 (2000).
[Crossref] [PubMed]

1997 (1)

A. Zauner and J. P. Muizelaar, “Brain metabolism and cerebral blood flow,” Head Inj. 199789–99 (1997).

1995 (1)

D. A. Boas, L. Campbell, and A. G. Yodh, “Scattering and imaging with diffusing temporal field correlations,” Phys. Rev. Lett. 75, 1855 (1995).
[Crossref] [PubMed]

Aichelburg, C.

P. Pinti, C. Aichelburg, F. Lind, S. Power, E. Swingler, A. Merla, A. Hamilton, S. Gilbert, P. Burgess, and I. Tachtsidis, “Using fiberless, wearable fnirs to monitor brain activity in real-world cognitive tasks,” J. Vis. Exp. (2015).
[Crossref] [PubMed]

Atsumori, H.

H. Atsumori, M. Kiguchi, A. Obata, H. Sato, T. Katura, T. Funane, and A. Maki, “Development of wearable optical topography system for mapping the prefrontal cortex activation,” Rev. Sci. Instrum. 80, 043704 (2009).
[Crossref] [PubMed]

Baker, W.

T. Durduran, R. Choe, W. Baker, and A. G. Yodh, “Diffuse optics for tissue monitoring and tomography,” Rep. Prog. Phys. 73, 076701 (2010).
[Crossref] [PubMed]

Bandyopadhyay, R.

R. Bandyopadhyay, A. Gittings, S. Suh, P. Dixon, and D. Durian, “Speckle-visibility spectroscopy: A tool to study time-varying dynamics,” Rev. Sci. Instrum. 76, 093110 (2005).
[Crossref]

Bellisai, S.

D. Bronzi, S. Tisa, F. Villa, S. Bellisai, A. Tosi, and F. Zappa, “Fast sensing and quenching of cmos spads for minimal afterpulsing effects,” IEEE Photon. Technol. Lett. 25, 776–779 (2013).
[Crossref]

Bi, R.

Blaschke, T. F.

H. W. Duchna, C. Guilleminault, R. A. Stoohs, J. L. Faul, H. Moreno, B. B. Hoffman, and T. F. Blaschke, “Vascular reactivity in obstructive sleep apnea syndrome,” Am. J. Respir. Crit. Care Med. 161, 187–191 (2000).
[Crossref] [PubMed]

Boas, D.

D. Boas and M. Franceschini, “Haemoglobin oxygen saturation as a biomarker: the problem and a solution,” Philos. Trans. Royal Soc. As. 3694407–4424 (2011).
[Crossref]

Boas, D. A.

D. A. Boas, S. Sakadžić, J. Selb, P. Farzam, M. A. Franceschini, and S. A. Carp, “Establishing the diffuse correlation spectroscopy signal relationship with blood flow,” Neurophotonics 3, 031412 (2016).
[Crossref] [PubMed]

D. A. Boas and A. K. Dunn, “Laser speckle contrast imaging in biomedical optics,” J. Biomed. Opt. 15, 011109 (2010).
[Crossref] [PubMed]

A. K. Dunn, H. Bolay, M. A. Moskowitz, and D. A. Boas, “Dynamic imaging of cerebral blood flow using laser speckle,” J. Cereb. Blood Flow Metab. 21, 195–201 (2001).
[Crossref] [PubMed]

D. A. Boas, L. Campbell, and A. G. Yodh, “Scattering and imaging with diffusing temporal field correlations,” Phys. Rev. Lett. 75, 1855 (1995).
[Crossref] [PubMed]

D. A. Boas, “Diffuse photon probes of structural and dynamical properties of turbid media: theory and biomedical applications,” Ph.D. thesis, Citeseer (1996).

Bolay, H.

A. K. Dunn, H. Bolay, M. A. Moskowitz, and D. A. Boas, “Dynamic imaging of cerebral blood flow using laser speckle,” J. Cereb. Blood Flow Metab. 21, 195–201 (2001).
[Crossref] [PubMed]

Bostian, A.

B. Walsh, F. Tian, J. Tourville, M. Yücel, T. Kuczek, and A. Bostian, “Hemodynamics of speech production: An fnirs investigation of children who stutter,” Sci. Rep. 74034 (2017).
[Crossref]

Briers, J. D.

J. D. Briers, “Laser doppler, speckle and related techniques for blood perfusion mapping and imaging,” Physiol. Meas. 22, R35 (2001).
[Crossref]

Brockherde, W.

D. Bronzi, F. Villa, S. Tisa, A. Tosi, F. Zappa, D. Durini, S. Weyers, and W. Brockherde, “100 000 frames/s 64 × 32 single-photon detector array for 2-d imaging and 3-d ranging,” IEEE J. Sel. Top. Quantum Electron. 20, 354–363 (2014).
[Crossref]

Bronzi, D.

T. Dragojević, D. Bronzi, H. M. Varma, C. P. Valdes, C. Castellvi, F. Villa, A. Tosi, C. Justicia, F. Zappa, and T. Durduran, “High-speed multi-exposure laser speckle contrast imaging with a single-photon counting camera,” Biomed. Opt. Express 6, 2865–2876 (2015).
[Crossref]

D. Bronzi, F. Villa, S. Tisa, A. Tosi, F. Zappa, D. Durini, S. Weyers, and W. Brockherde, “100 000 frames/s 64 × 32 single-photon detector array for 2-d imaging and 3-d ranging,” IEEE J. Sel. Top. Quantum Electron. 20, 354–363 (2014).
[Crossref]

D. Bronzi, S. Tisa, F. Villa, S. Bellisai, A. Tosi, and F. Zappa, “Fast sensing and quenching of cmos spads for minimal afterpulsing effects,” IEEE Photon. Technol. Lett. 25, 776–779 (2013).
[Crossref]

Burgess, P.

P. Pinti, C. Aichelburg, F. Lind, S. Power, E. Swingler, A. Merla, A. Hamilton, S. Gilbert, P. Burgess, and I. Tachtsidis, “Using fiberless, wearable fnirs to monitor brain activity in real-world cognitive tasks,” J. Vis. Exp. (2015).
[Crossref] [PubMed]

Buttafava, M.

D. Tamborini, M. Buttafava, A. Ruggeri, and F. Zappa, “Compact, low-power and fully reconfigurable 10 ps resolution, 160 range, time-resolved single-photon counting system,” IEEE Sens. J. 16, 3827–3833 (2016).
[Crossref]

Campbell, L.

D. A. Boas, L. Campbell, and A. G. Yodh, “Scattering and imaging with diffusing temporal field correlations,” Phys. Rev. Lett. 75, 1855 (1995).
[Crossref] [PubMed]

Carp, S. A.

D. A. Boas, S. Sakadžić, J. Selb, P. Farzam, M. A. Franceschini, and S. A. Carp, “Establishing the diffuse correlation spectroscopy signal relationship with blood flow,” Neurophotonics 3, 031412 (2016).
[Crossref] [PubMed]

Castellvi, C.

Chance, B.

G. Yu, T. Durduran, G. Lech, C. Zhou, B. Chance, E. R. Mohler, and A. G. Yodh, “Time-dependent blood flow and oxygenation in human skeletal muscles measured with noninvasive near-infrared diffuse optical spectroscopies,” J. Biomed. Opt. 10, 024027 (2005).
[Crossref] [PubMed]

Choe, R.

T. Durduran, R. Choe, W. Baker, and A. G. Yodh, “Diffuse optics for tissue monitoring and tomography,” Rep. Prog. Phys. 73, 076701 (2010).
[Crossref] [PubMed]

Claassen, J. A.

