Fully ambulatory, self-contained gait monitor

• US 20080053253A1
• Filed: 08/31/2007
• Published: 03/06/2008
• Est. Priority Date: 09/06/2006
• Status: Abandoned Application

• Current Assignee: Individual Monitoring Systems Incorporated
• Original Assignee: Individual Monitoring Systems Incorporated
• Inventors: MacDougall, Hamish G., Allen, Roberta, Moore, Steven T.
• Application Number:
  US11/897,722
• Publication Number:
  US 20080053253A1
• Time in Patent Office: Days
• US Class Current: 73/865.4
• CPC Class Codes: A61B 5/1038 Measuring plantar pressure during gait
• CPC Class Codes: A61B 5/4082 Diagnosing or monitoring movement diseases, e.g. Parkinson, Huntington or Tourette
• CPC Class Codes: A61B 5/6828 Leg

Abstract

A gait monitoring device for recording and assessing, with the use of a personal computer, the gait characteristics of one wearing the device, includes: (a) a transducer array for sensing the temporal variation in the vertical acceleration and angular velocity of the motion of the shank of a wearer, (b) an analog to digital converter for sampling the data sensed by the transducer array, (c) a microprocessor having embedded programmable memory, (d) a sampled data storage means, (e) firmware for controlling the operation of the microprocessor to sample the output of the transducer array at a prescribed time interval and to temporarily store the sampled data, (f) a USB interface that allows for the downloading of the stored data to the personal computer, and (g) software for controlling a personal computer in the analysis of the collected data.

Claims

1. A gait monitoring device for recording and assessing, with the use of a personal computer, the gait characteristics of one wearing said device, said device comprising:

a means for sensing the temporal variation in the vertical acceleration and angular velocity of the motion of said wearer at the location where said device is being worn,

an analog to digital converter connected to said sensing means for sampling the data sensed by said motion sensing means,

a microprocessor connected to said converter, said microprocessor having embedded programmable memory,

a means for storing said sampled data,

a firmware means for controlling the operation of said microprocessor to 1 s sample the output of said sensing means at a prescribed time interval and to temporarily store said sampled data in said data storage means, and

a means for transferring said stored data to said personal computer.

2. The gait monitoring device as recited in claim 1, wherein said device configured so as to be worn on the shank of said wearer.

3. The gait monitoring device as recited in claim 1, further comprising a software means for controlling the operation of said personal computer to analyze said sampled data to determine said gait characteristics of said wearer.

4. The gait monitoring device as recited in claim 2, further comprising a software means for controlling the operation of said personal computer to analyze said sampled data to determine said gait characteristics of said wearer.

5. The gait monitoring device as recited in claim 3, wherein said software means is configured so as to analyze gait characteristics chosen from the group consisting of:

a) the length of every stride taken by a wearer over an extended period of time, b) the variability in said stride lengths over said period of time, c) the times during said period when the length of said strides are less than a defined percentage of what can be computed to be the baseline value of said stride lengths, d) the impact on said stride lengths by the consumption of a dose of medication by said wearer, or e) the frequency spectra of said vertical accelerations and the identification of episodes of “

freezing gait”

in said wearer'"'"'s movements.

6. The gait monitoring device as recited in claim 4, wherein said software means is configured so as to analyze gait characteristics chosen from the group consisting of:

a) the length of every stride taken by a wearer over an extended period of time, b) the variability in said stride lengths over said period of time, c) the times during said period when the length of said strides are less than a defined percentage of what can be computed to be the baseline value of said stride lengths, d) the impact on said stride lengths by the consumption of a dose of medication by said wearer, or e) the frequency spectra of said vertical accelerations and the identification of episodes of “

freezing gait”

in said wearer'"'"'s movements.

7. The gait monitoring device as recited in claim 5, wherein said software means includes a calibration algorithm in said stride length analysis that accounts for the forward motion of said wearer'"'"'s body over the foot making said stride.

8. The gait monitoring device as recited in claim 6, wherein said software means includes a calibration algorithm in said stride length analysis that accounts for the forward motion of said wearer'"'"'s body over the foot making said stride.

9. The gait monitoring device as recited in claim 1, wherein said sensing means including a transducer array that includes an accelerometer and a gyroscopic sensor.

10. The gait monitoring device as recited in claim 8, further comprising a means for temporally indicating the occurrence, during said monitoring, of an event that is relevant to the analysis of said gait characteristics.

11. A method for recording and assessing, with the use of a personal computer, the gait characteristics of an individual of interest, said method comprising the steps of:

sensing the temporal variation in the vertical acceleration and angular velocity of the motion at a specified location on said individual,

sampling with an analog to digital converter at a prescribed frequency said sensed accelerations and angular velocities,

storing said sampled data,

controlling said sensing, sampling and data storage with a microprocessor having embedded programmable memory, and

transferring said stored data to said personal computer.

12. The method as recited in claim 11, wherein said specified location is on the shank of said individual.

13. The method as recited in claim 11, further comprising the step of controlling, with appropriate software, the operation of said personal computer to analyze said sampled data to determine said gait characteristics of said individual.

14. The method as recited in claim 12, further comprising the step of controlling, with appropriate software, the operation of said personal computer to analyze said sampled data to determine said gait characteristics of said individual.

15. The method as recited in claim 13, wherein said analysis of said gait characteristics includes characteristics chosen from the group consisting of:

a) the length of every stride taken by a wearer over an extended period of time, b) the variability in said stride lengths over said period of time, c) the times during said period when the length of said strides are less than a defined percentage of what can be computed to be the baseline value of said stride lengths, d) the impact on said stride lengths by the consumption of a dose of medication by said wearer, or e) the frequency spectra of said vertical accelerations and the identification of episodes of “

freezing gait”

in said wearer'"'"'s movements.

16. The method as recited in claim 14, wherein said analysis of said gait characteristics includes characteristics chosen from the group consisting of:

a) the length of every stride taken by a wearer over an extended period of time, b) the variability in said stride lengths over said period of time, c) the times during said period when the length of said strides are less than a defined percentage of what can be computed to be the baseline value of said stride lengths, d) the impact on said stride lengths by the consumption of a dose of medication by said wearer, or e) the frequency spectra of said vertical accelerations and the identification of episodes of “

freezing gait”

in said wearer'"'"'s movements.

17. The method as recited in claim 15, wherein said analysis includes using a calibration algorithm in said stride length analysis that accounts for the forward motion of said wearer'"'"'s body over the foot making said stride.

18. The method as recited in claim 16, wherein said analysis includes using a calibration algorithm in said stride length analysis that accounts for the forward motion of said wearer'"'"'s body over the foot making said stride.

19. The method as recited in claim 11, wherein said sensing step includes utilizing a transducer array that includes an accelerometer and a gyroscopic sensor.

20. The method as recited in claim 18, further comprising the step of utilizing a means for temporally indicating the occurrence, during said monitoring, of an event that is relevant to the analysis of said gait characteristics.