COMPUTER ASSISTED ERGONOMIC WORKSTATION DESIGNS AND METHODS

• US 20150142381A1
• Filed: 10/21/2014
• Published: 05/21/2015
• Est. Priority Date: 08/19/2013
• Status: Active Grant

• Current Assignee: Ergonomics First, Inc.
• Original Assignee: Fitzsimmons And Associates
• Inventors: Fitzsimmons, John, Kouznetsov, Alexander
• Granted Patent: US 10,078,096 B2
• Time in Patent Office: Days
• US Class Current: 702/166
• CPC Class Codes: A47C 3/20 Chairs or stools with vertically-adjustable seats tables with variable height A47B9/00
• CPC Class Codes: A47C 31/126 for chairs
• CPC Class Codes: A47C 7/006 with castors
• CPC Class Codes: G01P 15/00 Measuring acceleration; Measuring deceleration; Measuring shock, i.e. sudden change of acceleration
• CPC Class Codes: G16H 20/30 relating to physical therapies or activities, e.g. physiotherapy, acupressure or exercising
• CPC Class Codes: G16H 20/40 relating to mechanical, radiation or invasive therapies, e.g. surgery, laser therapy, dialysis or acupuncture

Abstract

Aspects of this invention include new measures of hip—torso posture and strength of the legs. These new measures are made using new tools. Measurement of hip-torso posture can be made using simple tools. One such tool can be applied to the hips, and indicates relative angle of the spine. Photographic tools can be used to analyze posture relative to vertical references. Measurement of leg strength can be made using a device incorporating accelerometers and computer implemented instructions to quantify forward/backward, left/right, or rotational acceleration when the legs are challenged. Other aspects include devices with computer implemented instructions to quantify leg strength. Using the new devices and methods, one can objectively determine postures that are ergonomically appropriate for persons sitting and working at workstations.

Claims

1. A method for determining chair height of a subject seated in a chair at a workstation, comprising the steps:

a. providing a mobile computing device, having a processor, a memory, a plurality of accelerometers; and

a display;

b. affixing said mobile computing device to said chair;

c. adjusting the height of said chair to a first height;

d. instructing said subject to sit in said chair and rapidly move the chair using said subjects legs placed on the floor;

e. determining the maximum acceleration achieved during said moving in step d;

f. adjusting the height of said chair to a second height;

g. repeating steps d and e;

h. adjusting the height of said chair to a third height;

i. repeating steps d and e; and

j. displaying on the display, the maximum accelerations achieved versus chair height.

2. The method of claim 1, where said determining maximum acceleration in step e is carried out by said processor programmed to perform the steps:

i. said accelerometers providing gravity data for three dimensions of motion, an “

X”

dimension, a “

Y”

dimension, and a “

Z”

dimension, each of said dimensions being perpendicular to each of the other dimensions, said data being “

gravX”

, “

gravy”

, and “

gravZ”

, respectively, each expressed as the effective gravitational acceleration in each of said dimensions;

ii. sampling said gravity data at a frequency of about 1 time per second to about 40 times per second, and storing said data in said memory;

iii. updating said gravX, gravy and gravZ values where said updated values are calculated according to the following formulas;

gravX=alpha*gravX+(1−

alpha)*ev.x;

gravY=alpha*gravY+(1−

alpha)*ev.y;

gravZ=alpha*gravZ+(1−

alpha)*ev.z;

where alpha is a time interval for a low pass filter, ev.x, ev.y, and ev.z are new gravity data in the X, Y, and Z dimensions respectively;

iv. calculate acceleration by removing the gravity contribution using a high-pass filter according to the following formula;

accX=ev.x−

gravX;

accY=ev.y−

gravY;

accZ ev.z−

gravZ,

where accZ, accY, and accZ are accelerations in the X, Y, and Z dimensions, respectively; and

v. calculating for each time point, total linear acceleration (“

A”

) according to the formula;

A=(accX²+accY²+accZ²)^1/2; and

vi. storing said values of A in said memory.

3. The method of claim 2, where sampling rate of said gravity data is a frequency of about 10 times per second.

4. A method for determining optimum chair height of a subject seated in a chair at a workstation, comprising:

determining the height of said chair that produces the maximum acceleration according to claim 1, step j.

5. The method of claim 4, further comprising the steps:

establishing proper chair/caster/floor conditions; and

confirming neutral spine posture.

6. The method of claim 4, further comprising the steps:

measuring the height of the elbow and the eye of said subject; and

providing a keyboard tray at a location that maintains neutral spine posture.

7. The method of claim 2, further comprising the steps:

determining maximum acceleration as for step e of claim 1 calculated for a first seat pan angle; and

changing said seat pan angle to a second pan angle and repeating said step e of claim 1.

8. The method of claim 5, where said step of confirming neutral spine posture is carried out by measuring the angle inscribed by a first line connecting a lateral point on said subject'"'"'s waist over the lumbar spine and said subject'"'"'s shoulder, and a second line connecting a lateral point on said subjects waist over the lumbar spine to said subject'"'"'s ear, where said angle inscribed is less than about 20 degrees.

9. The method of claim 5, where said step of confirming neutral spine posture is carried out by the steps:

i taking a photograph of said subject seated in said chair; and

ii comparing the angle inscribed between a vertical line from said floor and a line connecting a lateral point on said subject'"'"'s waist over the lumbar spine and said subject'"'"'s ear, where said angle inscribed is less than about 15 degrees.

10. A computer processing device, comprising:

a processor for carrying out computer implemented instructions; and

a memory module containing programming instructions for carrying out the following steps;

i. accepting data from accelerometers providing gravity data for two or three dimensions of motion, an “

X”

dimension, a “

Y”

dimension, and optionally, a “

Z”

dimension, each of said dimensions being perpendicular to each of the other dimensions, said data being “

gravX”

, “

gravy”

, and “

gravZ”

, respectively, each expressed as the effective gravitational acceleration in each of said dimensions;

ii. sampling said gravity data at a frequency of about 1 time per second to about 40 times per second, and storing said data in said memory;

iii. updating said gravX, gravy and gravZ values where said updated values are calculated according to the following formulas;

gravX=alpha*gravX+(1−

alpha)*ev.x;

gravY=alpha*gravY+(1−

alpha)*ev.y;

gravZ=alpha*gravZ+(1−

alpha)*ev.z;

where alpha is a time interval for a low pass filter, ev.x, ev.y, and ev.z are new gravity data in the X, Y, and Z dimensions respectively, where alpha is between about zero (0) and about one (1);

iv. calculating acceleration by removing the gravity contribution using a high-pass filter according to the following formula;

accX=ev.x−

gravX;

accY=ev.y−

gravY;

accZ=ev.z−

gravZ,

where accZ, accY, and accZ are accelerations in the X, Y, and Z dimensions, respectively; and

v. calculating for each time point, total linear acceleration (“

A”

) according to the formula;

A=(accX²+accY²+accZ²)^1/2.

11. The computer processing device of claim 10, where alpha is between about 0.1 and about 0.9.

12. The computer processing device of claim 10, where alpha is between about 0.2 and about 0.8.

13. The computer processing device of claim 10, where alpha is between about 0.3 and about 0.7.

14. The computer processing device of claim 10, where alpha is between about 0.4 ad about 0.6.

15. The computer processing device of claim 10, where alpha is about 0.5.

16. The computer processing device of claim 10, further comprising:

a memory storage module;

a user interface; and

a display.