Certain aspects relate to biopsy apparatuses, systems and techniques for biopsy using a biopsy pattern. Some aspects relate to moving a distal portion of a medical instrument to one or more sample locations of the biopsy pattern and guiding the instrument to obtain tissue samples from the sample locations within the biopsy pattern. Some aspects relate to obtaining the biopsy pattern and adjusting the sample locations within the biopsy pattern based on various factors such as anatomical features.

The differential voltage measuring system has a number of signal measuring circuits, each having a capacitive sensor element for capturing a measurement signal relating to the patient. The differential voltage measuring system further has a signal processing apparatus for determining at least one bioelectrical signal from the measurement signals and a computer unit which is configured to ascertain, on the basis of the at least one bioelectrical signal, and to provide, an item of breathing information, said breathing information indicating a breathing activity of the patient.

A system for monitoring a sleep of a user includes a plurality of patches for placement adjacent to a surface of a body of a user, a processor, and a data communication system. Each patch from the plurality of patches includes at least one sensor. The data communication system transmits positional data generated by the plurality of sensors, including orientation data and motion data, to the processor. The processing of the positional data includes detecting a change in position of the body of the user between a first position and a second position. Based on the first image and the second image, an animation of a movement of the body from the first position to the second position is generated.

Systems and methods for monitoring physiologic response to Valsalva maneuver (VM) are disclosed. An exemplary patient monitor may detect a natural incidence of a VM session occurred in an ambulatory setting using a heart sound (HS) signal sensed from the patient. The patient monitor may include a physiologic response analyzer to sense patient physiologic response during the detected VM session, and generate a cardiovascular or autonomic function indicator based on the sensed physiologic response to the VM. Using the physiologic response to the VM, the system may detect a target physiologic event using the sensed physiologic response to the VM.

Systems and methods for monitoring physiologic response to Valsalva maneuver (VM) are disclosed. An exemplary patient monitor may detect a natural incidence of a VM session occurred in an ambulatory setting using a heart sound (HS) signal sensed from the patient. The patient monitor may include a physiologic response analyzer to sense patient physiologic response during the detected VM session, and generate a cardiovascular or autonomic function indicator based on the sensed physiologic response to the VM. Using the physiologic response to the VM, the system may detect a target physiologic event using the sensed physiologic response to the VM.

An example monitoring device for detecting and measuring a vital sign of a subject includes: a base; a battery mounted to the base; first and second transceivers attached to the base at opposing angles, and powered by the battery to transmit pulses and receive reflected pulses; an antenna powered by the battery, and configured to wirelessly transmit data acquired from the first and second transceivers; and a computing device powered by the battery, and operatively coupled to the first and second transceivers and the antenna, the computing device having a processing device and a memory storing instructions that, when executed by the processing device, cause the monitoring device to determine a respiration rate by detecting a cyclical change in distance based on the reflected pulses.

Methods, apparatus and systems for radio-based sleep tracking are described. In one example, a described system comprises: a transmitter configured to transmit a first wireless signal through a wireless multipath channel in a venue; a receiver configured to receive a second wireless signal through the wireless multipath channel, wherein the second wireless signal differs from the first wireless signal due to the wireless multipath channel which is impacted by a sleeping motion of an object in the venue; and a processor. The processor is configured for: obtaining a time series of channel information (TSCI) of the wireless multipath channel based on the second wireless signal, wherein each channel information (CI) of the TSCI comprises N1 components, wherein N1 is a positive integer larger than one, computing N1 component-wise analytics each associated with one of the N1 components of the TSCI, identifying N2 largest component-wise analytics among the N1 component-wise analytics, wherein N2 is a positive integer less than N1 computing at least one first motion statistics based on the N2 largest component-wise analytics of the TSCI, and monitoring the sleeping motion of the object based on the at least one first motion statistics.

Embodiments are disclosed for sleep staging using machine learning. In an embodiment, a method comprises: receiving, with at least one processor, sensor signals from a sensor, the sensor signals including at least motion signals and respiratory signals of a user; extracting, with the at least one processor, features from the sensor signals; predicting, with a machine learning classifier, that the user is asleep or awake based on the features; and computing, with the at least one processor, a sleep or wake metric based on whether the user is predicted to be asleep or awake.

Doppler signal processing device for detecting an object according to a received wireless signal. The Doppler signal processing device includes a frequency analysis unit for generating a frequency domain signal vector according to at least one digital signal, an interference suppression unit for performing a suppression operation according to the frequency domain signal vector and a frequency domain interference estimation signal vector to generate an interference suppressed frequency domain signal vector, an interference estimation unit for generating the frequency domain interference estimation signal vector according to the frequency domain signal vector, a detection unit for generating a result signal according to the interference suppressed frequency domain signal vector, an error detection unit for optionally providing an error detection control signal to the interference estimation unit to adjust a rate of updating the frequency domain interference estimation signal vector.

Doppler signal processing device for detecting an object according to a received wireless signal. The Doppler signal processing device includes a frequency analysis unit for generating a frequency domain signal vector according to at least one digital signal, an interference suppression unit for performing a suppression operation according to the frequency domain signal vector and a frequency domain interference estimation signal vector to generate an interference suppressed frequency domain signal vector, an interference estimation unit for generating the frequency domain interference estimation signal vector according to the frequency domain signal vector, a detection unit for generating a result signal according to the interference suppressed frequency domain signal vector, an error detection unit for optionally providing an error detection control signal to the interference estimation unit to adjust a rate of updating the frequency domain interference estimation signal vector.