The present specification discloses systems and methods of patient monitoring in which multiple sensors are used to detect physiological parameters and the data from those sensors are correlated to determine if an alarm should, or should not, be issued, thereby resulting in more precise alarms and fewer false alarms. Electrocardiogram readings can be combined with invasive blood pressure, non-invasive blood pressure, and/or pulse oximetry measurements to provide a more accurate picture of pulse activity and patient respiration. In addition, the monitoring system can also use an accelerometer or heart valve auscultation to further improve accuracy.

A medical system for sensing a physiological state requiring defibrillation in a patient. The system comprising: a low power sensor, a physiological parameter measuring device, and a processor. The low power sensor generating a baseline signal relating to a physiological status of said patient. The physiological parameter measuring device comprising at least one higher power sensor configured to output at least one physiological parameter signal indicative of at least one physiological parameter of said patient. The processor assessing the baseline signal and determining if the physiological status is outside predetermined threshold boundaries.

There is provided a method for measuring heart activity of a person in a single-use electrode patch, the method comprising: measuring the heart activity of the person; displaying the heart activity of the person on the basis of the measuring the heart activity; and broadcasting at least one message enabling transfer of heart activity data indicating the heart activity of the person from the electrode patch to the one or more external devices, wherein the broadcasting is performed while the heart activity of the person is being measured and displayed by the electrode patch.

Method and apparatus are disclosed for monitoring of steering wheel engagement for autonomous vehicles. An example vehicle includes an autonomy unit configured to perform autonomous motive functions, a steering wheel, capacitive sensors coupled to the steering wheel, a second sensor configured to monitor an operator, and a controller. The controller is configured to detect a first heart rate via the capacitive sensors, detect a second heart rate via the second sensor, identify that an engagement-imitating device is coupled to the steering wheel responsive to determining that the first heart rate does not correlate with the second heart rate, and emit an alert responsive to determining that the engagement-imitating device is coupled to the steering wheel.

Technologies and implementations for wearable healthcare devices are generally disclosed. An example method performed by a wrist-wearable device includes: detecting, by a sensor, a physiological parameter of a user; determining, by a processor based on the physiological parameter, that the user is experiencing atrial fibrillation (AF); outputting, by a display, a visual signal indicating that the user is experiencing the AF; and transmitting, by a transceiver to a first external computing device, a first wireless signal indicating that the user experienced the AF.

The method allows controlling the quality of an initial RR series made up of a plurality of (RRi) samples which are respectively a function of time intervals (δti) which separate two successive heartbeats. During this method, one resamples the RR series so as to obtain a resampled RR series, and one automatically controls the quality of the RR series by automatically calculating at least the mathematical norm value (NORME), in a sliding window, of the resampled RR series, said mathematical norm value being given by the following formula: $\mathrm{NORME}=\sqrt{\underset{i=1}{\overset{N}{.Math.}}{\left({\mathrm{RR}}_i-\frac{1}{N}\underset{i=1}{\overset{N}{.Math.}}\left({\mathrm{RR}}_i\right)\right)}^2}$
where N is the number of RRi samples in said window.

A physiological signal monitoring method includes steps that involve: acquiring samples of at least one digitized physiological signal through the use of a device carried by a user; detecting events within the digitized physiological signal by means of the device and extracting characteristics of the detected events by means of the device; searching for an anomaly in the events and characteristics of the extracted events by means of the device; and, via an encrypted wireless link, transmitting the digitized physiological signal by means of the device to a server via a mobile terminal when an anomaly is detected. If an anomaly is not detected, the digitized physiological signal is deleted by the device.

One aspect of the apparatus comprising, a sensor configured to acquire a biological signal of a user, and a controller configured to, determine whether the biological signal is continuously outside a predetermined range for a first time period, after determining that the biological signal has been continuously outside the predetermined range for the first time period, then determine whether the biological signal is inside the predetermined range, and activate an alarm if the controller has determined that (i) the biological signal has been outside the predetermined range for the first time period, and (ii) the biological signal has been continuously inside the predetermined range for a second time period, the second time period being longer than the first time period.

The present invention relates to an electrocardiogram measurement system using a wearable device, comprising a photoplethysmograph, and an electrocardiograph provided in a wearable device or an electrocardiograph which can be separated from the wearable device and carried, wherein the photoplethysmograph comprises a photoplethysmogram measurement circuit comprising an LED and a photodiode, an AD converter connected to an output terminal of the photoplethysmogram measurement circuit, for converting an analog signal to a digital signal, a wireless communication means for transmitting and receiving data, and a microcontroller for measuring photoplethysmogram, the microcontroller extracts photoplethysmogram parameters by analyzing the measured photoplethysmogram, determines generation of an alarm by using the extracted photoplethysmogram parameters, and generates an alarm on the basis of the determination result, and the electrocardiograph comprises three dry electrocardiogram measurement electrodes and two amplifiers for amplifying two electrocardiogram signals induced at two electrocardiogram electrodes out of the three electrocardiogram electrodes.

A method for determining and responding in real-time to an increased risk of death relating to a patient with epilepsy is provided. The method includes receiving cardiac data and determining a cardiac index based upon the cardiac data. The method includes determining an increased risk of death associated with epilepsy if the indices are extreme, issuing a warning of the increased risk of death and logging information related to the increased risk of death. Also presented is a second method for determining and responding in real-time to an increased risk of death relating to a patient with epilepsy comprising receiving at least one of arousal data, responsiveness data or awareness data and determining an arousal index, a responsiveness index or an awareness index, where the indices are based on arousal data, responsiveness data or awareness data respectively. The second method includes determining an increased risk of death related to epilepsy if indices are extreme values, issuing a warning of the increased risk of death and logging information related to the increased risk of death. A computer readable program storage device is also provided. Also provided is a method for receiving body data, determining a cardiac, an arousal, a responsiveness, or a kinetic index, determining an increased or increasing risk of death over a first time window relating to a patient with epilepsy and issuing a warning and logging relevant information.