Angelo Sassaroli

Multichannel time-resolved optical tomographic imaging system

A time-resolved optical imaging system using near-infrared light has been developed. The system had three pulsed light sources and total 64 channels of detection, working simultaneously for acquisition of the time-resolved data of the pulsed light transmitted through scattering media like biological tissues. The light sources were provided by high power picosecond pulsed diode lasers, and optical switches directed one of the light sources to the object through an optical fiber. The light signals reemitted from the surface of the object were collected by optical fibers, and transmitted to a time-resolved detecting system. Each of the detecting channels consisted of an optical attenuator, a fast photomultiplier, and a time-correlated single photon counting circuit which contained a miniaturized constant fraction discriminator/time-to-amplitude converter module, and a signal acquisition unit with an A/D converter. The performance and potentiality of the imaging system have been examined by the image reconstr...

Comment on the modified Beer?Lambert law for scattering media

We present a concise overview of the modified Beer-Lambert law, which has been extensively used in the literature of near-infrared spectroscopy (NIRS) of scattering media. In particular, we discuss one form of the modified Beer-Lambert law that is commonly found in the literature and that is not strictly correct. However, this incorrect form of the modified Beer-Lambert law still leads to the correct expression for the changes in the continuous wave optical signal associated with changes in the absorption coefficient of the investigated medium. Here we propose a notation for the modified Beer-Lambert law that keeps the typical form commonly found in the literature without introducing any incorrect assumptions.

Brain measurement for usability testing and adaptive interfaces: an example of uncovering syntactic workload with functional near infrared spectroscopy

A well designed user interface (UI) should be transparent, allowing users to focus their mental workload on the task at hand. We hypothesize that the overall mental workload required to perform a task using a computer system is composed of a portion attributable to the difficulty of the underlying task plus a portion attributable to the complexity of operating the user interface. In this regard, we follow Shneidermans theory of syntactic and semantic components of a UI. We present an experiment protocol that can be used to measure the workload experienced by users in their various cognitive resources while working with a computer. We then describe an experiment where we used the protocol to quantify the syntactic workload of two user interfaces. We use functional near infrared spectroscopy, a new brain imaging technology that is beginning to be used in HCI. We also discuss extensions of our techniques to adaptive interfaces.

MONTE CARLO PROCEDURE FOR INVESTIGATING LIGHT PROPAGATION AND IMAGING OF HIGHLY SCATTERING MEDIA

A Monte Carlo procedure has been developed to study photon migration through highly scattering nonhomogeneous media. When two scaling relationships are used, the temporal response when scattering or absorbing inhomogeneities are introduced can be evaluated in a short time from the results of only one simulation carried out for the homogeneous medium. Examples of applications to the imaging of defects embedded into a diffusing slab, a model usually used for optical mammography, are given. Comparisons with experimental results show the correctness of the results obtained.

Using fNIRS brain sensing in realistic HCI settings: experiments and guidelines

Because functional near-infrared spectroscopy (fNIRS) eases many of the restrictions of other brain sensors, it has potential to open up new possibilities for HCI research. From our experience using fNIRS technology for HCI, we identify several considerations and provide guidelines for using fNIRS in realistic HCI laboratory settings. We empirically examine whether typical human behavior (e.g. head and facial movement) or computer interaction (e.g. keyboard and mouse usage) interfere with brain measurement using fNIRS. Based on the results of our study, we establish which physical behaviors inherent in computer usage interfere with accurate fNIRS sensing of cognitive state information, which can be corrected in data analysis, and which are acceptable. With these findings, we hope to facilitate further adoption of fNIRS brain sensing technology in HCI research.

Implantable, multifunctional, bioresorbable optics

Advances in personalized medicine are symbiotic with the development of novel technologies for biomedical devices. We present an approach that combines enhanced imaging of malignancies, therapeutics, and feedback about therapeutics in a single implantable, biocompatible, and resorbable device. This confluence of form and function is accomplished by capitalizing on the unique properties of silk proteins as a mechanically robust, biocompatible, optically clear biomaterial matrix that can house, stabilize, and retain the function of therapeutic components. By developing a form of high-quality microstructured optical elements, improved imaging of malignancies and of treatment monitoring can be achieved. The results demonstrate a unique family of devices for in vitro and in vivo use that provide functional biomaterials with built-in optical signal and contrast enhancement, demonstrated here with simultaneous drug delivery and feedback about drug delivery with no adverse biological effects, all while slowly degrading to regenerate native tissue.

