A system for monitoring medical conditions including pressure ulcers, pressure-induced ischemia and related medical conditions comprises at least one sensor adapted to detect one or more patient characteristic including at least position, orientation, temperature, acceleration, moisture, resistance, stress, heart rate, respiration rate, and blood oxygenation, a host for processing the data received from the sensors together with historical patient data to develop an assessment of patient condition and suggested course of treatment, including either suspending or adjusting turn schedule based on various types of patient movement. Compliance with Head-of-Bed protocols can also be performed based on actual patient position instead of being inferred from bed elevation angle. The sensor can include bi-axial or tri-axial accelerometers, as well as resistive, inductive, capacitive, magnetic and other sensing devices, depending on whether the sensor is located on the patient or the support surface, and for what purpose.

Various examples are described for detecting heart rate and respiratory rate by using measurements of light applied to skin through an article. For example, a sensor application obtains a set of measurements of light. The application compensates for a contribution of the article based on one or more known optical properties of the article. The sensor application further determines, from the set of measurements of light, a periodic change in amplitude. The sensor application identifies the periodic change in amplitude as a heart rate having an identical periodicity. The sensor application identifies a respiratory rate as equal to the rate of change of the heart rate.

A physiological sensor device and system, and a correction method are provided. The physiological sensor device includes a physiological signal sensor, a first compensation sensor, and a signal processing device. The physiological signal sensor is attached to an object to be detected to sense a physiological signal value. The first compensation sensor is disposed on the physiological signal sensor. The signal processing device is coupled to the physiological signal sensor and the first compensation sensor. The signal processing device obtains through the first compensation sensor a failure region of the physiological signal sensor partially detached from the object to be detected and obtains a first failure compensation value according to the failure region, so as to compensate the physiological signal value sensed by the physiological signal sensor.

Systems and methods are described for implementing a catheter model to estimate shape of a deformable catheter in a three-dimensional space. The catheter model includes two or more model segments that correspond to two or more segments of the deformable catheter. Each model segment includes a length and location of model electrode(s) and/or model magnetic sensor(s) corresponding electrodes and/or magnetic sensors of the deformable catheter. Variable shape parameter define a curvature of the segment. Varying the shape parameters generates a plurality of potential catheter shapes. In conjunction with generating the potential catheter shapes, impedance and/or magnetic responses (e.g., measured responses) are obtained for the physical electrodes and/or physical magnetic sensors of the deformable catheter. Using a selected one (e.g., most likely) of the potential catheter shapes and the measured responses, the shape parameters are updated and a catheter shape is generated and displayed.

A medical apparatus, method, or storage medium to perform monitoring a sensor of the medical apparatus to obtain a sensor reading, performing impact detection based on the sensor reading, generating an impact profile based on the impact detection, characterizing the impact detection, and responding to the impact detection.

Disclosed are a wearable multi-index integrated physiological intelligent sensor system and a physiological index monitoring method. The system includes a device body and an intelligent terminal. The device body is provided with a fixing piece, which is configured to fix the device body at a human ear; the device body is further provided with a collecting and processing assembly, which is in wireless communication connection with the intelligent terminal; the collecting and processing assembly collects a corresponding physiological index signal in response to a physiological index collection instruction sent by the intelligent terminal, and analyzes and processes the physiological index signal to obtain a corresponding physiological index data, and sends the physiological index data to the intelligent terminal; in which, the physiological index signal includes electrodermal signal, heart rate signal and blood oxygen signal; the intelligent terminal is configured to receive and display a physiological index data.

A method for detecting heart beats is disclosed. A plurality of sensors are configured to receive a cardiac signal and another cardiac signal or a signal correlated with a noise source. A processor is configured to detect candidate peaks in a cardiac signal and select a subset of the candidate peaks for temporal correlation with features, such as peaks, in another cardiac signal or noise correlated signal. This relationship is quantified by a correlation measure. The correlation measure, in turn, influences the likelihood that a particular peak or sequence corresponds to a heartbeat. Candidate peaks that were not part of the correlation process may then be added to a sequence or sequences associated with the peaks subject to the correlation analysis. Sequences are scored according to quality and a final sequence is selected as possible heartbeats.

The invention provides a multi-sensor system that uses an algorithm based on adaptive filtering to monitor a patient's respiratory rate. The system features a first sensor selected from the following group: i) an impedance pneumography sensor featuring at least two electrodes and a processing circuit configured to measure an impedance pneumography signal; ii) an ECG sensor featuring at least two electrodes and an ECG processing circuit configured to measure an ECG signal; and iii) a PPG sensor featuring a light source, photodetector, and PPG processing circuit configured to measure a PPG signal. Each of these sensors measures a time-dependent signal which is sensitive to respiratory rate and, during operation, is processed to determine an initial respiratory rate value. An adaptive digital filter is determined from the initial respiratory rate. The system features a second sensor (e.g. a digital 3-axis accelerometer) that attaches to the patient's torso and measures an ACC signal indicating movement of the chest or abdomen that is also sensitive to respiratory rate. This second signal is processed with the adaptive filter to determine a final value for respiratory rate.

The present invention provides for a data acquisition system for EEG and other physiological conditions, preferably wireless, and method of using such system. The wireless EEG system can be used in a number of applications including both studies and clinical work. These include both clinical and research sleep studies, alertness studies, emergency brain monitoring, and any other tests or studies where a subject's or patient's EEG reading is required or helpful. This system includes a number of features, which enhance this system over other systems presently in the marketplace. These features include but are not limited to the having multiple channels for looking at a number of physiological features of the subject or patient, a built in accelerometer for looking at a subject's or patient's body motion, a removable memory for data buffering and storage, capability of operating below 2.0 GHz, which among other things allows for more channels, movement artifact correction including video, pressure sensors capable of measuring or determining airflow, tidal volume and ventilation rate, and capability of manual and automatic RF sweep.

The invention comprises a method for estimating state of a cardiovascular system, comprising the steps of: providing a cardiac analyzer, comprising: a blood pressure sensor, the blood pressure sensor generating a time-varying pressure state waveform output from a portion of a person; a system processor connected to the blood pressure sensor; and a dynamic state-space model of a cardiovascular system, the system processor receiving cardiovascular input data, from the blood pressure sensor, related to a transient pressure state of the cardiovascular system, where at least one probabilistic model, of the dynamic state-space model, operating on the time-varying pressure state waveform output generates a probability distribution function to a non-pressure state of the cardiovascular system. The probability distribution function is iteratively updated using synchronized updated time-varying pressure state waveform output from the blood pressure sensor and a non-pressure state output related to a cardiovascular system parameter is generated.