Abstract: According to an aspect, there is provided a computer-implemented method for analyzing a pulse wave signal, PWS, obtained from a subject. The PWS comprises pulse wave measurements for one or more cardiac cycles of the subject during a first time period. The method comprises (i) determining (101) 1PWS as a first derivative with respect to time of the PWS; (ii) determining (103) 2PWS as a second derivative with respect to time of the PWS; (iii) analyzing (105) the 2PWS to identify a first time point corresponding to the occurrence of a first maximum value in the 2PWS; (iv) determining (107) a value of the 1PWS at the first time point; (v) normalizing (109) the value of the 1PWS at the first time point with respect to a maximum value of the 1PWS; (vi) evaluating (111) the quality of the PWS using the normalized value.

Abstract: According to an aspect, there is provided a computer-implemented method for analysing a pulse wave signal, PWS, obtained from a subject to determine an indication of the blood pressure or a change in blood pressure of the subject. The PWS comprises pulse wave measurements for a plurality of cardiac cycles of the subject during a first time period.

Abstract: The invention provides a method (10) for detecting a neural respiratory drive measure of a user. The method includes obtaining (100) an EMG signal and processing (200, 280) the EMG signal to produce a surrogate respiration signal and a processed EMG signal. Inhalations of the user are then detected (300) based on the surrogate respiration signal. The detected inhalations are then used in conjunction with the processed EMG signal to determine (400) a neural respiratory drive measure of the user.

Abstract: According to an aspect, there is provided a computer-implemented method for analysing a pulse wave signal, PWS, obtained from a subject. The PWS comprises pulse wave measurements for a plurality of cardiac cycles of the subject during a first time period.

Abstract: The invention provides a seismocardiograph system, which includes an accelerometer, adapted to obtain accelerometer data from user, and a bandpass filter, adapted to filter the accelerometer data. The system further includes an envelope filter, adapted to suppress S2 peaks in the band pass filtered accelerometer data, wherein the envelope filter comprises: a low-pass filter; and a comb filter, wherein the delay of the comb filter is tuned to a left ventricle ejection time (LVET).

Abstract: The invention provides a system and method for determining a respiratory effort for a subject. The method comprises obtaining a relaxed signal representing a subject breathing in a relaxed manner and a forced signal representing a subject breathing in a forced manner. The relaxed signal is then smoothed over a first averaging window and the forced signal is smoothed over a second averaging window, wherein the first averaging window is longer than the second averaging window. Based on the smoothed relaxed signal and the smoothed forced signal, a respiratory effort can thus be determined.

Abstract: The invention provides a system and method for determining a respiratory effort for a subject. The method comprises obtaining a relaxed signal representing the subject breathing in a relaxed manner and a forced signal representing the subject breathing in a forced manner. A plurality of forced peaks is derived from the forced signal and candidate peaks are selected from the plurality of forced peaks. The candidate peaks are selected based on features of the forced peaks. A user selects a user identified peak from the candidate peaks and thus, a respiratory effort is determined based on the relaxed signal and the user identified peak.

Abstract: A method for generating a filtered EMG signal includes obtaining a combined signal, wherein the combined signal comprises an ECG signal and an EMG signal. A first high pass filter is applied to the combined signal and an ECG model signal is generated, based on the high pass filtered combined signal. The method further includes, generating a partially filtered EMG signal by subtracting the ECG model from the high pass filtered combined signal. A second high pass filter is then applied to the partially filtered EMG signal to generate a second EMG signal and to the ECG model signal to generate a second ECG model signal. A filtered EMG signal is generated based on the second EMG signal and the second ECG model by way of a gating technique.

Abstract: A processor and method for deriving a respiratory signal is based on processing a 3-axis acceleration signal. A gravity vector is isolated from the 3-axis acceleration signal and a coordinate transformation is performed into a transformed 3-axis coordinate system in which the isolated average gravity vector is aligned with a first axis of the transformed 3-axis coordinate system. Analysis is then performed only of the components for the remaining two axes of the transformed 3-axis coordinate system, thereby to derive a 1 dimensional respiratory signal. A respiration rate may for example be obtained from the 1 dimensional respiratory signal using frequency analysis, or sleep disordered breathing events may be identified.

Abstract: A processing apparatus for processing a physiological signal using model subtraction, notch filtering and gating. The processing apparatus comprises a model subtraction circuit configured to receive the physiological signal and to reduce a first unwanted signal component, such as an ECG contamination, in the physiological signal by subtracting from the physiological signal a model of the first unwanted signal component to obtain a residual signal; a filter circuit configured to receive the residual signal and to reduce a second unwanted signal component, such as power line noise, in the residual signal by applying a notch filter to obtain a filtered signal; and a gating circuit configured to receive the filtered signal and to apply gating to the filtered signal to obtain a gated signal. The processing apparatus further relates to a corresponding electromyography system and a method for processing a physiological signal using model subtraction, notch filtering and gating.