A. H. van Beek, H. M. de Wit, O. Rikkert, G. Marcel, and J. A. Claassen, “Incorrect performance of the breath hold method in the old underestimates cerebrovascular reactivity and goes unnoticed without concomitant blood pressure and end-tidal co2 registration,” J. Neuroimaging 21, 340–347 (2011).
[Crossref] [PubMed]

Culver, J. P.

Dale, A. M.

A. Devor, S. Sakadžić, V. J. Srinivasan, M. A. Yaseen, K. Nizar, P. A. Saisan, P. Tian, A. M. Dale, S. A. Vinogradov, M. A. Franceschini, and et al., “Frontiers in optical imaging of cerebral blood flow and metabolism,” J. Cereb. Blood Flow Metab. 32, 1259–1276 (2012).
[Crossref] [PubMed]

de Wit, H. M.

A. H. van Beek, H. M. de Wit, O. Rikkert, G. Marcel, and J. A. Claassen, “Incorrect performance of the breath hold method in the old underestimates cerebrovascular reactivity and goes unnoticed without concomitant blood pressure and end-tidal co2 registration,” J. Neuroimaging 21, 340–347 (2011).
[Crossref] [PubMed]

Devor, A.

A. Devor, S. Sakadžić, V. J. Srinivasan, M. A. Yaseen, K. Nizar, P. A. Saisan, P. Tian, A. M. Dale, S. A. Vinogradov, M. A. Franceschini, and et al., “Frontiers in optical imaging of cerebral blood flow and metabolism,” J. Cereb. Blood Flow Metab. 32, 1259–1276 (2012).
[Crossref] [PubMed]

Dietsche, G.

Dixon, P.

R. Bandyopadhyay, A. Gittings, S. Suh, P. Dixon, and D. Durian, “Speckle-visibility spectroscopy: A tool to study time-varying dynamics,” Rev. Sci. Instrum. 76, 093110 (2005).
[Crossref]

Dong, J.

Dragojevic, T.

Duchna, H. W.

H. W. Duchna, C. Guilleminault, R. A. Stoohs, J. L. Faul, H. Moreno, B. B. Hoffman, and T. F. Blaschke, “Vascular reactivity in obstructive sleep apnea syndrome,” Am. J. Respir. Crit. Care Med. 161, 187–191 (2000).
[Crossref] [PubMed]

Dunn, A. K.

S. M. S. Kazmi, A. B. Parthasarthy, N. E. Song, T. A. Jones, and A. K. Dunn, “Chronic imaging of cortical blood flow using multi-exposure speckle imaging,” J. Cereb. Blood Flow Metab. 33, 798–808 (2013).
[Crossref] [PubMed]

A. K. Dunn, “Laser speckle contrast imaging of cerebral blood flow,” Ann. Biomed. Eng. 40, 367–377 (2012).
[Crossref]

D. A. Boas and A. K. Dunn, “Laser speckle contrast imaging in biomedical optics,” J. Biomed. Opt. 15, 011109 (2010).
[Crossref] [PubMed]

A. B. Parthasarathy, S. Shams Kazmi, and A. K. Dunn, “Quantitative imaging of ischemic stroke through thinned skull in mice with multi exposure speckle imaging,” Biomed. Opt. Express 1, 246–259 (2010).
[Crossref]

A. K. Dunn, H. Bolay, M. A. Moskowitz, and D. A. Boas, “Dynamic imaging of cerebral blood flow using laser speckle,” J. Cereb. Blood Flow Metab. 21, 195–201 (2001).
[Crossref] [PubMed]

Durduran, T.

Durian, D.

R. Bandyopadhyay, A. Gittings, S. Suh, P. Dixon, and D. Durian, “Speckle-visibility spectroscopy: A tool to study time-varying dynamics,” Rev. Sci. Instrum. 76, 093110 (2005).
[Crossref]

Durini, D.

D. Bronzi, F. Villa, S. Tisa, A. Tosi, F. Zappa, D. Durini, S. Weyers, and W. Brockherde, “100 000 frames/s 64 × 32 single-photon detector array for 2-d imaging and 3-d ranging,” IEEE J. Sel. Top. Quantum Electron. 20, 354–363 (2014).
[Crossref]

Englund, E. K.

Z. B. Rodgers, V. Jain, E. K. Englund, M. C. Langham, and F. W. Wehrli, “High temporal resolution mri quantification of global cerebral metabolic rate of oxygen consumption in response to apneic challenge,” J. Cereb. Blood Flow Metab. 33, 1514–1522 (2013).
[Crossref] [PubMed]

Farzam, P.

D. A. Boas, S. Sakadžić, J. Selb, P. Farzam, M. A. Franceschini, and S. A. Carp, “Establishing the diffuse correlation spectroscopy signal relationship with blood flow,” Neurophotonics 3, 031412 (2016).
[Crossref] [PubMed]

Faul, J. L.

H. W. Duchna, C. Guilleminault, R. A. Stoohs, J. L. Faul, H. Moreno, B. B. Hoffman, and T. F. Blaschke, “Vascular reactivity in obstructive sleep apnea syndrome,” Am. J. Respir. Crit. Care Med. 161, 187–191 (2000).
[Crossref] [PubMed]

Ferrari, M.

V. Quaresima and M. Ferrari, “Functional near-infrared spectroscopy (fnirs) for assessing cerebral cortex function during human behavior in natural/social situations: A concise review,” Organ. Res. Meth. 201610944 (2016).
[Crossref]

Franceschini, M.

D. Boas and M. Franceschini, “Haemoglobin oxygen saturation as a biomarker: the problem and a solution,” Philos. Trans. Royal Soc. As. 3694407–4424 (2011).
[Crossref]

Franceschini, M. A.

D. A. Boas, S. Sakadžić, J. Selb, P. Farzam, M. A. Franceschini, and S. A. Carp, “Establishing the diffuse correlation spectroscopy signal relationship with blood flow,” Neurophotonics 3, 031412 (2016).
[Crossref] [PubMed]

A. Devor, S. Sakadžić, V. J. Srinivasan, M. A. Yaseen, K. Nizar, P. A. Saisan, P. Tian, A. M. Dale, S. A. Vinogradov, M. A. Franceschini, and et al., “Frontiers in optical imaging of cerebral blood flow and metabolism,” J. Cereb. Blood Flow Metab. 32, 1259–1276 (2012).
[Crossref] [PubMed]

Fukuda, M.

M. Kameyama, M. Fukuda, T. Uehara, and M. Mikuni, “Sex and age dependencies of cerebral blood volume changes during cognitive activation: a multichannel near-infrared spectroscopy study,” Neuroimage 22, 1715–1721 (2004).
[Crossref] [PubMed]

Funane, T.

H. Atsumori, M. Kiguchi, A. Obata, H. Sato, T. Katura, T. Funane, and A. Maki, “Development of wearable optical topography system for mapping the prefrontal cortex activation,” Rev. Sci. Instrum. 80, 043704 (2009).
[Crossref] [PubMed]

Giavarina, D.

D. Giavarina, “Understanding bland altman analysis,” Biochem. Med. 25, 141–151 (2015).
[Crossref]

Gilbert, S.

P. Pinti, C. Aichelburg, F. Lind, S. Power, E. Swingler, A. Merla, A. Hamilton, S. Gilbert, P. Burgess, and I. Tachtsidis, “Using fiberless, wearable fnirs to monitor brain activity in real-world cognitive tasks,” J. Vis. Exp. (2015).
[Crossref] [PubMed]

Gisler, T.

Gittings, A.

R. Bandyopadhyay, A. Gittings, S. Suh, P. Dixon, and D. Durian, “Speckle-visibility spectroscopy: A tool to study time-varying dynamics,” Rev. Sci. Instrum. 76, 093110 (2005).
[Crossref]

Guilleminault, C.

