Abstract: The present invention relates to a device, system and method for automatic and unobtrusive caloric intake detection. The device comprises a respiration input for obtaining a respiration signal indicating the subject's respiration, and an analysis unit for analyzing the obtained respiration signal in the frequency domain by determining one or more respiration signal features from the obtained respiration signal in the frequency domain related to changes in oxidation and by detecting changes of the one or more determined respiration signal features to detect periods of caloric intake by the subject.

Abstract: A system for detecting sleep apnea uses a PPG sensor for generating a PPG signal. An estimate of respiratory effort is derived from the PPG signal, and from this a respiratory effort signal is derived. Characteristic features are extracted from the respiratory effort signal, and sleep disordered breathing events are detected from the extracted characteristic features. This analysis can distinguish between sleep disordered breathing events and normal breathing during sleep.

Abstract: The present invention relates to a device for accurately estimating the energy expenditure of a person, in particular by which the effect of cardiovascular drift is taken into account. The device comprises an input unit (10) for obtaining a movement signal (13) representing physical activity of the person and a heart rate signal (15) representing the heart rate of the person, a cardiovascular drift determination unit (16) for determining cardiovascular drift phases (17) from said movement signal (13) and either said heart rate signal (15) and/or one or more cardiovascular drift related signals (23) carrying information on one or more of amount of sweat, weight loss, temperature rise, blood lactate concentration and physical fatigue of the person, a correction unit (18) for correcting the heart rate signal (15) generated and representing the heart rate during a cardiovascular drift phase, and an estimation unit (20) for estimating the energy expenditure of the person from the corrected heart rate signal (19).

Abstract: A system for detecting sleep apnea uses a PPG sensor for generating a PPG signal. An estimate of respiratory effort is derived from the PPG signal, and from this a respiratory effort signal is derived. Characteristic features are extracted from the respiratory effort signal, and sleep disordered breathing events are detected from the extracted characteristic features. This analysis can distinguish between sleep disordered breathing events and normal breathing during sleep.

Abstract: The present invention relates to distinguishing different sedentary states of a subject. A sedentary state can refer to standing, sitting and/or lying. An apparatus for determining a sedentary state of a subject is presented that comprises a sensor interface for obtaining a movement signal indicative of a movement of the subject; an extraction unit for extracting a signal feature indicative of postural control oscillations of the subject from the movement signal, wherein the signal feature indicative of postural control oscillations is indicative of center of mass motion oscillations for preventing the subject from falling; and a classifier for classifying a sedentary state of the subject based on the signal feature indicative of postural control oscillations of the subject. Further, a corresponding method, computer program and system are presented.

Abstract: Method and apparatus for monitoring a subject There is provided a method of monitoring a subject, the method comprising obtaining measurements of a physiological characteristic of the subject over a period of time; obtaining information on a desired trend for the physiological characteristic of the subject; analysing the measurements of the physiological characteristic in a first time interval to determine a global trend having a global upper trend line for the physiological characteristic based on maxima in the measurements in the first time interval and a global lower trend line for the physiological characteristic based on minima in the measurements in the first time interval; analysing the measurements of the physiological characteristic in a second time interval to determine a local trend for the physiological characteristic, wherein the second time interval is shorter than the first time interval; determining whether feedback to the subject is required based on the global trend, the local trend and the

Abstract: Presented are concepts for monitoring the liquid or food consumption of a person. Once such concept employs the step of detecting a change in weight of the person resultant from usage of a toilet. A value representative of at least one of liquid consumption and food consumption of the person may then be determined based on the detected change in weight of the person.

Abstract: There is provided an apparatus for monitoring the ingestion of food and/or drink by a subject, the apparatus comprising a control unit that comprises a first obtaining module configured to obtain measurements of one or more physiological characteristics of the subject; a second obtaining module configured to obtain measurements of eddy currents generated in the body of the subject by an externally-applied magnetic field; a setting module configured to set a respective cut-off frequency for one or more filtering stages based on a respective frequency for each of said one or more physiological characteristics; a filtering module configured to filter the measurements of eddy currents using the one or more filtering stages to remove signal components due to the one or more physiological characteristics; and a processing module configured to process the filtered measurements to determine whether food and/or drink is present in the stomach of the subject.

Abstract: Methods and systems for assessing cardio-respiratory fitness (CRF) with the use of body motion data is disclosed. Specific measurements of body movement (for example, motion amplitude or velocity, or distance covered during repetitive displacement) are dependent on a user's fitness level. Embodiments prompt the user to execute a simple set of periodic movements which can be used to estimate cardiovascular function (e.g., VO2max). Body motion data, such as activity count, accelerometer signals, or cadence of motion, is captured and analyzed to estimate the user's fitness. The combination of body motion data with various physical measurements (e.g. body weight, height, BMI) permits the method to predict the user's VO2max or similar physical fitness parameters.

