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: One aspect of this disclosure involves a wearable device that includes a frame that is worn on a user's head, and an inward-facing camera (camera) physically coupled to the frame. The optical axis of the camera is either above the Frankfort horizontal plane and pointed upward to capture an image of a region of interest (ROI) above the user's eyes, or the optical axis is below the Frankfort horizontal plane and pointed downward to capture an image of an ROI below the user's eyes. The camera includes a sensor and a lens. The sensor plane is tilted by more than 2° relative to the lens plane according to the Scheimpflug principle in order to capture a sharper image. The Scheimpflug principle is a geometric rule that describes the orientation of the plane of focus of a camera when the lens plane is tilted relative to the sensor plane.

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: 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 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 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: 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: 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.

Abstract: Described herein are systems and methods for personalized detection of an allergic reaction 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 the nose (THN) of a user. The computer generates feature values based on THN and utilizes a model to detect an allergic reaction of the user based on the feature values. The model is trained based on previous THN of the user taken during different days. Some embodiments may utilize additional thermal cameras that take thermal measurements of other regions on the face, which may be utilized by the computer to generate additional feature values that are used to detect the allergic reaction. In some cases, detection of the allergic reaction may occur following a rise in nasal temperature, even before the user becomes aware of the allergic reaction.

Abstract: A wearable system configured to collect thermal measurements related to respiration. The system includes a frame configured to be worn on a user's head, and at least one non-contact thermal camera (e.g., thermopile or microbolometer based sensor). The thermal camera is small and lightweight, physically coupled to the frame, located close to the user's face, does not occlude any of the user's mouth and nostrils, and is configured to take thermal measurements of: a portion of the right side of the user's upper lip, a portion of the left side of the user's upper lip, and a portion of the user's mouth. The thermal measurements are forwarded to a computer that calculates breathing related parameters, such as breathing rate, an extent to which the breathing was done through the mouth, an extent to which the breathing was done through the nostrils, and ratio between exhaling and inhaling durations.

Abstract: Thermal measurements of the forehead can be indicative of brain activity, and as such, may be useful for conducting brain-related treatments, such as neurofeedback. In one embodiment, a system for conducting a neurofeedback session includes an inward-facing head-mounted thermal camera (CAM) and a user interface. CAM takes thermal measurements of a region on the forehead (THF) of a user, and is located below the middle of the region. The user interface provides, based on THF, the neurofeedback session for the user. Optionally, a computer controls the neurofeedback session by providing the user feedback via the user interface. The computer may generate the feedback based on the similarity between a current THF pattern and a previous THF pattern of the user taken while the user was in a target state.