H. W. Duchna, C. Guilleminault, R. A. Stoohs, J. L. Faul, H. Moreno, B. B. Hoffman, and T. F. Blaschke, “Vascular reactivity in obstructive sleep apnea syndrome,” Am. J. Respir. Crit. Care Med. 161, 187–191 (2000).
[Crossref] [PubMed]

Habermehl, C.

S. K. Piper, A. Krueger, S. P. Koch, J. Mehnert, C. Habermehl, J. Steinbrink, H. Obrig, and C. H. Schmitz, “A wearable multi-channel fnirs system for brain imaging in freely moving subjects,” Neuroimage 85, 64–71 (2014).
[Crossref]

Hamilton, A.

P. Pinti, C. Aichelburg, F. Lind, S. Power, E. Swingler, A. Merla, A. Hamilton, S. Gilbert, P. Burgess, and I. Tachtsidis, “Using fiberless, wearable fnirs to monitor brain activity in real-world cognitive tasks,” J. Vis. Exp. (2015).
[Crossref] [PubMed]

Hayes-Gill, B. R.

He, D.

Hoffman, B. B.

H. W. Duchna, C. Guilleminault, R. A. Stoohs, J. L. Faul, H. Moreno, B. B. Hoffman, and T. F. Blaschke, “Vascular reactivity in obstructive sleep apnea syndrome,” Am. J. Respir. Crit. Care Med. 161, 187–191 (2000).
[Crossref] [PubMed]

Izumi, S.-I.

N. Takeuchi, T. Mori, Y. Suzukamo, N. Tanaka, and S.-I. Izumi, “Parallel processing of cognitive and physical demands in left and right prefrontal cortices during smartphone use while walking,” BMC Neurosci. 17, 9 (2016).
[Crossref] [PubMed]

Jaillon, F.

Jain, V.

Z. B. Rodgers, V. Jain, E. K. Englund, M. C. Langham, and F. W. Wehrli, “High temporal resolution mri quantification of global cerebral metabolic rate of oxygen consumption in response to apneic challenge,” J. Cereb. Blood Flow Metab. 33, 1514–1522 (2013).
[Crossref] [PubMed]

Jones, T. A.

S. M. S. Kazmi, A. B. Parthasarthy, N. E. Song, T. A. Jones, and A. K. Dunn, “Chronic imaging of cortical blood flow using multi-exposure speckle imaging,” J. Cereb. Blood Flow Metab. 33, 798–808 (2013).
[Crossref] [PubMed]

Justicia, C.

Kameyama, M.

M. Kameyama, M. Fukuda, T. Uehara, and M. Mikuni, “Sex and age dependencies of cerebral blood volume changes during cognitive activation: a multichannel near-infrared spectroscopy study,” Neuroimage 22, 1715–1721 (2004).
[Crossref] [PubMed]

Katura, T.

H. Atsumori, M. Kiguchi, A. Obata, H. Sato, T. Katura, T. Funane, and A. Maki, “Development of wearable optical topography system for mapping the prefrontal cortex activation,” Rev. Sci. Instrum. 80, 043704 (2009).
[Crossref] [PubMed]

Kazmi, S. M. S.

S. M. S. Kazmi, A. B. Parthasarthy, N. E. Song, T. A. Jones, and A. K. Dunn, “Chronic imaging of cortical blood flow using multi-exposure speckle imaging,” J. Cereb. Blood Flow Metab. 33, 798–808 (2013).
[Crossref] [PubMed]

Keenan, B. T.

Z. B. Rodgers, S. E. Leinwand, B. T. Keenan, L. G. Kini, R. J. Schwab, and F. W. Wehrli, “Cerebral metabolic rate of oxygen in obstructive sleep apnea at rest and in response to breath-hold challenge,” J. Cereb. Blood Flow Metab. 36, 755–767 (2016).
[Crossref]

Kiguchi, M.

H. Atsumori, M. Kiguchi, A. Obata, H. Sato, T. Katura, T. Funane, and A. Maki, “Development of wearable optical topography system for mapping the prefrontal cortex activation,” Rev. Sci. Instrum. 80, 043704 (2009).
[Crossref] [PubMed]

Kini, L. G.

Z. B. Rodgers, S. E. Leinwand, B. T. Keenan, L. G. Kini, R. J. Schwab, and F. W. Wehrli, “Cerebral metabolic rate of oxygen in obstructive sleep apnea at rest and in response to breath-hold challenge,” J. Cereb. Blood Flow Metab. 36, 755–767 (2016).
[Crossref]

Koch, S. P.

S. K. Piper, A. Krueger, S. P. Koch, J. Mehnert, C. Habermehl, J. Steinbrink, H. Obrig, and C. H. Schmitz, “A wearable multi-channel fnirs system for brain imaging in freely moving subjects,” Neuroimage 85, 64–71 (2014).
[Crossref]

Kristoffersen, A. K.

Krueger, A.

S. K. Piper, A. Krueger, S. P. Koch, J. Mehnert, C. Habermehl, J. Steinbrink, H. Obrig, and C. H. Schmitz, “A wearable multi-channel fnirs system for brain imaging in freely moving subjects,” Neuroimage 85, 64–71 (2014).
[Crossref]

Kuczek, T.

B. Walsh, F. Tian, J. Tourville, M. Yücel, T. Kuczek, and A. Bostian, “Hemodynamics of speech production: An fnirs investigation of children who stutter,” Sci. Rep. 74034 (2017).
[Crossref]

Langham, M. C.

Z. B. Rodgers, V. Jain, E. K. Englund, M. C. Langham, and F. W. Wehrli, “High temporal resolution mri quantification of global cerebral metabolic rate of oxygen consumption in response to apneic challenge,” J. Cereb. Blood Flow Metab. 33, 1514–1522 (2013).
[Crossref] [PubMed]

Lech, G.

G. Yu, T. Durduran, G. Lech, C. Zhou, B. Chance, E. R. Mohler, and A. G. Yodh, “Time-dependent blood flow and oxygenation in human skeletal muscles measured with noninvasive near-infrared diffuse optical spectroscopies,” J. Biomed. Opt. 10, 024027 (2005).
[Crossref] [PubMed]

Lee, K.

Leinwand, S. E.

Z. B. Rodgers, S. E. Leinwand, B. T. Keenan, L. G. Kini, R. J. Schwab, and F. W. Wehrli, “Cerebral metabolic rate of oxygen in obstructive sleep apnea at rest and in response to breath-hold challenge,” J. Cereb. Blood Flow Metab. 36, 755–767 (2016).
[Crossref]

Li, J.

Lind, F.

P. Pinti, C. Aichelburg, F. Lind, S. Power, E. Swingler, A. Merla, A. Hamilton, S. Gilbert, P. Burgess, and I. Tachtsidis, “Using fiberless, wearable fnirs to monitor brain activity in real-world cognitive tasks,” J. Vis. Exp. (2015).
[Crossref] [PubMed]

Maki, A.

H. Atsumori, M. Kiguchi, A. Obata, H. Sato, T. Katura, T. Funane, and A. Maki, “Development of wearable optical topography system for mapping the prefrontal cortex activation,” Rev. Sci. Instrum. 80, 043704 (2009).
[Crossref] [PubMed]

Marcel, G.

A. H. van Beek, H. M. de Wit, O. Rikkert, G. Marcel, and J. A. Claassen, “Incorrect performance of the breath hold method in the old underestimates cerebrovascular reactivity and goes unnoticed without concomitant blood pressure and end-tidal co2 registration,” J. Neuroimaging 21, 340–347 (2011).
[Crossref] [PubMed]

Mehnert, J.

S. K. Piper, A. Krueger, S. P. Koch, J. Mehnert, C. Habermehl, J. Steinbrink, H. Obrig, and C. H. Schmitz, “A wearable multi-channel fnirs system for brain imaging in freely moving subjects,” Neuroimage 85, 64–71 (2014).
[Crossref]

Merla, A.

