Abstract: A system includes at least one processor and at least one memory storing program instructions that, when executed by the at least one processor, cause the system to send an acoustic ranging transmitter signal between a plurality of calibration reference positions and at least one anchor point, receive an acoustic ranging receiver signal associated with the acoustic ranging transmitter signal and with distances between the plurality of calibration reference positions and the at least one anchor point, and estimate a speed of sound based on the acoustic ranging receiver signal.

Abstract: A system includes at least one processor and at least one memory storing program instructions that, when executed by the at least one processor, cause the system to send an acoustic ranging transmitter signal between a plurality of calibration reference positions and at least one anchor point, receive an acoustic ranging receiver signal associated with the acoustic ranging transmitter signal and with distances between the plurality of calibration reference positions and the at least one anchor point, and estimate a speed of sound based on the acoustic ranging receiver signal.

Abstract: 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.

Abstract: 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.

Abstract: 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.

Abstract: A peripheral arterial flow obstruction detection system for providing a predictive diagnosis correlating to the diagnosis peripheral arterial disease. The system includes a host computer and a sensor used to detect and measure a physiological signal from a subject's finger or toe, such as the measurement of a signal using photoplethysmography using a PPG sensor. Sensor data is processed and filtered before being used to calculate a number of time-domain and frequency-domain calculations corresponding to the signal waveform. The calculations are used in a predictive model using a multi-faceted algorithm to provide a predictive diagnosis that is displayed on an indicator such as a monitor.

Abstract: 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.

Abstract: Disclosed embodiments relate to methods, apparatuses, and systems for characterizing gait. Specifically, disclosed embodiments are related methods, apparatuses, and systems for characterizing gait with wearable and wirelessly synchronized inertial measurement units. These include a method for gait characterization that comprises (a) detecting zero-velocity periods using two or more wearable and wirelessly synchronized movement monitoring devices including a triaxial accelerometer and a triaxial gyroscope and (b) calculating temporal measures of gait during walking by estimating the change in position and orientation during each step.

Abstract: 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.

Abstract: 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.

Abstract: Disclosed embodiments of the invention include a method, system, and apparatus to monitor cardiovascular signals such as arterial blood pressure (ABP), pulse oximetry (POX), and intracranial pressure (ICP). The system can be used to calculate and monitor useful clinical information such as heart rate, respiratory rate, pulse pressure variation (PPV), harmonic phases, pulse morphology, and for artifact removal. The method uses a statistical state-space model of cardiovascular signals and a generalized Kalman filter (EKF) to simultaneously estimate and track the cardiovascular parameters of interest such as the cardiac fundamental frequency and higher harmonics, respiratory fundamental frequency and higher harmonics, cardiac component harmonic amplitudes and phases, respiratory component harmonic amplitudes and phases, and PPV.

Abstract: Disclosed embodiments include a movement monitoring system and apparatus for objective assessment of movement disorders of a subject, comprising (a) one or more movement monitors, and (b) a computer-implemented analysis system comprising one or more protocols and associated data analysis methods to objectively quantify movement disorders based on movement data acquired by the movement monitors. According to one embodiment, the movement monitors are robust wireless synchronized movement monitors and the protocols include one or more tests for assessment of neural control of balance.

Abstract: 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.

Abstract: Disclosed embodiments include a system for objective assessment of motor signs at the extremities that comprises (a) a device for objective motor sign measurement, (b) a test protocol defining a prescribed repetitive activity, and (c) a signal processing and analysis system to generate one or more impairment metrics. According to a particular embodiment, the device for objective motor sign measurement is characterized by including means for producing a continuous measure of position of a limb or extremity during said prescribed repetitive activity during the entire movement.

Abstract: 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.

Abstract: Disclosed embodiments include a system for managing clinical data comprising: (a) a server configured to receive data from one or more external devices, and (b) a clinical data management application comprising one module for storing raw movement data received directly from at least one external device. The system is especially adapted for research in movement disorders and contains modules for investigators, collaborators, clinical subjects, and objective devices to upload movement disorders data, analyze data, obtain results of automatic analysis, publish results, and collaborate with other investigators.