Calculating heart rate from acceleration signals containing cardiac activity signals

• US 9,462,956 B2
• Filed: 03/24/2015
• Issued: 10/11/2016
• Est. Priority Date: 01/25/2008
• Status: Active Grant

• Current Assignee: Texas Instruments, Inc.
• Original Assignee: Texas Instruments, Inc.
• Inventors: Pandia, Keya R., Ravindran, Sourabh, Cole, Edwin Randolph
• Primary Examiner(s): Holmes, Rex R
• Application Number:
  US14/667,160
• Publication Number:
  US 20150196213A1
• Time in Patent Office: 567 Days
• US Class Current: 1/1
• CPC Class Codes: A61B 2505/07 Home care
• CPC Class Codes: A61B 2560/0475 Special features of memory means, e.g. removable memory cards
• CPC Class Codes: A61B 2562/0219 Inertial sensors, e.g. accelerometers, gyroscopes, tilt switches
• CPC Class Codes: A61B 2562/028 Microscale sensors, e.g. electromechanical sensors [MEMS]
• CPC Class Codes: A61B 5/029 Measuring or recording blood output from the heart, e.g. minute volume A61B8/065 takes precedence
• CPC Class Codes: A61B 5/1102 Ballistocardiography
• CPC Class Codes: A61B 5/113 occurring during breathing
• CPC Class Codes: A61B 5/316 Modalities, i.e. specific diagnostic methods
• CPC Class Codes: A61B 5/318 Heart-related electrical modalities, e.g. electrocardiography [ECG]
• CPC Class Codes: A61B 5/6831 Straps, bands or harnesses
• CPC Class Codes: A61B 5/7207 of noise induced by motion artifacts
• CPC Class Codes: A61B 5/725 using specific filters therefor, e.g. Kalman or adaptive filters A61B5/316 take precedence
• CPC Class Codes: A61B 5/7278 Artificial waveform generation or derivation, e.g. synthesising signals from measured signals A61B5/327 takes precedence
• CPC Class Codes: A61B 7/00 Instruments for auscultation
• CPC Class Codes: A61B 7/008 Detecting noise of gastric tract, e.g. caused by voiding

Abstract

A heart monitor includes a single chest accelerometer (210), an analog signal conditioning and sampling section (215) responsive to said accelerometer to produce a digital signal substantially representing acceleration, and a digital processor (220) operable to filter the acceleration signal into a signal affected by body motion and to cancel the body motion signal from the acceleration signal, thereby to produce an acceleration-based cardiac-related signal. Other processes and electronic systems are also disclosed.

Claims

1. A process of operating a data acquisition and signal processing unit comprising:

A. receiving acceleration signals that contain cardiac activity signals at an input of the unit;

B. digitally low pass filtering the acceleration signals with a filter cutoff of substantially a power line frequency to obtain filtered accelerometer signals;

C. decimating the filtered accelerometer signals by a factor of 10 to obtain decimated filtered accelerometer signals, x(i);

D. Savitzky-Golay polynomial smoothing filtering the decimated filtered accelerometer signals to obtain relatively slow-varying motion wander signals g(i);

E. subtracting the slow-varying motion wander signals g(i) from the decimated filtered accelerometer signals, x(i) to obtain heart sound signals S1 and S2, r(i);

F. generating envelope-processed residue signals R(i) from the heart sound signals S1 and S2, r(i);

G. performing a folded correlation process of the envelope-processed residue signals R(i) to obtain folded correlation signals fc(i);

H. locating peaks of the folded correlation signals fc(i) using an electronic amplitude-based peak picking process;

I. counting the peaks to calculate heart rate signals; and

J. providing calculated heart rate signals to an output of the unit.

2. The process of claim 1 in which digitally low pass filtering the acceleration signals includes filtering with a rolloff frequency less than 60 Hertz to attenuates 60 Hertz power line interference, and a rolloff frequency less than 50 Hertz to attenuate using 50 Hertz power line interference.

3. The process of claim 1 including processing the residue signals R(i) in overlapping frames indexed (i).

4. The process of claim 1 in which the Savitzky-Golay polynomial smoothing filtering uses 28th order and 401 point frame.

5. The process of claim 1 in which the folded correlation process includes folding heart monitoring residue samples R(i) from the later half of a frame around the center heart monitoring sample R(i) in the frame and multiplied by dot product with heart monitoring residue samples R(i) in the earlier half of the frame to obtain an instant (i) of an input residue signal stream R(i) in the center of the frame.

6. The process of claim 1 including performing at least some of the steps on a computer.