P. Pinti, C. Aichelburg, F. Lind, S. Power, E. Swingler, A. Merla, A. Hamilton, S. Gilbert, P. Burgess, and I. Tachtsidis, “Using fiberless, wearable fnirs to monitor brain activity in real-world cognitive tasks,” J. Vis. Exp. (2015).
[Crossref] [PubMed]

Mikuni, M.

M. Kameyama, M. Fukuda, T. Uehara, and M. Mikuni, “Sex and age dependencies of cerebral blood volume changes during cognitive activation: a multichannel near-infrared spectroscopy study,” Neuroimage 22, 1715–1721 (2004).
[Crossref] [PubMed]

Mohler, E. R.

G. Yu, T. Durduran, G. Lech, C. Zhou, B. Chance, E. R. Mohler, and A. G. Yodh, “Time-dependent blood flow and oxygenation in human skeletal muscles measured with noninvasive near-infrared diffuse optical spectroscopies,” J. Biomed. Opt. 10, 024027 (2005).
[Crossref] [PubMed]

Moreno, H.

H. W. Duchna, C. Guilleminault, R. A. Stoohs, J. L. Faul, H. Moreno, B. B. Hoffman, and T. F. Blaschke, “Vascular reactivity in obstructive sleep apnea syndrome,” Am. J. Respir. Crit. Care Med. 161, 187–191 (2000).
[Crossref] [PubMed]

Morgan, S. P.

Mori, T.

N. Takeuchi, T. Mori, Y. Suzukamo, N. Tanaka, and S.-I. Izumi, “Parallel processing of cognitive and physical demands in left and right prefrontal cortices during smartphone use while walking,” BMC Neurosci. 17, 9 (2016).
[Crossref] [PubMed]

Moskowitz, M. A.

A. K. Dunn, H. Bolay, M. A. Moskowitz, and D. A. Boas, “Dynamic imaging of cerebral blood flow using laser speckle,” J. Cereb. Blood Flow Metab. 21, 195–201 (2001).
[Crossref] [PubMed]

Muizelaar, J. P.

A. Zauner and J. P. Muizelaar, “Brain metabolism and cerebral blood flow,” Head Inj. 199789–99 (1997).

Ninck, M.

Nizar, K.

A. Devor, S. Sakadžić, V. J. Srinivasan, M. A. Yaseen, K. Nizar, P. A. Saisan, P. Tian, A. M. Dale, S. A. Vinogradov, M. A. Franceschini, and et al., “Frontiers in optical imaging of cerebral blood flow and metabolism,” J. Cereb. Blood Flow Metab. 32, 1259–1276 (2012).
[Crossref] [PubMed]

Obata, A.

H. Atsumori, M. Kiguchi, A. Obata, H. Sato, T. Katura, T. Funane, and A. Maki, “Development of wearable optical topography system for mapping the prefrontal cortex activation,” Rev. Sci. Instrum. 80, 043704 (2009).
[Crossref] [PubMed]

Obrig, H.

S. K. Piper, A. Krueger, S. P. Koch, J. Mehnert, C. Habermehl, J. Steinbrink, H. Obrig, and C. H. Schmitz, “A wearable multi-channel fnirs system for brain imaging in freely moving subjects,” Neuroimage 85, 64–71 (2014).
[Crossref]

Ortolf, C.

Parthasarathy, A. B.

Parthasarthy, A. B.

S. M. S. Kazmi, A. B. Parthasarthy, N. E. Song, T. A. Jones, and A. K. Dunn, “Chronic imaging of cortical blood flow using multi-exposure speckle imaging,” J. Cereb. Blood Flow Metab. 33, 798–808 (2013).
[Crossref] [PubMed]

Pinti, P.

P. Pinti, C. Aichelburg, F. Lind, S. Power, E. Swingler, A. Merla, A. Hamilton, S. Gilbert, P. Burgess, and I. Tachtsidis, “Using fiberless, wearable fnirs to monitor brain activity in real-world cognitive tasks,” J. Vis. Exp. (2015).
[Crossref] [PubMed]

Piper, S. K.

S. K. Piper, A. Krueger, S. P. Koch, J. Mehnert, C. Habermehl, J. Steinbrink, H. Obrig, and C. H. Schmitz, “A wearable multi-channel fnirs system for brain imaging in freely moving subjects,” Neuroimage 85, 64–71 (2014).
[Crossref]

Power, S.

P. Pinti, C. Aichelburg, F. Lind, S. Power, E. Swingler, A. Merla, A. Hamilton, S. Gilbert, P. Burgess, and I. Tachtsidis, “Using fiberless, wearable fnirs to monitor brain activity in real-world cognitive tasks,” J. Vis. Exp. (2015).
[Crossref] [PubMed]

Quaresima, V.

V. Quaresima and M. Ferrari, “Functional near-infrared spectroscopy (fnirs) for assessing cerebral cortex function during human behavior in natural/social situations: A concise review,” Organ. Res. Meth. 201610944 (2016).
[Crossref]

Rajan, V.

V. Rajan, B. Varghese, T. G. van Leeuwen, and W. Steenbergen, “Review of methodological developments in laser doppler flowmetry,” Lasers Med. Sci. 24, 269–283 (2009).
[Crossref]

Rikkert, O.

A. H. van Beek, H. M. de Wit, O. Rikkert, G. Marcel, and J. A. Claassen, “Incorrect performance of the breath hold method in the old underestimates cerebrovascular reactivity and goes unnoticed without concomitant blood pressure and end-tidal co2 registration,” J. Neuroimaging 21, 340–347 (2011).
[Crossref] [PubMed]

Rodgers, Z. B.

Z. B. Rodgers, S. E. Leinwand, B. T. Keenan, L. G. Kini, R. J. Schwab, and F. W. Wehrli, “Cerebral metabolic rate of oxygen in obstructive sleep apnea at rest and in response to breath-hold challenge,” J. Cereb. Blood Flow Metab. 36, 755–767 (2016).
[Crossref]

Z. B. Rodgers, V. Jain, E. K. Englund, M. C. Langham, and F. W. Wehrli, “High temporal resolution mri quantification of global cerebral metabolic rate of oxygen consumption in response to apneic challenge,” J. Cereb. Blood Flow Metab. 33, 1514–1522 (2013).
[Crossref] [PubMed]

Ruggeri, A.

D. Tamborini, M. Buttafava, A. Ruggeri, and F. Zappa, “Compact, low-power and fully reconfigurable 10 ps resolution, 160 range, time-resolved single-photon counting system,” IEEE Sens. J. 16, 3827–3833 (2016).
[Crossref]

Saisan, P. A.

A. Devor, S. Sakadžić, V. J. Srinivasan, M. A. Yaseen, K. Nizar, P. A. Saisan, P. Tian, A. M. Dale, S. A. Vinogradov, M. A. Franceschini, and et al., “Frontiers in optical imaging of cerebral blood flow and metabolism,” J. Cereb. Blood Flow Metab. 32, 1259–1276 (2012).
[Crossref] [PubMed]

Sakadžic, S.

D. A. Boas, S. Sakadžić, J. Selb, P. Farzam, M. A. Franceschini, and S. A. Carp, “Establishing the diffuse correlation spectroscopy signal relationship with blood flow,” Neurophotonics 3, 031412 (2016).
[Crossref] [PubMed]

A. Devor, S. Sakadžić, V. J. Srinivasan, M. A. Yaseen, K. Nizar, P. A. Saisan, P. Tian, A. M. Dale, S. A. Vinogradov, M. A. Franceschini, and et al., “Frontiers in optical imaging of cerebral blood flow and metabolism,” J. Cereb. Blood Flow Metab. 32, 1259–1276 (2012).
[Crossref] [PubMed]

Sato, H.