Abstract: There is provided a method and apparatus for determining at least one of a position and an orientation of a wearable device on a subject. At least one physiological characteristic signal is acquired from a subject (402). The acquired at least one physiological characteristic signal from the subject has one or more characteristics indicative of at least one of a position and an orientation of a wearable device on the subject. The at least one of the position and orientation of the wearable device on the subject is determined based on the one or more characteristics indicative of the at least one of the position and orientation of the wearable device on the subject (404).

Abstract: The present invention relates to determining a neural respiratory drive (NRD) in patients with chronic obstructive pulmonary disease (COPD) based on surface electromyography measurements taken from the intercostal muscles on the chest of a subject (100).

Abstract: An apparatus comprises an activity monitor for measuring physical activity of a subject. The activity monitor is configured to obtain a first set of physical activity data over a first time period, for example during the day, and a second set of physical activity data over a second time period, for example during the night. A processor processes the data obtained by the activity monitor to calculate a physical activity ratio which is the ratio of the physical activity measured during the first time period to the physical activity measured in the second time period. The processor also calculates a first overall value which represents an activity level of the subject during the first time period. The physical activity ratio together with the first overall value may be used to assess the severity of symptoms of COPD displayed by a subject or to identify respiratory disease comorbidity information for example psychological issues such as low motivation, or sleep quality issues displayed by the subject.

Abstract: The present invention relates to the field of medical technology and in particular to determining a respiratory activity in patients with chronic obstructive pulmonary disease (COPD) based on surface electromyography measurements taken from the intercostal muscles on the chest of a subject. A processing apparatus for processing an electromyography signal indicative of an activity of a target muscle in a human or animal body that relates to the measurement of respiratory effort amid an activity of at least one further muscle is presented.

Abstract: A processing apparatus (6) for determining a respiration signal (34) of a subject (100) is presented. The processing apparatus (6) is configured to perform the steps of obtaining a movement signal (22) descriptive of a respiratory movement, determining a first quantity (24) descriptive of a rotation axis and/or rotation angle based on the obtained movement signal (22), and estimating a rotation axis (25) and/or rotation angle (26) based on the first quantity (24) and a rotation model, wherein the rotation model models the respiratory movement as a rotation around a single rotation axis. This model of the rotation can be further used as a feature for an instantaneous classifier descriptive of a movement artifact descriptive of a non-respiratory movement. Furthermore, a processing method, a respiration monitor (1, 91), a computer-readable non-transitory storage medium and a computer program are presented.

Abstract: The invention relates to a method and an apparatus for the detection of the body position, especially while sleeping. More particularly, the invention relates to how the main body positions during sleep can be derived from the distribution of the reflection of a projected IR light from a subject's body under a blanket. Additionally, the breathing signals can be analyzed to determine the body posture.

Abstract: The present invention relates to a processing device for processing accelerometer signals (17, 17a-c) for use in monitoring vital signs of a subject, comprising—a signal input unit (38) for inputting an accelerometer signal (17, 17a-c) of the subject in time, the accelerometer signal (17, 17a-c) being related to at least one physiological event being a cardiovascular or a respiratory event of the subject and measured for at least one spatial direction, an envelope determination unit (19, 40) for determining an envelope signal (21) of the input accelerometer signal (17, 17a-c), a calculation unit (44) for calculating an adjustment factor (43) based on an estimated time interval (45) between a first and a second physiological event of the subject, and a signal adjustment unit (42) for adjusting the determined envelope signal (21) by multiplying the envelope signal (21) with the calculated adjustment factor (43).

Abstract: The invention provides a method (10) for detecting a neural respiratory drive measure of a user. The method includes obtaining (100) an EMG signal and processing (200, 280) the EMG signal to produce a surrogate respiration signal and a processed EMG signal. Inhalations of the user are then detected (300) based on the surrogate respiration signal. The detected inhalations are then used in conjunction with the processed EMG signal to determine (400) a neural respiratory drive measure of the user.

Abstract: The invention provides a seismocardiograph system, which includes an accelerometer, adapted to obtain accelerometer data from user, and a bandpass filter, adapted to filter the accelerometer data. The system further includes an envelope filter, adapted to suppress S2 peaks in the band pass filtered accelerometer data, wherein the envelope filter comprises: a low-pass filter; and a comb filter, wherein the delay of the comb filter is tuned to a left ventricle ejection time (LVET).

Abstract: A method for generating a filtered EMG signal includes obtaining a combined signal, wherein the combined signal comprises an ECG signal and an EMG signal. A first high pass filter is applied to the combined signal and an ECG model signal is generated, based on the high pass filtered combined signal. The method further includes, generating a partially filtered EMG signal by subtracting the ECG model from the high pass filtered combined signal. A second high pass filter is then applied to the partially filtered EMG signal to generate a second EMG signal and to the ECG model signal to generate a second ECG model signal. A filtered EMG signal is generated based on the second EMG signal and the second ECG model by way of a gating technique.