Abstract: Method, device, system and associated processing logic for providing optimal perioperative nociception management to anesthetized patient, including monitoring a plurality of nociception-related physiological parameters of the patient using at least two non-invasive physiological sensors; combining the plurality of nociception-related physiological parameters into a nociception index value indicative of a level of nociception of the patient, by applying a machine learning algorithm on the plurality of nociception-related physiological parameters and/or features derived therefrom; comparing the nociception index value to a first threshold value indicative of an upper limit of nociceptive-anti-nociceptive balance (NANB) and to a second threshold value indicative of a lower limit of NANB; and providing a treatment or treatment recommendation based on the comparison and on a clinical concern.

Abstract: Method, device, system and associated processing logic for providing optimal perioperative nociception management to anesthetized patient, including monitoring a plurality of nociception-related physiological parameters of the patient using at least two non-invasive physiological sensors; combining the plurality of nociception-related physiological parameters into a nociception index value indicative of a level of nociception of the patient, by applying a machine learning algorithm on the plurality of nociception-related physiological parameters and/or features derived therefrom; comparing the nociception index value to a first threshold value indicative of an upper limit of nociceptive-anti-nociceptive balance (NANB) and to a second threshold value indicative of a lower limit of NANB; and providing a treatment or treatment recommendation based on the comparison and on a clinical concern.

Abstract: Method, device, system and associated processing logic for providing optimal perioperative nociception management to anesthetized patient, including monitoring a plurality of nociception-related physiological parameters of the patient using at least two non-invasive physiological sensors; combining the plurality of nociception-related physiological parameters into a nociception index value indicative of a level of nociception of the patient, by applying a machine learning algorithm on the plurality of nociception-related physiological parameters and/or features derived therefrom; comparing the nociception index value to a first threshold value indicative of an upper limit of nociceptive-anti-nociceptive balance (NANB) and to a second threshold value indicative of a lower limit of NANB; and providing a treatment or treatment recommendation based on the comparison and on a clinical concern.

Abstract: A finger probe for acquiring physiological signals of a subject, the finger probe including a housing and a body portion, the body portion configured to hold therein the housing in a liquid tight manner, wherein the body portion includes a strap configured to secure the finger probe to the subject's finger, a longitudinal groove configured to accommodate the subject's finger, and a hood configured to cover the distal end of the subject's finger from an opposite side thereof, and wherein the housing includes a Printed Circuit Board, a PPG sensor and at least one additional sensor.

Abstract: A CD metrology system and method of classifying similar structural elements. The method includes: a) obtaining an image of the semiconductor structure; b) identifying sufficient numbers of structural elements belonging to first and second groups of similar structural elements, each group originating from a different manufacturing stage; c) assessing to each given structural element within the sufficient numbers of structural elements belonging to the first and second groups, one or more features indicative of a respective manufacturing stage, wherein values of the respective features are derived from the obtained image and; d) using results of the assessment for a classification decision related to manufacturing stages and, respectively, originating therefrom structural elements in the first and second groups of similar structural elements.

Abstract: A CD metrology system and method of classifying similar structural elements. The method includes: a) obtaining an image of the semiconductor structure; b) identifying sufficient numbers of structural elements belonging to first and second groups of similar structural elements, each group originating from a different manufacturing stage; c) assessing to each given structural element within the sufficient numbers of structural elements belonging to the first and second groups, one or more features indicative of a respective manufacturing stage, wherein values of the respective features are derived from the obtained image and; d) using results of the assessment for a classification decision related to manufacturing stages and, respectively, originating therefrom structural elements in the first and second groups of similar structural elements.