H. Atsumori, M. Kiguchi, A. Obata, H. Sato, T. Katura, T. Funane, and A. Maki, “Development of wearable optical topography system for mapping the prefrontal cortex activation,” Rev. Sci. Instrum. 80, 043704 (2009).
[Crossref] [PubMed]

Scarcella, C.

C. Scarcella, A. Tosi, F. Villa, S. Tisa, and F. Zappa, “Low-noise low-jitter 32-pixels cmos single-photon avalanche diodes array for single-photon counting from 300 nm to 900 nm,” Rev. Sci. Instrum. 84, 123112 (2013).
[Crossref]

Schmitz, C. H.

S. K. Piper, A. Krueger, S. P. Koch, J. Mehnert, C. Habermehl, J. Steinbrink, H. Obrig, and C. H. Schmitz, “A wearable multi-channel fnirs system for brain imaging in freely moving subjects,” Neuroimage 85, 64–71 (2014).
[Crossref]

Schwab, R. J.

Z. B. Rodgers, S. E. Leinwand, B. T. Keenan, L. G. Kini, R. J. Schwab, and F. W. Wehrli, “Cerebral metabolic rate of oxygen in obstructive sleep apnea at rest and in response to breath-hold challenge,” J. Cereb. Blood Flow Metab. 36, 755–767 (2016).
[Crossref]

Selb, J.

D. A. Boas, S. Sakadžić, J. Selb, P. Farzam, M. A. Franceschini, and S. A. Carp, “Establishing the diffuse correlation spectroscopy signal relationship with blood flow,” Neurophotonics 3, 031412 (2016).
[Crossref] [PubMed]

Shams Kazmi, S.

Song, N. E.

S. M. S. Kazmi, A. B. Parthasarthy, N. E. Song, T. A. Jones, and A. K. Dunn, “Chronic imaging of cortical blood flow using multi-exposure speckle imaging,” J. Cereb. Blood Flow Metab. 33, 798–808 (2013).
[Crossref] [PubMed]

Srinivasan, V. J.

A. Devor, S. Sakadžić, V. J. Srinivasan, M. A. Yaseen, K. Nizar, P. A. Saisan, P. Tian, A. M. Dale, S. A. Vinogradov, M. A. Franceschini, and et al., “Frontiers in optical imaging of cerebral blood flow and metabolism,” J. Cereb. Blood Flow Metab. 32, 1259–1276 (2012).
[Crossref] [PubMed]

Steenbergen, W.

V. Rajan, B. Varghese, T. G. van Leeuwen, and W. Steenbergen, “Review of methodological developments in laser doppler flowmetry,” Lasers Med. Sci. 24, 269–283 (2009).
[Crossref]

Steinbrink, J.

S. K. Piper, A. Krueger, S. P. Koch, J. Mehnert, C. Habermehl, J. Steinbrink, H. Obrig, and C. H. Schmitz, “A wearable multi-channel fnirs system for brain imaging in freely moving subjects,” Neuroimage 85, 64–71 (2014).
[Crossref]

Stoohs, R. A.

H. W. Duchna, C. Guilleminault, R. A. Stoohs, J. L. Faul, H. Moreno, B. B. Hoffman, and T. F. Blaschke, “Vascular reactivity in obstructive sleep apnea syndrome,” Am. J. Respir. Crit. Care Med. 161, 187–191 (2000).
[Crossref] [PubMed]

Suh, S.

R. Bandyopadhyay, A. Gittings, S. Suh, P. Dixon, and D. Durian, “Speckle-visibility spectroscopy: A tool to study time-varying dynamics,” Rev. Sci. Instrum. 76, 093110 (2005).
[Crossref]

Sun, S.

Suzukamo, Y.

N. Takeuchi, T. Mori, Y. Suzukamo, N. Tanaka, and S.-I. Izumi, “Parallel processing of cognitive and physical demands in left and right prefrontal cortices during smartphone use while walking,” BMC Neurosci. 17, 9 (2016).
[Crossref] [PubMed]

Swingler, E.

P. Pinti, C. Aichelburg, F. Lind, S. Power, E. Swingler, A. Merla, A. Hamilton, S. Gilbert, P. Burgess, and I. Tachtsidis, “Using fiberless, wearable fnirs to monitor brain activity in real-world cognitive tasks,” J. Vis. Exp. (2015).
[Crossref] [PubMed]

Tachtsidis, I.

P. Pinti, C. Aichelburg, F. Lind, S. Power, E. Swingler, A. Merla, A. Hamilton, S. Gilbert, P. Burgess, and I. Tachtsidis, “Using fiberless, wearable fnirs to monitor brain activity in real-world cognitive tasks,” J. Vis. Exp. (2015).
[Crossref] [PubMed]

Takeuchi, N.

N. Takeuchi, T. Mori, Y. Suzukamo, N. Tanaka, and S.-I. Izumi, “Parallel processing of cognitive and physical demands in left and right prefrontal cortices during smartphone use while walking,” BMC Neurosci. 17, 9 (2016).
[Crossref] [PubMed]

Tamborini, D.

D. Tamborini, M. Buttafava, A. Ruggeri, and F. Zappa, “Compact, low-power and fully reconfigurable 10 ps resolution, 160 range, time-resolved single-photon counting system,” IEEE Sens. J. 16, 3827–3833 (2016).
[Crossref]

Tanaka, N.

N. Takeuchi, T. Mori, Y. Suzukamo, N. Tanaka, and S.-I. Izumi, “Parallel processing of cognitive and physical demands in left and right prefrontal cortices during smartphone use while walking,” BMC Neurosci. 17, 9 (2016).
[Crossref] [PubMed]

Tian, F.

B. Walsh, F. Tian, J. Tourville, M. Yücel, T. Kuczek, and A. Bostian, “Hemodynamics of speech production: An fnirs investigation of children who stutter,” Sci. Rep. 74034 (2017).
[Crossref]

Tian, P.

A. Devor, S. Sakadžić, V. J. Srinivasan, M. A. Yaseen, K. Nizar, P. A. Saisan, P. Tian, A. M. Dale, S. A. Vinogradov, M. A. Franceschini, and et al., “Frontiers in optical imaging of cerebral blood flow and metabolism,” J. Cereb. Blood Flow Metab. 32, 1259–1276 (2012).
[Crossref] [PubMed]

Tisa, S.

D. Bronzi, F. Villa, S. Tisa, A. Tosi, F. Zappa, D. Durini, S. Weyers, and W. Brockherde, “100 000 frames/s 64 × 32 single-photon detector array for 2-d imaging and 3-d ranging,” IEEE J. Sel. Top. Quantum Electron. 20, 354–363 (2014).
[Crossref]

C. Scarcella, A. Tosi, F. Villa, S. Tisa, and F. Zappa, “Low-noise low-jitter 32-pixels cmos single-photon avalanche diodes array for single-photon counting from 300 nm to 900 nm,” Rev. Sci. Instrum. 84, 123112 (2013).
[Crossref]

D. Bronzi, S. Tisa, F. Villa, S. Bellisai, A. Tosi, and F. Zappa, “Fast sensing and quenching of cmos spads for minimal afterpulsing effects,” IEEE Photon. Technol. Lett. 25, 776–779 (2013).
[Crossref]

Tosi, A.

