Abstract: Described herein are embodiments of a system and a method to calculate a user's physiological signal, such as blood pressure, cardiac output, or tissue perfusion. The system includes a head-mounted device configured to measure photoplethysmographic signal (PPG signal) at a region on the user's head, and a head-mounted camera configured to capture images indicative of the user's posture. Additionally, the system includes a computer configured to calculate the physiological signal based on the PPG signal and the user's posture. In some embodiments, the computer adjusts calculations of the physiological signal based on the user's posture, such that for the same PPG signal the computer outputs different values for the physiological signal for the following different postures: standing, sitting, and lying down.

Abstract: Some aspects of this disclosure involve ranking types of food based on measurements of affective response of users who consumed the types of food. In one embodiment, a system that ranks types of food includes sensors that take measurements of affective response of users and a computer. The computer receives indications of times at which the users consumed the types of food and selects for each type of food, based on the indications, measurements of at least five of the users taken up to four hours after consuming the type of food. The computer ranks the types of food based on the selected measurements. Optionally, each of the types of food is a different item on a menu comprising food items.

Abstract: A head mounted system (HMS) configured to collect facial expressions of the user wearing the HMS. The HMS includes a frame and at least four cameras coupled to the frame. First and second cameras capture the user's right and left eyebrows, and third and fourth cameras capture the right and left sides of the user's upper lip. An optional computer utilizes the images captured by the cameras to detect facial expressions, microexpressions, and/or to improve the user's emotional awareness.

Abstract: A system for detecting blood pressure based on imaging photoplethysmography (iPPG) includes a first inward-facing head-mounted camera to capture images of a first region of interest located on the face below the eyes and above the lips (IMROI1) of a user, and a second inward-facing head-mounted camera to capture images of a second region of interest comprising a portion of a temple and/or forehead (IMROI2) of the user. The system further includes a computer to calculate a blood pressure value for the user based on first and second photoplethysmographic signals recognizable in IMROI1 and IMROI2.

Abstract: A system for detecting blood pressure based on imaging photoplethysmography (iPPG) includes an inward-facing head-mounted camera to capture images of a first region of interest (IMROI1) that comprises a portion of exposed skin of the user's face, and an outward-facing head-mounted camera to capture images of a second region of interest (IMROI2) that comprises exposed skin on a hand of the user. The head-mounted cameras may be coupled to a frame of eyeglasses or smartglasses, and the system further includes a computer to calculate a blood pressure value for the user based on first and second photoplethysmographic signals recognizable in IMROI1 and IMROI2.

Abstract: A system for detecting blood pressure based on imaging photoplethysmography (iPPG) includes a first inward-facing head-mounted camera to capture images of a first region of interest located on the face below the eyes and above the lips (IMROI1) of a user, and a second inward-facing head-mounted camera to capture images of a second region of interest comprising a portion of a temple and/or forehead (IMROI2) of the user. The system further includes a computer to calculate a blood pressure value for the user based on first and second photoplethysmographic signals recognizable in IMROI1 and IMROI2.

Abstract: A system for detecting blood pressure based on imaging photoplethysmography (iPPG) includes an inward-facing head-mounted camera to capture images of a first region of interest (IMROI1) that comprises a portion of exposed skin of the user's face, and an outward-facing head-mounted camera to capture images of a second region of interest (IMROI2) that comprises exposed skin on a hand of the user. The head-mounted cameras may be coupled to a frame of eyeglasses or smartglasses, and the system further includes a computer to calculate a blood pressure value for the user based on first and second photoplethysmographic signals recognizable in IMROI1 and IMROI2.

Abstract: Described herein are systems and methods for detecting a stress level of a user. In one embodiment, a system includes an inward-facing head-mounted thermal camera (CAM) and a computer. CAM takes thermal measurements of a region on a periorbital area (THROI1) of the user. The computer generates feature values based on THROI1, and utilizes a model to detect the stress level based on the feature values. The model was trained based on: previous THROI1 taken while the user was under elevated stress, and other previous THROI1 taken while the user was not under elevated stress. Some embodiments may utilize additional thermal cameras that take thermal measurements of other regions on the face, which may be utilized to detect the stress level.

Abstract: Some aspects of this disclosure include systems, methods, and/or computer programs that may be used to determine a cause of an inaccuracy in predicted affective response to an event that involves a user who has an experience. Some embodiments described herein involve identifying when a difference between a measurement of affective response corresponding to an event is different from the predicted affective response corresponding to the event. When such a discrepancy is identified, a presentation is made to the user of at least one of the following: one or more factors characterizing the event, and effects of the one or more factors on the user, as determined based on a model of the user. Based on a comment made by the user in response to the presentation, at least one of the following is identified: a discrepancy in a description of the event, and an inaccuracy in the model.

Abstract: Described herein are systems, methods and computer-readable media for recommending a repeated experience. One embodiment includes collecting a subset of the measurements that includes measurements of at least five of the users who had an experience; each measurement of a user is associated with a value indicative of an extent to which the user had previously experienced the experience. Calculating parameters of a function based on the measurements in the subset and their associated values, where the function describes, for different extents to which the experience had been previously experienced, an expected affective response to experiencing the experience again. And responsive to determining that an expected affective response to experiencing the experience again after having experiencing it for at least a certain extent reaches a threshold, recommending the experience.

