A method, apparatus, and system for measuring respiratory effort of a subject are provided. According to the method, a thoracic effort signal (T) is obtained, the thoracic effort signal (T) being an indicator of a thoracic component of the respiratory effort. An abdomen effort signal (A), the abdomen effort signal (A) being an indicator of an abdominal component of the respiratory effort. A respiratory flow (F) is obtained. The respiratory effort is determined by adjusting the components of a model of the respiratory system based on the thoracic effort signal (T), the abdomen effort signal (A), or the respiratory flow (F) or any combination of the thoracic effort signal (T), the abdomen effort signal (A), and the respiratory flow (F).

A method of estimating a stress level of a human by an apparatus using heart activity measurement data includes: executing a breathing exercise application by the apparatus, starting a breathing exercise of the breathing exercise application and outputting, during the breathing exercise, breathing instructions to a user of the apparatus; acquiring a set of heart activity measurement data samples measured by a heart activity sensor from the user during the breathing exercise; computing a set of inter-heartbeat interval samples of the set of heart activity measurement data samples; computing a cardiac coherence of the user during the exercise from the set of inter-heartbeat interval samples; measuring a respiratory rate of the user during the breathing exercise; computing a score of the breathing exercise on the basis of the respiratory rate and the cardiac coherence, the score indicating a stress level of the user; and outputting the score through an interface of the apparatus.

A respiratory effort sensing apparatus (2) includes a flexible belt member (8) having a first buckle member (12A) and a second buckle member (12B), and a wearable respiratory monitoring recording device (6). The monitoring device includes: (i) a processing apparatus (34) structured to be selectively operable in a sleep mode and an active mode, and (ii) buckle detection circuitry (46) structured to detect that both buckle members are operatively coupled to the respiratory monitoring recording device and in response thereto generate a buckle detection signal. The processing apparatus is structured to, in response to receiving the buckle detection signal, automatically: (a) move from the sleep mode to the active mode, and (b) generate data indicative of a respiratory effort of a patient over time based on an effort-based signal generated by the respiratory effort sensing apparatus in response to changes in volume of a body part of the patient.

Embodiments described herein relate generally to biosensing garments, and in particular, to systems and methods for monitoring respiration in a biosensing garment, whereby an improved integration of the respiration monitoring circuit into the garment is achieved, resulting in improved signal quality and durability. In some embodiments, an apparatus includes an elongate member having a longitudinal axis and configured to be stretchable along its longitudinal axis. The elongate member includes a plurality of elastic members (e.g., a first elastic member, a second elastic member, and a third elastic member) that extend along the longitudinal axis. A conductive member is coupled to the first, second and third members, and forms a curved pattern along the longitudinal axis of the elongate member. The conductive member is configured to change from a first configuration to a second configuration as the elongate member stretches along its longitudinal axis.

Systems and methods for non-invasive blood pressure measurement are disclosed. In some embodiments, a system comprises a wearable member configured to generate first and second signals, and a blood pressure calculation system. The blood pressure calculation system a pre-processing module configured to filter noise from the signals, and a wave selection module configured to identify subsets of waves of the signals, a feature extraction module configured to generate sets of feature vectors form the subsets of waves, and a blood pressure processing module configured to calculate an arterial blood pressure value based on the sets of feature vectors and an empirical blood pressure calculation model, the empirical blood pressure calculation model configured to receive the sets of feature vectors as input values. The blood pressure calculation system further includes a communication module configured to provide a message including or being based on the arterial blood pressure value.

A method includes retrieving a lung volume waveform from an electrical impedance tomography device. The method further includes retrieving at least one of a flow waveform and a pressure waveform. The method also includes aligning the lung volume waveform and the at least one of the flow waveform and the pressure waveform with respect to time. The method further includes comparing the lung volume waveform and the at least one of the flow waveform and the pressure waveform. The method also includes determining if an asynchronous respiratory event occurred based on comparing the lung volume waveform and the at least one of the flow waveform and the pressure waveform. The method further includes classifying the asynchronous respiratory event. The method also includes providing an alert identifying the asynchronous respiratory event. A system includes a receiver, a processor, and a memory device configured to perform the method.

The present invention provides, among other things, apparatus and methods of use for treating a subject in need of assistance with breathing. In some embodiments the subject suffers from airflow obstruction. In some embodiments, the subject suffers from chronic obstructive pulmonary disease.

Embodiments described herein relate generally to biosensing garments, and in particular, to systems and methods for monitoring respiration in a biosensing garment, whereby an improved integration of the respiration monitoring circuit into the garment is achieved, resulting in improved signal quality and durability. In some embodiments, an apparatus includes an elongate member having a longitudinal axis and configured to be stretchable along its longitudinal axis. The elongate member includes a plurality of elastic members (e.g., a first elastic member, a second elastic member, and a third elastic member) that extend along the longitudinal axis. A conductive member is coupled to the first, second and third members, and forms a curved pattern along the longitudinal axis of the elongate member. The conductive member is configured to change from a first configuration to a second configuration as the elongate member stretches along its longitudinal axis.

The present technology relates to the field of medical monitoring. Patient monitoring systems and associated devices, methods, and computer readable media are described. In some embodiments, a patient monitoring system includes one or more sensors configured to capture first data related to a patient and a wearable wireless hub configured to receive the first data. In these and other embodiments, the patient monitoring system can include an image capture device configured to capture second data related to the patient. In these and still other embodiments, the patient monitoring system can determine one or more patient parameters based on the first and/or the second data. The patient monitoring system can monitor the one or more patent parameters and trigger an alert or alarm when a patient parameter abnormality is detected.

A method, apparatus, and system for measuring respiratory effort of a subject are provided. A thorax effort signal and an abdomen effort signal are obtained. The thorax effort signal and the abdomen effort signal are each divided into a volume-contributing component of the respiratory effort and a paradox component. The paradox component represents a non-volume-contributing component of the respiratory effort. The abdomen paradox component is negatively proportional to the thoracic paradox component. The thorax effort signal or the abdomen effort signal or both are weighted by a weight factor to obtain a volume-proportional signal. The volume-proportional signal is proportional to the actual respiratory volume of the respiratory effort. A calibration factor for calibrating the thorax effort signal and the abdomen effort signal is obtained by optimizing the weight factor by minimizing thoracic paradox component and the abdomen paradox component.