T. Dragojević, D. Bronzi, H. M. Varma, C. P. Valdes, C. Castellvi, F. Villa, A. Tosi, C. Justicia, F. Zappa, and T. Durduran, “High-speed multi-exposure laser speckle contrast imaging with a single-photon counting camera,” Biomed. Opt. Express 6, 2865–2876 (2015).
[Crossref]

D. Bronzi, F. Villa, S. Tisa, A. Tosi, F. Zappa, D. Durini, S. Weyers, and W. Brockherde, “100 000 frames/s 64 × 32 single-photon detector array for 2-d imaging and 3-d ranging,” IEEE J. Sel. Top. Quantum Electron. 20, 354–363 (2014).
[Crossref]

C. Scarcella, A. Tosi, F. Villa, S. Tisa, and F. Zappa, “Low-noise low-jitter 32-pixels cmos single-photon avalanche diodes array for single-photon counting from 300 nm to 900 nm,” Rev. Sci. Instrum. 84, 123112 (2013).
[Crossref]

D. Bronzi, S. Tisa, F. Villa, S. Bellisai, A. Tosi, and F. Zappa, “Fast sensing and quenching of cmos spads for minimal afterpulsing effects,” IEEE Photon. Technol. Lett. 25, 776–779 (2013).
[Crossref]

Tourville, J.

B. Walsh, F. Tian, J. Tourville, M. Yücel, T. Kuczek, and A. Bostian, “Hemodynamics of speech production: An fnirs investigation of children who stutter,” Sci. Rep. 74034 (2017).
[Crossref]

Uehara, T.

M. Kameyama, M. Fukuda, T. Uehara, and M. Mikuni, “Sex and age dependencies of cerebral blood volume changes during cognitive activation: a multichannel near-infrared spectroscopy study,” Neuroimage 22, 1715–1721 (2004).
[Crossref] [PubMed]

Valdes, C. P.

van Beek, A. H.

A. H. van Beek, H. M. de Wit, O. Rikkert, G. Marcel, and J. A. Claassen, “Incorrect performance of the breath hold method in the old underestimates cerebrovascular reactivity and goes unnoticed without concomitant blood pressure and end-tidal co2 registration,” J. Neuroimaging 21, 340–347 (2011).
[Crossref] [PubMed]

van Leeuwen, T. G.

V. Rajan, B. Varghese, T. G. van Leeuwen, and W. Steenbergen, “Review of methodological developments in laser doppler flowmetry,” Lasers Med. Sci. 24, 269–283 (2009).
[Crossref]

Varghese, B.

V. Rajan, B. Varghese, T. G. van Leeuwen, and W. Steenbergen, “Review of methodological developments in laser doppler flowmetry,” Lasers Med. Sci. 24, 269–283 (2009).
[Crossref]

Varma, H. M.

Villa, F.

T. Dragojević, D. Bronzi, H. M. Varma, C. P. Valdes, C. Castellvi, F. Villa, A. Tosi, C. Justicia, F. Zappa, and T. Durduran, “High-speed multi-exposure laser speckle contrast imaging with a single-photon counting camera,” Biomed. Opt. Express 6, 2865–2876 (2015).
[Crossref]

D. Bronzi, F. Villa, S. Tisa, A. Tosi, F. Zappa, D. Durini, S. Weyers, and W. Brockherde, “100 000 frames/s 64 × 32 single-photon detector array for 2-d imaging and 3-d ranging,” IEEE J. Sel. Top. Quantum Electron. 20, 354–363 (2014).
[Crossref]

C. Scarcella, A. Tosi, F. Villa, S. Tisa, and F. Zappa, “Low-noise low-jitter 32-pixels cmos single-photon avalanche diodes array for single-photon counting from 300 nm to 900 nm,” Rev. Sci. Instrum. 84, 123112 (2013).
[Crossref]

D. Bronzi, S. Tisa, F. Villa, S. Bellisai, A. Tosi, and F. Zappa, “Fast sensing and quenching of cmos spads for minimal afterpulsing effects,” IEEE Photon. Technol. Lett. 25, 776–779 (2013).
[Crossref]

Vinogradov, S. A.

A. Devor, S. Sakadžić, V. J. Srinivasan, M. A. Yaseen, K. Nizar, P. A. Saisan, P. Tian, A. M. Dale, S. A. Vinogradov, M. A. Franceschini, and et al., “Frontiers in optical imaging of cerebral blood flow and metabolism,” J. Cereb. Blood Flow Metab. 32, 1259–1276 (2012).
[Crossref] [PubMed]

Walsh, B.

B. Walsh, F. Tian, J. Tourville, M. Yücel, T. Kuczek, and A. Bostian, “Hemodynamics of speech production: An fnirs investigation of children who stutter,” Sci. Rep. 74034 (2017).
[Crossref]

Wehrli, F. W.

Z. B. Rodgers, S. E. Leinwand, B. T. Keenan, L. G. Kini, R. J. Schwab, and F. W. Wehrli, “Cerebral metabolic rate of oxygen in obstructive sleep apnea at rest and in response to breath-hold challenge,” J. Cereb. Blood Flow Metab. 36, 755–767 (2016).
[Crossref]

Z. B. Rodgers, V. Jain, E. K. Englund, M. C. Langham, and F. W. Wehrli, “High temporal resolution mri quantification of global cerebral metabolic rate of oxygen consumption in response to apneic challenge,” J. Cereb. Blood Flow Metab. 33, 1514–1522 (2013).
[Crossref] [PubMed]

Weyers, S.

D. Bronzi, F. Villa, S. Tisa, A. Tosi, F. Zappa, D. Durini, S. Weyers, and W. Brockherde, “100 000 frames/s 64 × 32 single-photon detector array for 2-d imaging and 3-d ranging,” IEEE J. Sel. Top. Quantum Electron. 20, 354–363 (2014).
[Crossref]

Yaseen, M. A.

A. Devor, S. Sakadžić, V. J. Srinivasan, M. A. Yaseen, K. Nizar, P. A. Saisan, P. Tian, A. M. Dale, S. A. Vinogradov, M. A. Franceschini, and et al., “Frontiers in optical imaging of cerebral blood flow and metabolism,” J. Cereb. Blood Flow Metab. 32, 1259–1276 (2012).
[Crossref] [PubMed]

Yodh, A. G.

T. Durduran, R. Choe, W. Baker, and A. G. Yodh, “Diffuse optics for tissue monitoring and tomography,” Rep. Prog. Phys. 73, 076701 (2010).
[Crossref] [PubMed]

G. Yu, T. Durduran, G. Lech, C. Zhou, B. Chance, E. R. Mohler, and A. G. Yodh, “Time-dependent blood flow and oxygenation in human skeletal muscles measured with noninvasive near-infrared diffuse optical spectroscopies,” J. Biomed. Opt. 10, 024027 (2005).
[Crossref] [PubMed]

D. A. Boas, L. Campbell, and A. G. Yodh, “Scattering and imaging with diffusing temporal field correlations,” Phys. Rev. Lett. 75, 1855 (1995).
[Crossref] [PubMed]

Yu, G.

G. Yu, T. Durduran, G. Lech, C. Zhou, B. Chance, E. R. Mohler, and A. G. Yodh, “Time-dependent blood flow and oxygenation in human skeletal muscles measured with noninvasive near-infrared diffuse optical spectroscopies,” J. Biomed. Opt. 10, 024027 (2005).
[Crossref] [PubMed]

Yücel, M.

B. Walsh, F. Tian, J. Tourville, M. Yücel, T. Kuczek, and A. Bostian, “Hemodynamics of speech production: An fnirs investigation of children who stutter,” Sci. Rep. 74034 (2017).
[Crossref]

Zappa, F.

