Medtronic, Inc.

Patrick Scholten

Mattias Rouw

Willem Boute

Giorgio Corbucci

Josephus P A Smit

Harry Bernardus Antonius Kerver

Henricus W M De Bruyn

Josephus Smit

Harry Bernardus-Antonius Kerver

A three-axis accelerometer signal is used in a medical device for detecting that a patient has fallen. The accelerometer signal is sampled at a low sampling rate for determining a patient position. The accelerometer signal is sampled at a high sampling rate for determining an acceleration magnitude in response to determining the patient position. The patient position and acceleration magnitude are used to detect that a patient has fallen.

Fall detection algorithm utilizing a three-axis accelerometer

An implantable medical device and associated method predict syncope based on detecting a change in ejection time. A physiological signal is sensed that is responsive to mechanical changes associated with the cardiac ejection phase. A time interval corresponding to cardiac ejection time is detected from the physiological signal. A sudden change in the time interval is used as a predictor of syncope and causes a patient alert to be generated in response to the detected change.

System and method to monitor ejection time and QT interval to alert patients before syncopal events

Waveform analysis is used to identify and distinguish components of a sensed input signal, such as P-wave and Far Field R-wave signal components present in a sensed cardiac signal, even when the components are so closely spaced in time that the overlap to create a distorted input signal. A set of composite waveforms are generated by superimposing waveform templates of the signal components with different time delays or degree of overlap. Form parameters for each composite waveform are derived and mapped in a multidimensional map, from which form parameter boundaries are derived. Waveform data is collected from an input signal during a sensed event time window, and form parameters for the input signal waveform are derived. An output identifying the signal component of interest (e.g., a P-wave) and its location within the sensed event time window is produced based upon the set of form parameters of the input signal waveform and the form parameter boundaries.

Form parameter forecaster for analyzing signals distorted by noise

An implantable medical device having a prioritized multiplexor sensing circuit used for monitoring the condition or status of a patient. The device includes patient parameter sensors, such as electrodes, that are monitored for indications of significant events. Sensors indicating the presence of significant events may then be monitored more often than the other sensors.

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Lettele, Netherlands

Patrick Scholten