Apdm, Inc

Portland State University

Innovatec, S.l.

Mortara Instrument, Inc.

Universidad De Valladolid

Other

Universidad Politècnica De València

Universidade De Vigo

Tiba Medical, Inc.

University of Valladolid

Pedro Mateo Riobo Aboy

James McNames

Andrew S Greenberg

Stephen Dylan Berry

David Cuesta Frau

Sean Pearson

Timothy Brandon

Francisco Ibanez Garcia

Jose Miguel Llopis Vaño

Roberto Hornero Sánchez

Gavin Gallino

Merat Bagha

Jose Ramon Fernandez Bernardez

Francisco Ibañez Garcia

Artemio Mojon Ojea

Felix Del Campo Matias

Daniel Álvarez González

Sunghan Kim

Félix Del Campo Matías

M Elena Fabregat

Cristina Crespo Veiga

Carlos Gómez Peña

Roberto Hornero Sanchez

Diego Aboy Garcia

Jose Victor Marcos Martin

José Victor Marcos Martín

Daniel Alvarez Gonzalez

Disclosed embodiments include an apparatus that comprises (a) a kinematics sensor module including an accelerometer, a gyroscope, a magnetometer, or combinations thereof; and (b) a bidirectional wireless communication module configured for wirelessly synchronizing the sampling time instances of the kinematics sensor module with the sampling time instances of at least a second wearable apparatus including a second kinematics sensor module.

Wireless synchronized apparatus and system

Disclosed embodiments include a method and an apparatus for monitoring sleep apnea severity that comprise: (a) analyzing an oxygen saturation signal to extract a plurality of time-domain and frequency-domain metrics; (b) calculating an oxygen saturation-based Apnea Hyponea Index (AHI) by employing a predetermined functional mapping between said metrics and polysomnography (PSG)-based AHI; and (c) displaying an oxygen saturation-based AHI to enable a specialist to monitor sleep apnea severity without requiring PSG. According to a particular embodiment, the oxygen saturation signal is nocturnal oxygen saturation and the functional mapping is a multilinear regression model (MLR) or a multilayer perceptron network (MLP).

Method and apparatus for monitoring sleep apnea severity

Disclosed embodiments include an apparatus for generating a plurality of movement impairment indices from one or more kinematic signals to characterize movement disorders. Additionally we disclose methods for generating a plurality of movement impairment indices from one or more kinematic signals obtained from one or more kinematic sensors, said methods implemented in a digital computer with one or more processors in order to characterize movement disorders based on spectral analysis, regularity metrics, and time-frequency analysis.

Method and apparatus for continuous measurement of motor symptoms in parkinson's disease and essential tremor with wearable sensors

Disclosed embodiments include a method for automatic identification of activity and rest periods based on an actigraphy signal. According to an embodiment, the method comprises (a) applying one or more filters to the actigraphy signal to generate a filtered actigraphy signal, and (b) comparing the filtered actigraphy signal against an adaptive threshold to generate an output signal corresponding to the activity and rest periods. The method can be implemented as part of a medical apparatus or medical system for automatic activity/rest identification from actigraphy signals.

Method and system for activity/rest identification

Disclosed embodiments include a method for measuring non-invasive blood pressure from an oscillometric signal and a cuff pressure signal implemented in a medical apparatus comprising: (a) calculating a pulse pressure signal by subtracting an upper and a lower envelope of the oscillometric signal; and (b) calculating without the use of beat detection a mean arterial pressure, a systolic blood pressure, and a diastolic blood pressure from said oscillometric signal, said cuff pressure signal, and a plurality of thresholds a device with at least one processor.

Method for blood pressure measurement from noninvasive oscillometric pressure signals

Disclosed embodiments include a complete system and platform which allows for continuous monitoring of movement disorders during normal daily activities in the clinic, home, and other normal daily environments. The system comprises: 1) a wearable apparatus for continuous monitoring of movement disorders, 2) a docking station, 3) a web server, and 4) methods for statistical analysis that generate movement impairment measures. Disclosed embodiments include a wearable movement monitoring apparatus comprising of (a) a sensor module including a plurality of low power micro-electromechanical systems kinematics sensors; (b) a microprocessor module including a low power microcontroller configured for device control, device status, and device communication; (c) a data storage module including a solid state local storage medium; (d) a wireless communication module including a low power surface mount transceiver and an integrated antenna; and (e) a power and docking module including a battery, an energy charging regulator circuit, and a docking connector.

