METHOD, APPARATUS, AND SYSTEM FOR CHARACTERIZING GAIT

• US 20140066816A1
• Filed: 06/17/2013
• Published: 03/06/2014
• Est. Priority Date: 12/07/2008
• Status: Abandoned Application

• Current Assignee: Wearables IP Holdings LLC
• Original Assignee: APDM, Inc.
• Inventors: McNames, James, Riobo Aboy, Pedro Mateo, Greenberg, Andrew, Gallino, Gavin, Brandon, Timothy, Pearson, Sean, Holmstrom, Lars
• Application Number:
  US13/920,032
• Publication Number:
  US 20140066816A1
• Time in Patent Office: Days
• US Class Current: 600/595
• 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 5/0004 characterised by the type of physiological signal transmitted
• CPC Class Codes: A61B 5/002 Monitoring the patient using a local or closed circuit, e.g. in a room or building A61B5/0017 takes precedence
• CPC Class Codes: A61B 5/0024 for multiple sensor units attached to the patient, e.g. using a body or personal area network
• CPC Class Codes: A61B 5/1101 Detecting tremor
• CPC Class Codes: A61B 5/112 Gait analysis
• CPC Class Codes: A61B 5/4082 Diagnosing or monitoring movement diseases, e.g. Parkinson, Huntington or Tourette
• CPC Class Codes: A61B 5/6831 Straps, bands or harnesses
• CPC Class Codes: A61B 5/7246 using correlation, e.g. template matching or determination of similarity
• CPC Class Codes: A61B 5/7257 using Fourier transforms
• CPC Class Codes: H04L 1/08 by repeating transmission, e.g. Verdan system H04L1/1858 and H04L1/189 take precedence
• CPC Class Codes: H04W 56/002 Mutual synchronization

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.

Claims

1. A method for gait characterization comprising:

(a) detecting zero-velocity periods using two or more wearable and wirelessly synchronized movement monitoring devices, said movement monitoring devices comprising a triaxial accelerometer and a triaxial gyroscope with a bandwidth of at least 15 Hz; and

(b) calculating temporal measures of gait during walking by estimating the change in position and orientation during each step.

2. The method of claim 1, wherein said calculating temporal measures of gait includes performing template matching based on the magnitude of said accelerometer'"'"'s and said gyroscope'"'"'s signals from both feet.

3. The method of claim 2, wherein said template matching is characterized by 1) enabling multiple iterations to refine a final template, 2) weighting each template by the standard deviation of said template across detected steps, 3) scaling the template'"'"'s error to be equal to one when said movement monitoring devices are stationary, 5) using a fast method based on a fast Fourier transform configured for calculating the template'"'"'s matching error, or combinations thereof.

4. The method of claim 3, wherein said calculating temporal measures of gait further comprises:

a) detecting initial steps, b) estimating a gait cycle duration, c) building an initial template, d) calculating a template match, e) detecting initial template steps, f) validating steps, g) adding missed steps, or combinations thereof.

5. The method of claim 4, wherein calculating temporal measures of gait further comprises measuring asymmetry using time-proximate steps by combining left and right steps into consecutive left-right pairs.

6. The method of claim 5, wherein calculating temporal measures of gait further comprises characterizing gait during normal periods of walking by isolating sequences of steps in which the subject is traveling forward on a flat surface based on changes in height, bank angle, elevation angle, and heading angle.

7. The method of claim 6, wherein calculating temporal measures of gait further comprises generating an indicator of foot drop and fall risk by characterizing the pitch of the foot with wearable sensors at the moments of heel strike and toe-off.

8. The method of claim 7, wherein calculating temporal measures of gait further comprises characterizing the lateral deviation in a sequence of two steps resulting in three foot placements based on how far a middle foot placement deviates from a straight path from a first to a last foot placement.

9. The method of claim 8, wherein calculating temporal measures of gait further comprises measuring the lateral swing of the foot during a single step.

10. The method of claim 9, wherein said method comprises:

1) upsampling,

     2) estimating biases,

     3) calculating magnitudes,

     4) finding still periods,

     5) calculating positions,

     6) detecting steps,

     7) finding and validating step sequences, and

     8) calculating gait metrics.