System and method for processing signals for the real-time detection of a functional cyclic activity

• US 8,897,867 B2
• Filed: 04/06/2010
• Issued: 11/25/2014
• Est. Priority Date: 04/07/2009
• Status: Expired due to Fees

• Current Assignee: Assistance Publique - Hopitaux De Paris, Université Grenoble Alpes
• Original Assignee: Assistance Publique - Hopitaux De Paris
• Inventors: Heyer, Laurent, Gumery, Pierre-Yves
• Primary Examiner(s): D'ANGELO, MICHAEL J
• Application Number:
  US13/263,180
• Publication Number:
  US 20120095742A1
• Time in Patent Office: 1,694 Days
• Field of Search: None
• US Class Current: 600/546
• CPC Class Codes: A61B 5/08 Detecting, measuring or recording devices for evaluating the respiratory organs A61B5/0205 takes precedence
• CPC Class Codes: A61B 5/389 Electromyography [EMG]
• CPC Class Codes: A61B 5/4818 Sleep apnoea

Abstract

A system and method for processing signals for the real-time detection of a functional cyclic activity, include: elements for simultaneously receiving signals acquired by a sensor array having at least two sensors; elements for recording and preprocessing the acquired signals during a plurality of consecutive cycles; elements for identifying event combinations from the recordings of the acquired signals, enabling a calibration to be carried out, including: elements for identifying a plurality of events in the acquired signals, each signal including an identified event; elements for defining a model of the functional activity, consisting of a time order of the events and the mean delays between the events, and elements for defining a detection time window from the functional activity model.

Claims

1. A system for processing signals for the real-time detection of a cyclic functional activity, the processing system comprising:

a signal acquisition means forming an instrumental network including at least two sensors;

one or more processing devices configured to;

simultaneously receive signals acquired by the signal acquisition means,

record and preprocess the acquired signals during a plurality of consecutive processing cycles,

identify event combinations from recordings from the acquired signals, enabling a calibration to be carried out by the one or more processing devices, the calibration being carried out by;

identifying a plurality of events in the acquired signals, each one of the events corresponding to an activation of a muscle and each acquired signal of the signal acquisition means including a plurality of identified events,

defining a model of the cyclic functional activity, the model being a timing chart consisting of a time order of the plurality of identified events and mean delays between the identified events,

defining a detection time window from the model of the cyclic functional activity, and

detecting events into the detection time window taking into account the model of the cyclic functional activity; and

a monitoring device configured to monitor the cyclic functional activity for a last full cycle, the monitoring device configured to;

calculate a sliding mean of the delays between the events detected into the signals acquired during a plurality of consecutive monitoring cycles, the plurality of consecutive monitoring cycles comprising the last full cycle,

display the sliding mean of the delays,

compare the sliding mean of the delays to the mean of the delays calculated during the calibration in order to detect an anomaly, and

generate and transmit an alert signal when the anomaly is detected.

2. The processing system according to claim 1, wherein the plurality of consecutive processing cycles includes ten to twenty cycles.

3. The processing system according to claim 1, wherein the one or more processing devices is configured to validate the sensor array, by

calculating match scores for one or more pairs of the acquired signals, and

comparing each of the calculated match scores of each of the pairs of the acquired signals to a threshold value.

4. The processing system according to claim 1, wherein the plurality of consecutive monitoring cycles is smaller than the plurality of consecutive processing cycles.

5. The processing system according to claim 1, wherein the signal acquisition means are cardiac muscular signal acquisition means.

6. The processing system according to claim 1, wherein the signal acquisition means are cardiac skeletal muscular signal acquisition means.

7. The processing system according to claim 1, wherein the signal acquisition means are respiratory muscular signal acquisition means.

8. The processing system according to claim 1, wherein the signal acquisition means are noninvasive acquisition means.

9. The processing system according to claim 7, further comprising a complementary processing device configured to:

receive a signal of ventilatory activity of a patient comprising a ventilatory event;

detect, in real-time, a ventilatory demand, the ventilatory demand being defined by an ordered succession of the ventilatory event and respiratory events identified using the respiratory activity model and detected in the acquired muscular signals, and

generate and transmit a control signal to a respiratory aid device connected to the patient.

10. The processing system according to claim 7, wherein the complementary processing device is configured to acquire information relative to the status of the respiratory aid device and compare that information relative to the respiratory aid device and the detection of the patient'"'"'s respiratory activity.