There are provided a biological signal measurement device capable of obtaining a variety of biological information and applicable also to medical fields and the like, a biological state inference device, and a biological state inference system using these. The biological signal measurement device 1 of the present invention includes three biological signal detection units, namely, a left upper part biological signal detection unit 11, a right upper part biological signal detection unit 12, and a lower part biological signal detection unit 13. The biological state inference device 1 is capable of obtaining a highly precise inference-use processed waveform from which electrical noise has been removed, by using an appropriate combination of time-series data obtained from the three biological signal detection units 11 to 13. Because the precision of an inference-use processed waveform corresponding to target biological information on breathing, heart sound, or the like increases, the precision of inferring a biological state also increases.

Systems, devices, and techniques are disclosed for automatically detecting arrhythmia locations. The systems, devices, and techniques include a plurality of body surface electrodes configured to sense electrocardiogram (ECG) data. The systems, devices, and techniques include a processor including a neural network configured to receive a plurality of historical ECG data and corresponding arrhythmia locations determined based on each of the plurality of historical ECG data, train a learning system based on the plurality of historical ECG data and corresponding arrhythmia locations, generate a model based on the learning system. New ECG data may be received from the plurality of body surface electrodes and the processor may provide a new arrhythmia location based on the new ECG data. Additionally, a new coherent mapping adjustment may be provided based on a model that is trained using historical coherent mapping adjustments.

A wearable monitoring system and associated method that is configured to (i) determine three dimensional displacement of the spine of a subject's chest wall with respect to the subject's spine, (ii) process the three dimensional anatomical data, (iii) determine at least one respiratory parameter associated with the monitored subject and value thereof as a function of the three dimensional anatomical data, and (iv) determine a respiratory disorder as a function of the determined respiratory parameter and value thereof.

A wearable respiration monitoring system having a transmitter coil that is adapted to generate and transmit multi-frequency AC magnetic fields, a plurality of receiving coils adapted to detect variable strengths in the AC magnetic fields and generate AC magnetic field strength signals representing anatomical displacements of a monitored subject, and at least one accelerometer that is configured to detect and monitor anatomical positions and movement of the subject, and generate and transmit accelerometer signals representing same. The wearable monitoring system further includes an electronics module that is adapted to receive the AC magnetic field strength signals and accelerometer signals, and determine at least one respiratory disorder as a function of the AC magnetic field strength signals and at least one anatomical position of the subject as a function of the accelerometer signals.

Methods and systems estimate cardio-respiratory parameter(s), such as from in-phase and quadrature channels. The channels may represent patient chest movement and may be generated with a sensor, such as a contactless sensor that may sense movement with radio-frequency signals. In the methods/systems, the in-phase and quadrature channels may be processed, such as in a processor(s), using relative demodulation to generate cardio-respiratory parameter estimate(s). Optionally, the processing produces a jerk signal that may be filtered for producing a heart rate estimate, such as from zero-crossings of the filtered signal. Optionally, the processing produces a chest velocity signal that may be filtered for producing a respiratory rate estimate, such as from zero-crossings of the filtered signal. Optionally, a respiratory volume, such as tidal volume, may be estimated from an intrapulmonary pressure signal generated by applying a function to a chest displacement signal where the function relates intrapulmonary pressure and chest displacement.

Methods and systems estimate cardio-respiratory parameter(s), such as from in-phase and quadrature channels. The channels may represent patient chest movement and may be generated with a sensor, such as a contactless sensor that may sense movement with radio-frequency signals. In the methods/systems, the in-phase and quadrature channels may be processed, such as in a processor(s), using relative demodulation to generate cardio-respiratory parameter estimate(s). Optionally, the processing produces a jerk signal that may be filtered for producing a heart rate estimate, such as from zero-crossings of the filtered signal. Optionally, the processing produces a chest velocity signal that may be filtered for producing a respiratory rate estimate, such as from zero-crossings of the filtered signal. Optionally, a respiratory volume, such as tidal volume, may be estimated from an intrapulmonary pressure signal generated by applying a function to a chest displacement signal where the function relates intrapulmonary pressure and chest displacement.

A baby bottle device (100) is provided which comprises at least one 100 movement sensor (140, 150) for detecting a movement of the baby bottle device (100). The movement data from the movement sensor (140, 150) is analyzed in an analyzer (200) to perform a suck-swallow-breathe analysis during a drinking phase of the baby based on the movement data from the movement sensor (140, 150). Thus, a drinking behavior of a baby can be efficiently analyzed.

A baby bottle device (100) is provided which comprises at least one 100 movement sensor (140, 150) for detecting a movement of the baby bottle device (100). The movement data from the movement sensor (140, 150) is analyzed in an analyzer (200) to perform a suck-swallow-breathe analysis during a drinking phase of the baby based on the movement data from the movement sensor (140, 150). Thus, a drinking behavior of a baby can be efficiently analyzed.

A method for monitoring a patient includes receiving sensor signals from a sensor arrangement, extracting movement information from the sensor signals, determining a sensing period between the sensor arrangement and a body part of a patient based on the movement information, and determining a respiratory rate of the patient based on the sensor signals occurring during the period of contact. The sensor signals may be received from a sensor arrangement incorporated on or within a wearable item that moves relative to the body part of the patient. The sensor arrangement is in intermittent patterns of contact and non-contact with patient as a result of movement of the wearable item. The wearable item may be, for example, a pendant on a necklace.

A method for monitoring a patient includes receiving sensor signals from a sensor arrangement, extracting movement information from the sensor signals, determining a sensing period between the sensor arrangement and a body part of a patient based on the movement information, and determining a respiratory rate of the patient based on the sensor signals occurring during the period of contact. The sensor signals may be received from a sensor arrangement incorporated on or within a wearable item that moves relative to the body part of the patient. The sensor arrangement is in intermittent patterns of contact and non-contact with patient as a result of movement of the wearable item. The wearable item may be, for example, a pendant on a necklace.