The present invention relates to a detecting device for detecting a blood count parameter in a blood vessel. The detecting device comprises a signal generator, which is designed to generate a calibration measurement signal, wherein the calibration measurement signal comprises a superimposition of a first excitation signal and a second excitation signal, wherein the first excitation signal has a higher frequency than the second excitation signal and/or the second excitation signal is a direct signal and/or wherein the second excitation signal has a higher power than the first excitation signal; a transceiver arrangement which is designed to emit the calibration measurement signal towards the blood vessel and to receive a first system response signal in response to the emission of the calibration signal; wherein the transceiver arrangement is designed to emit a third excitation signal directed towards the blood vessel and to receive a second system response signal in response to the emission of the third excitation signal; and a processor which is designed to link the first system response signal and the second system response signal in order to obtain a measurement signal for determining the blood count parameter.

An intelligent dog collar for monitoring physiological parameters of a dog, comprising: a movement sensor unit comprising an accelerometer and/or a gyrometer, wherein the movement sensor unit is configured to detect raw movement signals of the dog collar, a storage module storing a trained neural network, the neural network being configured to determine a physiologic information into raw movement signals detected by the movement sensor unit, a processing unit connected to the movement sensor unit and configured to operate the trained neural network, a memory configured to store the identified physiologic information, an interface for transmitting to a communication device the identified physiologic information.

Radar based HR and BR measurements by simultaneous decoding is a technical problem due to presence of intermodulation of BR and HR harmonics, which degrades simultaneous decoding. Embodiments herein provide a method and system for unobtrusive liveliness detection and monitoring of a subject using a Dual Frequency Radar (DFR) in an IOT network. The system has the capability to completely process the captured raw signals onboard to by applying required signal conditioning and extraction of relevant information using unique signal processing techniques for determining the HR and the BR of the subject accurately. The intermodulation of BR and HR harmonics is eliminated by the system by performing frequency spectrum averaging of both radars signals, which improves the accuracy. Further, the system is configured with a light MQTT protocol and encoding modules for any data to be shared for off board processing, ensuring data security and privacy compliance.

An apparatus, system, and method monitors the motion, breathing, heart rate and sleep state of subjects, e.g., humans, in a convenient, non-invasive/non-contact, and low-cost fashion. More particularly, the motion, breathing, and heart rate signals are obtained through processing applied to a raw signal obtained in a non-contact fashion, typically using a radio-frequency sensor. Periods of sleep disturbed respiration, or central apnea can be detected through analysis of the respiratory signal. The mean heart rate, and derived information, such as the presence of cardiac arrhythmias can be determined from the cardiac signal. Motion estimates can be used to recognize disturbed sleep and periodic limb movements. The sleep state may be determined by applying a classifier model to the resulting streams of respiratory, cardiac and motion data. A means for display of the sleep state, respiratory, cardiac, and movement status may also be provided.

An apparatus, system, and method monitors the motion, breathing, heart rate and sleep state of subjects, e.g., humans, in a convenient, non-invasive/non-contact, and low-cost fashion. More particularly, the motion, breathing, and heart rate signals are obtained through processing applied to a raw signal obtained in a non-contact fashion, typically using a radio-frequency sensor. Periods of sleep disturbed respiration, or central apnea can be detected through analysis of the respiratory signal. The mean heart rate, and derived information, such as the presence of cardiac arrhythmias can be determined from the cardiac signal. Motion estimates can be used to recognize disturbed sleep and periodic limb movements. The sleep state may be determined by applying a classifier model to the resulting streams of respiratory, cardiac and motion data. A means for display of the sleep state, respiratory, cardiac, and movement status may also be provided.

An electromagnetic (EM) probe for monitoring one or more biological tissues. The EM probe comprises a cup shaped cavity having an opening and an interior volume, a circumferential flange formed substantially around the cup shaped cavity, in proximity to the opening, at least one layer of a material, for absorbing electromagnetic radiation, applied over at least one of a portion of the circumferential flange and a portion of the outer surface of the cup shaped cavity, and at least one EM radiation element which performs at least one of emitting and capturing EM radiation via the interior volume.

An electromagnetic (EM) probe for monitoring one or more biological tissues. The EM probe comprises a cup shaped cavity having an opening and an interior volume, a circumferential flange formed substantially around the cup shaped cavity, in proximity to the opening, at least one layer of a material, for absorbing electromagnetic radiation, applied over at least one of a portion of the circumferential flange and a portion of the outer surface of the cup shaped cavity, and at least one EM radiation element which performs at least one of emitting and capturing EM radiation via the interior volume.

The present invention provides a carotid blood pressure detection device, comprising: a first sensing unit, a second sensing unit, and a controller connected or coupled to the first sensing unit and the second sensing unit. The first sensing unit is disposed on a subject's neck and adjacent to a first position of the subject's carotid arteries. The second sensing unit is disposed on the subject's neck and adjacent to a second position of the subject's carotid arteries. The controller derives a mean arterial pressure of a section of the subject's carotid arteries that lies between the first position and the second position of the subject's carotid arteries from pulse wave data measured and obtained by the first sensing unit and pulse wave data measured and obtained by the second sensing unit.

The present invention provides a carotid blood pressure detection device, comprising: a first sensing unit, a second sensing unit, and a controller connected or coupled to the first sensing unit and the second sensing unit. The first sensing unit is disposed on a subject's neck and adjacent to a first position of the subject's carotid arteries. The second sensing unit is disposed on the subject's neck and adjacent to a second position of the subject's carotid arteries. The controller derives a mean arterial pressure of a section of the subject's carotid arteries that lies between the first position and the second position of the subject's carotid arteries from pulse wave data measured and obtained by the first sensing unit and pulse wave data measured and obtained by the second sensing unit.

An estimation system includes: a first sensor that detects a first amount of activity that is an amount of activity of a subject in a room; a second sensor that detects a second amount of activity that is an amount of activity of the subject on a bed in the room; and an estimation device that estimates at least one of a position and an action of the subject in association with a position in the room based on the first amount of activity detected by the first sensor and the second amount of activity detected by the second sensor, and outputs an estimation result obtained from the estimation. The first sensor and the second sensor are sensors other than two-dimensional image sensors.