The invention provides a body-worn system that continuously measures pulse oximetry and blood pressure, along with motion, posture, and activity level, from an ambulatory patient. The system features an oximetry probe that comfortably clips to the base of the patient's thumb, thereby freeing up their fingers for conventional activities in a hospital, such as reading and eating. The probe secures to the thumb and measures time-dependent signals corresponding to LEDs operating near 660 and 905 nm. Analog versions of these signals pass through a low-profile cable to a wrist-worn transceiver that encloses a processing unit. Also within the wrist-worn transceiver is an accelerometer, a wireless system that sends information through a network to a remote receiver, e.g. a computer located in a central nursing station.

A neurological profile associated with introversion/extroversion levels, simultaneous visual element processing capability, and/or dynamism processing capability, etc., is determined to select market categories and stimulus material targeted to the particular neurological profile. The neurological profile is determined using information such as user input, user activity, social and environmental factors, genetic and developmental factors, and/or neuro-response data. The neurological profile can be matched with corresponding neurological profile templates to select market categories and stimulus material.

The present invention relates to a physiological monitor and system, more particularly to an electroencephalogram (EEG) monitor and system, and a method of detecting the presence or occurrence of suppression in the EEG signal. Accurately detecting signal suppression in real-time provides the clinician with the ability to prevent possibly severe, long-term damage to patients as a result of excessive anesthetic or sedative. The present invention provides such a system and method for accurately and automatically detecting suppression in physiological, particularly EEG, signals in real-time and allowing for the administration of treatment or medication to reverse the effects of such situations, or minimize the harm caused. The present invention also allows for the use of closed-loop treatment or drug delivery systems to further automate the process and provide rapid treatment to a patient to reverse or minimize potential harm.

A patient monitoring device configured to monitor cardiac activity and sleep stage information of a patient is provided. The device includes a plurality of electrodes to acquire electrocardiogram (ECG) signals from the patient, at least one motion sensor configured to generate a motion signal based upon movement of the patient, and at least one processor. The processor is configured derive motion parameters from the motion signal, derive ECG parameters from the ECG signals, determine whether the patient is in an immobilized sleep stage or a non-immobilized sleep stage based upon the motion parameters and the ECG parameters, adjust one or more cardiac arrhythmia detection parameters such that the device operates in a first monitoring and treatment mode when the patient is in an immobilized sleep stage, and monitor the patient for the cardiac arrhythmia using the first monitoring and treatment mode.

An optical data sensing device of a biological information measuring device, comprising: an optical sensor; a first light emitting device, configured to emit first light away from the optical sensor; and a first opaque isolation component, located between the optical sensor and the first light emitting device, configured to reduce the first light received by the optical sensor. The present invention also discloses an optical data sensing device comprising a plurality of light emitting devices with different emitting directions or wavelengths, to improve the accuracy of biological information measuring.

Continuous Glucose Monitoring (CGM) devices provide glucose concentration measurements in the subcutaneous tissue with limited accuracy and precision. Therefore, CGM readings cannot be incorporated in a straightforward manner in outcome metrics of clinical trials e.g. aimed to assess new glycaemic-regulation therapies. To define those outcome metrics, frequent Blood Glucose (BG) reference measurements are still needed, with consequent relevant difficulties in outpatient settings. Here we propose a “retrofitting” algorithm that produces a quasi continuous time BG profile by simultaneously exploiting the high accuracy of available BG references (possibly very sparsely collected) and the high temporal resolution of CGM data (usually noisy and affected by significant bias). The inputs of the algorithm are: a CGM time series; some reference BG measurements; a model of blood to interstitial glucose kinetics; and a model of the deterioration in time of sensor accuracy, together with (if available) a priori information (e.g. probabilistic distribution) on the parameters of the model. The algorithm first checks for the presence of possible artifacts or outliers on both CGM datastream and BG references, and then rescales the CGM time series by exploiting a retrospective calibration approach based on a regularized deconvolution method subject to the constraint of returning a profile laying within the confidence interval of the reference BG measurements. As output, the retrofitting algorithm produces an improved “retrofitted” quasi-continuous glucose concentration signal that is better (in terms of both accuracy and precision) than the CGM trace originally measured by the sensor. In clinical trials, the so-obtained retrofitted traces can be used to calculate solid outcome measures, avoiding the need of increasing the data collection burden at the patient level.

A non-invasive method and system is provided for determining an internal component of respiratory effort of a subject in a respiratory study. Both a thoracic signal (T) and an abdomen signal (A) are obtained, which are indicators of a thoracic component and an abdominal component of the respiratory effort, respectively. A first parameter of a respiratory model is determined from the obtained thoracic signal (T) and the abdomen signal (A). The first parameter is an estimated parameter of the respiratory model that is not directly measured during the study. The internal component of the respiratory effort is determined based at least on the determined first parameter of the respiratory model. The first model parameter is determined based on the thorax signal (T) and the obtained abdomen signal (A) without an invasive measurement.

Methods, systems, and apparatus for signal artifact detection and reduction are provided. The signal artifact may comprise an interference between an electroencephalography (EEG) signal and a magnetic resonance imaging (MRI) signal arising out of simultaneous EEG and MRI treatment.

In a method and system, a medical imaging modality and the parameters to be deployed for the determined imaging modality are determined to produce an image of an examination object using the determined imaging modality and the determined parameters. Information from the preliminary examination(s) of the examination object can be automatically classified to generate classification results corresponding to interfering influence(s) resulting from the production of the image. The classification results can be analyzed to evaluate the classification results. The medical imaging modality and the parameter(s) is determined, based on the evaluated results, to minimize an influence of the interfering influences of the classification results in image(s) of the examination object generated using the determined medical imaging modality and the determined one or more parameters. The image(s) may then be generated using the determined medical imaging modality and the determined parameter(s).

A method includes, in a processor, receiving example representations of geometrical shapes of a given type of organ. In a training phase, a neural network model is trained using the example representations. In a modeling phase, the trained neural network model is applied to a set of location measurements acquired in an organ of the given type, to produce a three-dimensional model of the organ.