Abstract: Printing system and method for reducing the visibility of gloss differentials having at least one computer-supported inline imaging unit assembly designed to measure specular light reflecting gloss differentials of printed ink. At least one smoothing roller assembly is operationally connected to at least one sheet transport assembly or a smoothing transport subassembly of the sheet transport assembly of the printing system. A smoothing roller assembly is designed to roll at least partly the length and width of at least one printed side of at least one printed sheet disposed along the transport subassembly, pressure generated by the smoothing roller assembly configured to reduce detected gloss differentials from printed ink. At least the outer surface of the at least one smoothing roller assembly is substantially at least one or more of metal and polyurethane.

Abstract: In an embodiment, a method comprises: establishing, by a wireless wearable computer worn by a user, a wireless communication connection with a fitness machine; obtaining machine data from the fitness machine while the user is engaged in a workout session on the fitness machine; obtaining, from a heart rate sensor of the wireless device, heart rate data of the user; determining a calibrated maximal oxygen consumption of the user based on the heart rate data and the machine data; determining a heart rate caloric expenditure based on the heart rate data and the calibrated maximal oxygen consumption of the user; and providing information corresponding to the heart rate caloric expenditure for presentation.

Abstract: In an embodiment, a method comprises: establishing, by a wireless wearable computer worn by a user, a wireless communication connection with a fitness machine; obtaining machine data from the fitness machine while the user is engaged in a workout session on the fitness machine; obtaining, from a heart rate sensor of the wireless device, heart rate data of the user; determining a work rate caloric expenditure by applying a work rate calorie model to the machine data; determining a calibrated maximal oxygen consumption of the user based on the heart rate data and the work rate caloric expenditure; determining a heart rate caloric expenditure by applying a heart rate calorie model to the heart rate data and the calibrated maximal oxygen consumption of the user; and sending to the fitness machine via the communication connection, at least one of the work rate caloric expenditure or the heart rate caloric expenditure.

Abstract: A method of automatically displaying a predetermined set of print attributes of a print job, the method including receiving an image of a first printed sheet, the first printed sheet including one or more at least partial machine-readable codes, the one or more at least partial machine-readable codes encoded with data related to the predetermined set of print attributes, decoding the data from the one or more at least partial machine-readable codes, determining if the data includes all of the print attributes in the predetermined set of print attributes, and if the data includes all of the print attributes in the predetermined set of print attributes, displaying the data using augmented reality (AR) over the first printed sheet.

Abstract: Embodiments are disclosed for estimating caloric expenditure using a heart rate model specific to a motion class. In an embodiment, a method comprises: obtaining acceleration and rotation rate from motion sensors of a wearable device; determining a vertical component of inertial acceleration and a vertical component of rotational acceleration from the acceleration and rotation rate, respectively; determining a magnitude of the rotation rate; determining a correlation between the inertial vertical acceleration component and rotational acceleration; determining a percentage of motion outside a dominant plane of motion; predicting a motion class based on a motion classification model that takes as input the motions, correlation and percentage; determining a likelihood the user is walking; in accordance with determining that the user is likely not walking, configuring a heart rate model based on the predicted motion class; and estimating, using the configured heart rate model, a caloric expenditure of the user.

Abstract: A method of analyzing decurling settings for a print request including a plurality of sheets, the method including receiving a real image of a first portion of the plurality of sheets, receiving a first input, displaying one or more decurler settings, and displaying a first augmented image of a stack of the plurality of sheets.

Abstract: A method of analyzing decurling settings for a print request including a plurality of sheets, the method including receiving a real image of a first portion of the plurality of sheets, receiving a first input, displaying one or more decurler settings, and displaying a first augmented image of a stack of the plurality of sheets.

Abstract: Embodiments of the present disclosure provide systems and methods for monitoring a patient to produce a signal representing a blood oxygen concentration. The signal may be analyzed to determine the presence of one or more sleep apnea events, and an integral of the signal may be calculated if the signal is outside of a set range or threshold. A practitioner may choose to be informed of the presence of sleep apnea events if the blood oxygen concentration is less then a preset limit, if an upper limit has been reached for an integral representing the severity of the oxygen deprivation over time, or anytime sleep apnea events may be present in the signal.

Abstract: Embodiments are disclosed for estimating caloric expenditure based on center of mass motion and heart rate. In an embodiment, a method comprises: obtaining acceleration and rotation rate of a wearable device worn on a limb of a user; transforming the acceleration and rotation rate into an inertial frame; determining a vertical component of acceleration, rotation rate magnitude and vertical component of rotational acceleration due to limb rotation; determining a work rate (WR) based caloric expenditure based on the vertical component of acceleration, rotation rate magnitude and a correlation coefficient that measures a correlation between the vertical component of acceleration and the vertical component of rotational acceleration; obtaining heart rate (HR) data from a heart rate sensor of the wearable device; determining an HR based caloric expenditure based on the HR data; and fusing, the WR based caloric expenditure with the HR based caloric expenditure to get a fused caloric expenditure.