D. Tamborini, M. Buttafava, A. Ruggeri, and F. Zappa, “Compact, low-power and fully reconfigurable 10 ps resolution, 160 range, time-resolved single-photon counting system,” IEEE Sens. J. 16, 3827–3833 (2016).
[Crossref]

T. Dragojević, D. Bronzi, H. M. Varma, C. P. Valdes, C. Castellvi, F. Villa, A. Tosi, C. Justicia, F. Zappa, and T. Durduran, “High-speed multi-exposure laser speckle contrast imaging with a single-photon counting camera,” Biomed. Opt. Express 6, 2865–2876 (2015).
[Crossref]

D. Bronzi, F. Villa, S. Tisa, A. Tosi, F. Zappa, D. Durini, S. Weyers, and W. Brockherde, “100 000 frames/s 64 × 32 single-photon detector array for 2-d imaging and 3-d ranging,” IEEE J. Sel. Top. Quantum Electron. 20, 354–363 (2014).
[Crossref]

C. Scarcella, A. Tosi, F. Villa, S. Tisa, and F. Zappa, “Low-noise low-jitter 32-pixels cmos single-photon avalanche diodes array for single-photon counting from 300 nm to 900 nm,” Rev. Sci. Instrum. 84, 123112 (2013).
[Crossref]

D. Bronzi, S. Tisa, F. Villa, S. Bellisai, A. Tosi, and F. Zappa, “Fast sensing and quenching of cmos spads for minimal afterpulsing effects,” IEEE Photon. Technol. Lett. 25, 776–779 (2013).
[Crossref]

Zauner, A.

A. Zauner and J. P. Muizelaar, “Brain metabolism and cerebral blood flow,” Head Inj. 199789–99 (1997).

Zhou, C.

G. Yu, T. Durduran, G. Lech, C. Zhou, B. Chance, E. R. Mohler, and A. G. Yodh, “Time-dependent blood flow and oxygenation in human skeletal muscles measured with noninvasive near-infrared diffuse optical spectroscopies,” J. Biomed. Opt. 10, 024027 (2005).
[Crossref] [PubMed]

Zhu, Y.

Am. J. Respir. Crit. Care Med. (1)

H. W. Duchna, C. Guilleminault, R. A. Stoohs, J. L. Faul, H. Moreno, B. B. Hoffman, and T. F. Blaschke, “Vascular reactivity in obstructive sleep apnea syndrome,” Am. J. Respir. Crit. Care Med. 161, 187–191 (2000).
[Crossref] [PubMed]

Ann. Biomed. Eng. (1)

A. K. Dunn, “Laser speckle contrast imaging of cerebral blood flow,” Ann. Biomed. Eng. 40, 367–377 (2012).
[Crossref]

Appl. Opt. (1)

Biochem. Med. (1)

D. Giavarina, “Understanding bland altman analysis,” Biochem. Med. 25, 141–151 (2015).
[Crossref]

Biomed. Opt. Express (3)

BMC Neurosci. (1)

N. Takeuchi, T. Mori, Y. Suzukamo, N. Tanaka, and S.-I. Izumi, “Parallel processing of cognitive and physical demands in left and right prefrontal cortices during smartphone use while walking,” BMC Neurosci. 17, 9 (2016).
[Crossref] [PubMed]

Head Inj. (1)

A. Zauner and J. P. Muizelaar, “Brain metabolism and cerebral blood flow,” Head Inj. 199789–99 (1997).

IEEE J. Sel. Top. Quantum Electron. (1)

D. Bronzi, F. Villa, S. Tisa, A. Tosi, F. Zappa, D. Durini, S. Weyers, and W. Brockherde, “100 000 frames/s 64 × 32 single-photon detector array for 2-d imaging and 3-d ranging,” IEEE J. Sel. Top. Quantum Electron. 20, 354–363 (2014).
[Crossref]

IEEE Photon. Technol. Lett. (1)

D. Bronzi, S. Tisa, F. Villa, S. Bellisai, A. Tosi, and F. Zappa, “Fast sensing and quenching of cmos spads for minimal afterpulsing effects,” IEEE Photon. Technol. Lett. 25, 776–779 (2013).
[Crossref]

IEEE Sens. J. (1)

D. Tamborini, M. Buttafava, A. Ruggeri, and F. Zappa, “Compact, low-power and fully reconfigurable 10 ps resolution, 160 range, time-resolved single-photon counting system,” IEEE Sens. J. 16, 3827–3833 (2016).
[Crossref]

J. Biomed. Opt. (2)

G. Yu, T. Durduran, G. Lech, C. Zhou, B. Chance, E. R. Mohler, and A. G. Yodh, “Time-dependent blood flow and oxygenation in human skeletal muscles measured with noninvasive near-infrared diffuse optical spectroscopies,” J. Biomed. Opt. 10, 024027 (2005).
[Crossref] [PubMed]

D. A. Boas and A. K. Dunn, “Laser speckle contrast imaging in biomedical optics,” J. Biomed. Opt. 15, 011109 (2010).
[Crossref] [PubMed]

J. Cereb. Blood Flow Metab. (5)

A. Devor, S. Sakadžić, V. J. Srinivasan, M. A. Yaseen, K. Nizar, P. A. Saisan, P. Tian, A. M. Dale, S. A. Vinogradov, M. A. Franceschini, and et al., “Frontiers in optical imaging of cerebral blood flow and metabolism,” J. Cereb. Blood Flow Metab. 32, 1259–1276 (2012).
[Crossref] [PubMed]

A. K. Dunn, H. Bolay, M. A. Moskowitz, and D. A. Boas, “Dynamic imaging of cerebral blood flow using laser speckle,” J. Cereb. Blood Flow Metab. 21, 195–201 (2001).
[Crossref] [PubMed]

S. M. S. Kazmi, A. B. Parthasarthy, N. E. Song, T. A. Jones, and A. K. Dunn, “Chronic imaging of cortical blood flow using multi-exposure speckle imaging,” J. Cereb. Blood Flow Metab. 33, 798–808 (2013).
[Crossref] [PubMed]

Z. B. Rodgers, S. E. Leinwand, B. T. Keenan, L. G. Kini, R. J. Schwab, and F. W. Wehrli, “Cerebral metabolic rate of oxygen in obstructive sleep apnea at rest and in response to breath-hold challenge,” J. Cereb. Blood Flow Metab. 36, 755–767 (2016).
[Crossref]

Z. B. Rodgers, V. Jain, E. K. Englund, M. C. Langham, and F. W. Wehrli, “High temporal resolution mri quantification of global cerebral metabolic rate of oxygen consumption in response to apneic challenge,” J. Cereb. Blood Flow Metab. 33, 1514–1522 (2013).
[Crossref] [PubMed]

J. Neuroimaging (1)

A. H. van Beek, H. M. de Wit, O. Rikkert, G. Marcel, and J. A. Claassen, “Incorrect performance of the breath hold method in the old underestimates cerebrovascular reactivity and goes unnoticed without concomitant blood pressure and end-tidal co2 registration,” J. Neuroimaging 21, 340–347 (2011).
[Crossref] [PubMed]

Lasers Med. Sci. (1)

V. Rajan, B. Varghese, T. G. van Leeuwen, and W. Steenbergen, “Review of methodological developments in laser doppler flowmetry,” Lasers Med. Sci. 24, 269–283 (2009).
[Crossref]

Neuroimage (2)

S. K. Piper, A. Krueger, S. P. Koch, J. Mehnert, C. Habermehl, J. Steinbrink, H. Obrig, and C. H. Schmitz, “A wearable multi-channel fnirs system for brain imaging in freely moving subjects,” Neuroimage 85, 64–71 (2014).
[Crossref]

M. Kameyama, M. Fukuda, T. Uehara, and M. Mikuni, “Sex and age dependencies of cerebral blood volume changes during cognitive activation: a multichannel near-infrared spectroscopy study,” Neuroimage 22, 1715–1721 (2004).
[Crossref] [PubMed]

Neurophotonics (1)

D. A. Boas, S. Sakadžić, J. Selb, P. Farzam, M. A. Franceschini, and S. A. Carp, “Establishing the diffuse correlation spectroscopy signal relationship with blood flow,” Neurophotonics 3, 031412 (2016).
[Crossref] [PubMed]