Abstract: A system, method and corresponding computer program for quantifying physical fatigue are provided, the system comprising: a physiological measure providing unit (20) for providing a physiological measure of the subject, a fatigue index determination unit (200) for determining a fatigue index of the subject. The fatigue index determination unit (200) comprises a first fatigue index determination subunit (210) for determining a first fatigue index based on the physiological measure and a second fatigue index determination subunit (240) for determining a second fatigue index based on the physiological measure. The first fatigue index and the second fatigue index have a respectively different characteristic based on the physiological measure. The system, method and corresponding computer program improve the quantifying of physical fatigue of a subject.

Abstract: The present invention relates to a device, system and method for automatic and unobtrusive caloric intake detection. The device comprises a respiration input for obtaining a respiration signal indicating the subject's respiration, and an analysis unit for analyzing the obtained respiration signal in the frequency domain by determining one or more respiration signal features from the obtained respiration signal in the frequency domain related to changes in oxidation and by detecting changes of the one or more determined respiration signal features to detect periods of caloric intake by the subject.

Abstract: There is provided an apparatus for monitoring the ingestion of food and/or drink by a subject, the apparatus comprising a control unit that comprises a first obtaining module configured to obtain measurements of one or more physiological characteristics of the subject; a second obtaining module configured to obtain measurements of eddy currents generated in the body of the subject by an externally-applied magnetic field; a setting module configured to set a respective cut-off frequency for one or more filtering stages based on a respective frequency for each of said one or more physiological characteristics; a filtering module configured to filter the measurements of eddy currents using the one or more filtering stages to remove signal components due to the one or more physiological characteristics; and a processing module configured to process the filtered measurements to determine whether food and/or drink is present in the stomach of the subject.

Abstract: The present invention relates to a device for accurately estimating the energy expenditure of a person, in particular by which the effect of cardiovascular drift is taken into account. The device comprises an input unit (10) for obtaining a movement signal (13) representing physical activity of the person and a heart rate signal (15) representing the heart rate of the person, a cardiovascular drift determination unit (16) for determining cardiovascular drift phases (17) from said movement signal (13) and either said heart rate signal (15) and/or one or more cardiovascular drift related signals (23) carrying information on one or more of amount of sweat, weight loss, temperature rise, blood lactate concentration and physical fatigue of the person, a correction unit (18) for correcting the heart rate signal (15) generated and representing the heart rate during a cardiovascular drift phase, and an estimation unit (20) for estimating the energy expenditure of the person from the corrected heart rate signal (19).

Abstract: The present invention relates to distinguishing different sedentary states of a subject. A sedentary state can refer to standing, sitting and/or lying. An apparatus for determining a sedentary state of a subject is presented that comprises a sensor interface for obtaining a movement signal indicative of a movement of the subject; an extraction unit for extracting a signal feature indicative of postural control oscillations of the subject from the movement signal, wherein the signal feature indicative of postural control oscillations is indicative of center of mass motion oscillations for preventing the subject from falling; and a classifier for classifying a sedentary state of the subject based on the signal feature indicative of postural control oscillations of the subject. Further, a corresponding method, computer program and system are presented.

Abstract: Presented are concepts for monitoring the liquid or food consumption of a person. Once such concept employs the step of detecting a change in weight of the person resultant from usage of a toilet. A value representative of at least one of liquid consumption and food consumption of the person may then be determined based on the detected change in weight of the person.

Abstract: Apparatus and methods to monitor changes in user weight. The apparatus includes at least one sensor configured to capture superquotidien measurements of the user's weight and an accelerometer to measure movements of the user, and estimates cumulative weight of the user based on the superquotidien measurements, wherein only sudden changes in the user's weight are used in the estimation. The sensor(s) can be located, e.g., within a shoe insole, within a chair, within a floor, etc.

Abstract: Methods and systems for assessing cardio-respiratory fitness (CRF) with the use of body motion data is disclosed. Specific measurements of body movement (for example, motion amplitude or velocity, or distance covered during repetitive displacement) are dependent on a user's fitness level. Embodiments prompt the user to execute a simple set of periodic movements which can be used to estimate cardiovascular function (e.g., VO2max). Body motion data, such as activity count, accelerometer signals, or cadence of motion, is captured and analyzed to estimate the user's fitness. The combination of body motion data with various physical measurements (e.g. body weight, height, BMI) permits the method to predict the user's VO2max or similar physical fitness parameters.