Abstract: Embodiments are disclosed for estimating caloric expenditure using a heart rate model specific to a motion class. In an embodiment, a method comprises: obtaining acceleration and rotation rate from motion sensors of a wearable device; determining a vertical component of inertial acceleration and a vertical component of rotational acceleration from the acceleration and rotation rate, respectively; determining a magnitude of the rotation rate; determining a correlation between the inertial vertical acceleration component and rotational acceleration; determining a percentage of motion outside a dominant plane of motion; predicting a motion class based on a motion classification model that takes as input the motions, correlation and percentage; determining a likelihood the user is walking; in accordance with determining that the user is likely not walking, configuring a heart rate model based on the predicted motion class; and estimating, using the configured heart rate model, a caloric expenditure of the user.

Abstract: In an embodiment, a method comprises: establishing, by a wireless wearable computer worn by a user, a wireless communication connection with a fitness machine; obtaining machine data from the fitness machine while the user is engaged in a workout session on the fitness machine; obtaining, from a heart rate sensor of the wireless device, heart rate data of the user; determining a work rate caloric expenditure by applying a work rate calorie model to the machine data; determining a calibrated maximal oxygen consumption of the user based on the heart rate data and the work rate caloric expenditure; determining a heart rate caloric expenditure by applying a heart rate calorie model to the heart rate data and the calibrated maximal oxygen consumption of the user; and sending to the fitness machine via the communication connection, at least one of the work rate caloric expenditure or the heart rate caloric expenditure.

Abstract: Embodiments are disclosed for a wireless wearable computer with fitness machine connectivity for improved activity monitoring using caloric expenditure models.

Abstract: Systems and methods are provided for determining respiration information from physiological signals such as PPG signals. A physiological signal is processed to generate at least one respiration information signal and an autocorrelation sequence is generated based on the at least one respiration information signal. In some embodiments, a respiration peak is identified based on the autocorrelation sequence and a composite peak is generated based on the identified peak and at least one previous respiration peak. Respiration information is calculated based on the composite peak. In some embodiments, a determination is made whether the autocorrelation sequence includes an undesired harmonic. When the autocorrelation sequence includes an undesired harmonic, the autocorrelation sequence may not be used in the calculation of respiration information.

Abstract: A patient monitoring system may receive a physiological signal such as a photoplethysmograph (PPG) signal that exhibits frequency and amplitude modulation based on respiration. A phase locked loop may generate a frequency demodulated signal and an amplitude demodulated signal from the PPG signal. An autocorrelation sequence may be generated for each of the frequency demodulated signal and the amplitude demodulated signal. The autocorrelation sequences may be combined and respiration information may be determined based on the combined autocorrelation sequence.

Abstract: Embodiments are disclosed for a wireless wearable computer with fitness machine connectivity for improved activity monitoring using caloric expenditure models.

Abstract: Embodiments of the present disclosure provide systems and methods for monitoring a patient to produce a signal representing a blood oxygen concentration. The signal may be analyzed to determine the presence of one or more sleep apnea events, and an integral of the signal may be calculated if the signal is outside of a set range or threshold. A practitioner may choose to be informed of the presence of sleep apnea events if the blood oxygen concentration is less then a preset limit, if an upper limit has been reached for an integral representing the severity of the oxygen deprivation over time, or anytime sleep apnea events may be present in the signal.

Abstract: Embodiments of the present disclosure provide systems and methods for monitoring a patient to produce a signal representing a blood oxygen concentration. The signal may be analyzed to determine the presence of one or more sleep apnea events, and an integral of the signal may be calculated if the signal is outside of a set range or threshold. A practitioner may choose to be informed of the presence of sleep apnea events if the blood oxygen concentration is less then a preset limit, if an upper limit has been reached for an integral representing the severity of the oxygen deprivation over time, or anytime sleep apnea events may be present in the signal.

Abstract: Systems and methods are provided for detecting held breath events. A physiological signal, such as a photoplethysmograph (PPG) signal, is processed to extract respiration-related morphology metric signals. The morphology signals are analyzed to determine when a patient's breath is being held.

Abstract: Systems and methods are provided for determining respiration information from physiological signals such as PPG signals. A physiological signal is processed to generate at least one respiration information signal and an autocorrelation sequence is generated based on the at least one respiration information signal. In some embodiments, a respiration peak is identified based on the autocorrelation sequence and a composite peak is generated based on the identified peak and at least one previous respiration peak. Respiration information is calculated based on the composite peak. In some embodiments, a determination is made whether the autocorrelation sequence includes an undesired harmonic. When the autocorrelation sequence includes an undesired harmonic, the autocorrelation sequence may not be used in the calculation of respiration information.

Abstract: Systems and methods are provided for determining respiration information from physiological signals such as PPG signals. A physiological signal is processed to generate at least one respiration information signal and an autocorrelation sequence is generated based on the at least one respiration information signal. In some embodiments, a respiration peak is identified based on the autocorrelation sequence and a composite peak is generated based on the identified peak and at least one previous respiration peak. Respiration information is calculated based on the composite peak. In some embodiments, a determination is made whether the autocorrelation sequence includes an undesired harmonic. When the autocorrelation sequence includes an undesired harmonic, the autocorrelation sequence may not be used in the calculation of respiration information.