Opt. Express (1)

Opt. Lett. (2)

Organ. Res. Meth. (1)

V. Quaresima and M. Ferrari, “Functional near-infrared spectroscopy (fnirs) for assessing cerebral cortex function during human behavior in natural/social situations: A concise review,” Organ. Res. Meth. 201610944 (2016).
[Crossref]

Philos. Trans. Royal Soc. As. (1)

D. Boas and M. Franceschini, “Haemoglobin oxygen saturation as a biomarker: the problem and a solution,” Philos. Trans. Royal Soc. As. 3694407–4424 (2011).
[Crossref]

Phys. Rev. Lett. (1)

D. A. Boas, L. Campbell, and A. G. Yodh, “Scattering and imaging with diffusing temporal field correlations,” Phys. Rev. Lett. 75, 1855 (1995).
[Crossref] [PubMed]

Physiol. Meas. (1)

J. D. Briers, “Laser doppler, speckle and related techniques for blood perfusion mapping and imaging,” Physiol. Meas. 22, R35 (2001).
[Crossref]

Rep. Prog. Phys. (1)

T. Durduran, R. Choe, W. Baker, and A. G. Yodh, “Diffuse optics for tissue monitoring and tomography,” Rep. Prog. Phys. 73, 076701 (2010).
[Crossref] [PubMed]

Rev. Sci. Instrum. (3)

C. Scarcella, A. Tosi, F. Villa, S. Tisa, and F. Zappa, “Low-noise low-jitter 32-pixels cmos single-photon avalanche diodes array for single-photon counting from 300 nm to 900 nm,” Rev. Sci. Instrum. 84, 123112 (2013).
[Crossref]

R. Bandyopadhyay, A. Gittings, S. Suh, P. Dixon, and D. Durian, “Speckle-visibility spectroscopy: A tool to study time-varying dynamics,” Rev. Sci. Instrum. 76, 093110 (2005).
[Crossref]

H. Atsumori, M. Kiguchi, A. Obata, H. Sato, T. Katura, T. Funane, and A. Maki, “Development of wearable optical topography system for mapping the prefrontal cortex activation,” Rev. Sci. Instrum. 80, 043704 (2009).
[Crossref] [PubMed]

Sci. Rep. (1)

B. Walsh, F. Tian, J. Tourville, M. Yücel, T. Kuczek, and A. Bostian, “Hemodynamics of speech production: An fnirs investigation of children who stutter,” Sci. Rep. 74034 (2017).
[Crossref]

Other (2)

P. Pinti, C. Aichelburg, F. Lind, S. Power, E. Swingler, A. Merla, A. Hamilton, S. Gilbert, P. Burgess, and I. Tachtsidis, “Using fiberless, wearable fnirs to monitor brain activity in real-world cognitive tasks,” J. Vis. Exp. (2015).
[Crossref] [PubMed]

D. A. Boas, “Diffuse photon probes of structural and dynamical properties of turbid media: theory and biomedical applications,” Ph.D. thesis, Citeseer (1996).

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Figures (7)

Fig. 1
Fig. 1 Detection block diagram. The detection board hosts the 32 by 2 SPAD array and two FPGAs, able to compute the speckle contrast. The platform board handles the serial interfaces and transfers data to the PC by means of USB 2.0 controller.
Fig. 2
Fig. 2 Simplified block diagram of the logic implemented into both FPGA devices. Each FPGA receives the 32 pixel outputs (16 by 2 pixels, half of the array) and employs 18 bit counters to measure the light intensity. The exposure time generator gates the counters to perform the measurement during proper exposure times. The pre-processing logic block computes a partial result of the mean intensity and the variance of the measured light, optimizing resources and processing time. Then a processor unit computes the speckle contrast and transfers the result to the PC through the SPI interface.
Fig. 3
Fig. 3 SCOS/DCS probe geometry (a), with laser source fiber (785 nm) placed at 2 cm distance from SPAD array and DCS detector. For the arm cuff occlusion (b) SCOS/DCS probe was placed on the flexor carpi ulnaris muscle of a right arm; For the cerebral blood flow measurement (c) the probe was placed on the frontal bone (frontal eminence) of the left hemisphere of the subject head during voluntary apnea measurement and verbal fluency task.
Fig. 4
Fig. 4 Averaged rBF with the mean standard deviation error for seven subjects during arm cuff occlusion is shown in panel (a). A concordance plot with the concordance correlation coefficient (ρc =0.98) and the Pearson’s correlation coefficient (R=0.96), including the slope (1.14) and the intercept (6.03) of a linear fit are shown in panel (b). The Bland-Altman (difference) plot is shown in panel (c) with a p-value of 0.1, showing that there is no significant difference between the SCOS and the DCS results for the shaded region in panel (a).
Fig. 5
Fig. 5 Embletta result for one representative subject during the whole voluntary apnea protocol. The oxygen saturation (SpO2, left axis, solid line) and the pulse rate (PR, right axis, dotted line) are shown in the top panel. Shaded regions correspond to the 30 s breath-hold period. There is a decrease of the SpO2 after the apnea challenge, and alteration of the PR during the challenge. In the second panel the respiration rate (RR) is shown. In the bottom plot the abdomen and the thorax movement are shown in left (solid line) and right (dotted line) axis respectively. During the breath-hold (shaded region) subject is not breathing (respiration panel), and there is no movement of the thorax and the abdomen (bottom panel).
Fig. 6
Fig. 6 Averaged rCBF over seven subjects with the standard error of the mean computed for all epochs from all seven subjects is shown in panel (a); Concordance plot with Pearson’s correlation coefficient (R=0.95), linear regression fit (the slope (0.9) and the intercept (10.9)), and concordance coefficient (ρc =0.94) are shown in panel (b). The Bland-Altman plot, panel (c) with the p-value of 0.06, showing that there is no significant difference between two techniques for the shaded region in panel (a).
Fig. 7
Fig. 7 Averaged rCBF over three subjects and four letters with the standard deviation of the mean error is shown in panel (a). The concordance correlation coefficient (ρc = 0.80) with Pearson’s R-value (R=0.82) including the slope (0.81) and the intercept (18.3) of the linear regression fit are shown in panel (b). The Bland-Altman plot with the p-value of 0.05, showing that there is no significant difference between the SCOS and the DCS (c) during VTF (shaded region) is shown in panel (c).

Equations (7)

Equations on this page are rendered with MathJax. Learn more.

κ 2 ( r , T ) = σ I 2 ( r , T ) < I ( r , T ) > 2 ,
κ c 2 = σ I C 2 σ S 2 σ D 2 < I C > 2 .
κ 2 ( r , T ) = 2 β T 0 T | g 1 ( r , τ ) | 2 ( 1 τ T ) d τ ,
σ M 2 = < I M 2 > < I M > 2 = i = 0 N M ( I Mi 2 ) N M ( i = 0 N M I Mi ) 2 N M 2
σ D 2 = < I D 2 > < I D > 2 = i = 0 N D ( I Di 2 ) N D ( i = 0 N D I Di ) 2 N D 2 .
σ S 2 = < I M > < I D > = i = 0 N M I Mi N M i = 0 N D I Di N D .
κ 2 = N D 2 ( N M ( i = 0 N M I Mi 2 ) ( i = 0 N M I Mi ) 2 N M ( i = 0 N M I Mi ) ) ( N D i = 0 N M I Mi N M i = 0 N D I Di ) 2 N M 2 ( N D ( i = 0 N D I Di 2 ) ( i = o N D I Di ) 2 N D ( i = 0 N M I Di ) ) ( N D i = 0 N M I Mi N M i = 0 N D I Di ) 2 .

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