System and apparatus for continuous monitoring of movement disorders

A patient monitoring device that combines physiological data collection with actigraphy data collection and associates the physiological data with synchronous actigraphy data. A method for processing actigraphy data by calculating absolute difference vectors of actigraphy signal vectors.

Ambulatory patient monitoring apparatus, system and method

Disclosed embodiments include a method for automatic detection of sleep apnea implemented in a medical apparatus, the method comprising (a) extracting a plurality of signal features by analyzing an oxygen saturation signal, (b) performing dimensionality reduction on the plurality of signal features to generate a plurality of signal features in a transformed space; and (c) displaying a sleep apnea diagnosis result based on a statistical classifier that operates on the plurality of signal features in a transformed space.

Method, system, and apparatus for automatic detection of obstructive sleep apnea from oxygen saturation recordings

Disclosed embodiments include a movement monitoring apparatus comprising a wireless synchronization scheme. Depending on the particular embodiment such wireless synchronization scheme is a master synchronization scheme or a mesh synchronization scheme. Additionally, in a particular embodiment, the movement monitor further comprises a robust wireless data transfer data controller. The disclosure includes a description of the complete system, namely, the wireless synchronized movement monitors with robust data transfer capabilities, the docking station, the access point, and the computer-implemented analysis system.

Wireless synchronized movement monitoring apparatus and system

Methods and apparatus for determining a cardiac parameter from cardiovascular pressure signals including arterial blood pressure (ABP) and the photoplethysmographic signal to quantify the degree of amplitude modulation due to respiration and predict fluid responsiveness are disclosed. Disclosed embodiments include a method for assessing fluid responsiveness implemented in a digital computer with one or more processors comprising: (a) measuring a cardiovascular signal, and (b) computing a dynamic index predictive of fluid responsiveness from said cardiovascular signal using a nonlinear state space estimator. According to one particular embodiment, and without limitation, the nonlinear state space estimator is based on a model for cardiovascular signals such as arterial blood pressure or plethysmogram signals, and employs a marginalized particle filter to estimate a dynamic index predictive of fluid responsiveness that is substantially equivalent to a variation in pulse pressure of said cardiovascular signal.

Method and apparatus for assessment of fluid responsiveness

The invention disclosed includes a method and apparatus for calculation of T-wave alternas in electrocardiographic (ECG) signals; said method comprises the following method steps: (a) collecting and storing an ECG signal; (b) detecting each heartbeat T-wave in the ECG signal using an automatic detection and segmentation algorithm; (c) classifying said heartbeat T-wave as an even or odd heartbeat T-wave; (d) initializing said method by taking the first even and the first odd heartbeat T-wave as their respective initial average; (e) processing all the heartbeat T-waves in the ECG signal to generate an even heartbeat T-wave weighted average and odd heartbeat T-wave weighted average; and (f) calculating TWA using a distance metric between the even heartbeat weighted average and the odd heartbeat weighted average, said distance metric including curve matching Continuous Dynamic Time Warping (CDTW).

Method and apparatus for automatic analysis of T-wave alternans

Disclosed embodiments include a telemedicine communication system designed to make possible 'virtual' patient visits by approved visitors such as the spouse, family, and friends of the hospitalized patient having the appropriate digital certificate and visitation/communication permissions. According to one embodiment, the system enables relatives to visit hospitalized patients using audiovisual communication modalities selected according to the severity and health status of the patient. Additionally, the system provides functionality to enable approved relatives to follow the health status of the patient according to their permissions.

Communication system for remote patient visits and clinical status monitoring

The present invention discloses a method and related apparatus for determining a cardiac parameter from either the arterial blood pressure signal or the photoplethysmographic signal to quantify the degree of amplitude modulation due to respiration (pulse pressure variation) and predict fluid responsiveness. The method involves the application of Lempel-Ziv complexity to a filtered and segmented physiologic signal for direct determination of the fluid status of a patient. Real-time monitoring of fluid status involves the implementation of the disclosed method as part of a bedside monitoring apparatus.

Method and apparatus for evaluation of fluid responsiveness

Wearable movement monitor docket station

Wireless access point

Growing community of inventors

Beaverton, OR, United States of America

Pedro Mateo Riobo Aboy