Brainput: enhancing interactive systems with streaming fnirs brain input

This paper describes the Brainput system, which learns to identify brain activity patterns occurring during multitasking. It provides a continuous, supplemental input stream to an interactive human-robot system, which uses this information to modify its behavior to better support multitasking. This paper demonstrates that we can use non-invasive methods to detect signals coming from the brain that users naturally and effortlessly generate while using a computer system. If used with care, this additional information can lead to systems that respond appropriately to changes in the users state. Our experimental study shows that Brainput significantly improves several performance metrics, as well as the subjective NASA-Task Load Index scores in a dual-task human-robot activity.

Optical measurements of absorption changes in two-layered diffusive media

We have used Monte Carlo simulations for a two-layered diffusive medium to investigate the effect of a superficial layer on the measurement of absorption variations from optical diffuse reflectance data processed by using: (a) a multidistance, frequency-domain method based on diffusion theory for a semi-infinite homogeneous medium; (b) a differential-pathlength-factor method based on a modified Lambert-Beer law for a homogeneous medium and (c) a two-distance, partial-pathlength method based on a modified Lambert-Beer law for a two-layered medium. Methods (a) and (b) lead to a single value for the absorption variation, whereas method (c) yields absorption variations for each layer. In the simulations, the optical coefficients of the medium were representative of those of biological tissue in the near-infrared. The thickness of the first layer was in the range 0.3-1.4 cm, and the source-detector distances were in the range 1-5 cm, which is typical of near-infrared diffuse reflectance measurements in tissue. The simulations have shown that (1) method (a) is mostly sensitive to absorption changes in the underlying layer, provided that the thickness of the superficial layer is approximately 0.6 cm or less; (2) method (b) is significantly affected by absorption changes in the superficial layer and (3) method (c) yields the absorption changes for both layers with a relatively good accuracy of approximately 4% for the superficial layer and approximately 10% for the underlying layer (provided that the absorption changes are less than 20-30% of the baseline value). We have applied all three methods of data analysis to near-infrared data collected on the forehead of a human subject during electroconvulsive therapy. Our results suggest that the multidistance method (a) and the two-distance partial-pathlength method (c) may better decouple the contributions to the optical signals that originate in deeper tissue (brain) from those that originate in more superficial tissue layers.

DISCRIMINATION OF MENTAL WORKLOAD LEVELS IN HUMAN SUBJECTS WITH FUNCTIONAL NEAR-INFRARED SPECTROSCOPY

We have applied functional near-infrared spectroscopy (fNIRS) to the human forehead to distinguish different levels of mental workload on the basis of hemodynamic changes occurring in the prefrontal cortex. We report data on 3 subjects from a protocol involving 3 mental workload levels based on to working memory tasks. To quantify the potential of fNIRS for mental workload discrimination, we have applied a 3-nearest neighbor classification algorithm based on the amplitude of oxyhemoglobin (HbO2) and deoxyhemoglobin (HbR) concentration changes associated with the working memory tasks. We have found classification success rates in the range of 44%–72%, which are significantly higher than the corresponding chance level (for random data) of 19.1%. This work shows the potential of fNIRS for mental workload classification, especially when more parameters (rather than just the amplitude of concentration changes used here) and more sophisticated classification algorithms (rather than the simple 3-nearest neighbor algorithm used here) are considered and optimized for this application.

Near-Infrared Optical Mammography for Breast Cancer Detection with Intrinsic Contrast

Optical methods to detect breast cancer on the basis of its increased opacity have been explored for some time. These methods have matured to a point in which they are capable of quantifying the optical properties of breast tissue and translating them into measures of concentrations of relevant tissue components. In particular, near-infrared spectroscopy has been employed to determine the concentrations of hemoglobin, water, and lipids, as well as oxygen saturation of hemoglobin and optical scattering properties in normal and cancerous breast tissue. Dynamic optical measurements can also identify abnormal hemodynamic patterns associated with breast cancer. We review, in this article, a number of results in the field, which show that cancerous tissue is associated with higher hemoglobin and water concentrations, and a lower lipid concentration with respect to normal breast tissue. Indications that breast cancers are characterized by lower hemoglobin saturation and stronger scattering decay as a function of wavelength are less robust, with variable results reported in the literature. Intrinsic sources of optical contrast associated with breast cancer can also be used to monitor individual response to neoadjuvant therapy.