Abstract: Described herein are embodiments of systems, method, and computer programs for recommending an experience to a user. In one embodiment, a sensor takes measurements of affective response of the user while the user is exposed to token instances that are instantiations of visual tokens. An eye tracker measures the gaze of the user while the user is exposed to the token instances. A computer calculates, based on the measurements of affective response and measurements of the gaze, values of expected affective response of the user to exposure to instantiations of the visual tokens. These values are utilized to select an experience for the user, such that based on the values, an expected affective response of the user to exposure to token instances corresponding to the selected experience is more positive than an expected affective response of the user to exposure to token instances corresponding to other experiences.

Abstract: Described herein are systems and methods for detecting a physiological response based on facial skin color changes (FSCC) recognizable in images taken with an inward-facing head-mounted visible-light camera (VCAMin). Some examples of physiological responses whose manifestation involves FSCC include emotional responses (which at times may be hidden to the naked eye), and physiological signals such as a heart rate, heart rate variability, and/or a breathing rate. In one embodiment, a system that detects a physiological response based on FSCC includes VCAMin that takes images of a region of interest (IMROI) on a user's face, which is illuminated by ambient light, and a computer that detects the physiological response based on FSCC recognizable in IMROI. Optionally, the system includes an outward-facing head-mounted visible-light camera (VCAMout) that takes images of the environment (IMENV), and the computer detects the physiological response also based on IMENV.

Abstract: Disclosed herein are embodiments of a system that utilizes measurements indicative of respiration in order to estimate an aerobic activity parameter, such as oxygen consumption (VO2), maximal oxygen consumption (VO2 max), or energy expenditure (EE). In one embodiment, this system includes at least one inward-facing head-mounted thermal camera (CAM) and a computer. Each CAM, from among the at least one CAM, is configured to take thermal measurements of a region below the nostrils (THRBN) of a user. THRBN are indicative of an exhale stream of the user, such as an exhale stream from one, or both, of the nostrils and/or the exhale from the mouth. The computer calculates, based on THRBN, the aerobic activity parameter. Optionally, the computer generates feature values based on data comprising THRBN and utilizes a model to calculate the aerobic activity parameter based on the feature values.

Abstract: Disclosed herein are embodiments of an athletic coaching system that includes at least one inward-facing head-mounted thermal camera (CAM) and a computer. Each CAM from among the at least one CAM is configured to take thermal measurements of a region below the nostrils (denoted THRBN) of a user. THRBN are indicative of an exhale stream of the user (e.g., an exhale stream from a nostril and/or from the mouth). The computer is configured to: receive measurements of movements (Mmove) involving the user; generate, based on THRBN and Mmove, a coaching indication; and present, via a user interface, the coaching indication to the user. In one example, the coaching indication is indicative of a change the user should make to one or more of the following: cadence of movements, stride length, breathing rate, breathing type (mouth or nasal), and duration of exhales.

Abstract: This disclosure describes systems, methods, and computer program products that may be used to provide crowd-based scores for experiences, which are computed based on measurements of affective response of multiple users who had the experiences. The measurements of affective response may be collected using a wide array of sensors that measure physiological signals and/or behavioral cues. Additionally, the scores may be personalized for a certain user based on similarities between a profile of the certain user and profiles of the multiple users.

Abstract: A head mounted system (HMS) configured to collect facial expressions of the user wearing the HMS. The HMS includes a frame and at least four cameras coupled to the frame. First and second cameras capture the user's right and left eyebrows, and third and fourth cameras capture the right and left sides of the user's upper lip. An optional computer utilizes the images captured by the cameras to detect facial expressions, microexpressions, and/or to improve the user's emotional awareness.

Abstract: System and method for estimating posture of a user based on a model and images captured by at least two head-mounted cameras that are worn by the user and are oriented downward such that portions of the user's torso are in the respective fields of view of the cameras when the user stands up straight.

Abstract: A system that detects an irregular physiological response while being exposed to sensitive data includes: a head-mounted display (HMD), an inward-facing head-mounted thermal camera (CAM), and a computer. The HMD exposes sensitive data to the user who wears the HMD. The CAM takes thermal measurements of a region of interest (THROI) on the user's face while the user is exposed to the sensitive data. And the computer detects, based on certain THROI taken while the user was exposed to certain sensitive data, whether the user experienced the irregular physiological response while being exposed to the certain sensitive data.

Abstract: System and method that identify atypical behavior of a user. One embodiment of the system includes an eye tracker to perform tracking of a user's gaze while viewing items, an inward-facing head-mounted thermal camera to take thermal measurements of a region of interest on the face (THROI) of the user, and a computer. The computer generates feature values based on THROI and the tracking, and utilizes a model to identify atypical behavior of the user based on the feature values. The model may be trained based on previous tracking and previous THROI of the user, taken while viewing other items.

Abstract: Described herein are systems and methods for detecting a physiological response based on thermal measurements while accounting for effects of the environment. In one embodiment, a system includes an inward-facing head-mounted thermal camera (CAMin) that takes thermal measurements of a region of interest (THROI) on a user's face, and an outward-facing head-mounted thermal camera (CAMout) that takes thermal measurements of the environment (THENV). CAMin does not occlude the region of interest, and the system further includes a computer that detects the physiological response based on THROI and THENV. Optionally, the computer generates feature values based on sets of THROI and THENV, and utilizes a machine learning-based model to detect, based on the feature values, the physiological response.