Device for measuring muscle signals

• US 10,244,976 B2
• Filed: 06/22/2015
• Issued: 04/02/2019
• Est. Priority Date: 06/22/2015
• Status: Active Grant

• Current Assignee: Fibrux Oy
• Original Assignee: Fibrux Oy
• Inventors: Herrala, Mika, Vimpari, Markku, Tavi, Pasi, Lampela, Juha
• Primary Examiner(s): Hindenburg, Max
• Application Number:
  US15/738,920
• Publication Number:
  US 20180177447A1
• Time in Patent Office: 1,380 Days
• CPC Class Codes: A61B 2503/10 Athletes
• CPC Class Codes: A61B 2505/09 Rehabilitation or training
• CPC Class Codes: A61B 2560/0443 Modular apparatus
• CPC Class Codes: A61B 2560/0462 Apparatus with built-in sensors
• CPC Class Codes: A61B 5/0004 characterised by the type of physiological signal transmitted
• 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 5/1108 of excised organs, e.g. muscle preparations
• CPC Class Codes: A61B 5/222 combined with detection or measurement of physiological parameters, e.g. heart rate
• CPC Class Codes: A61B 5/224 Measuring muscular strength
• CPC Class Codes: A61B 5/296 for electromyography [EMG]
• CPC Class Codes: A61B 5/316 Modalities, i.e. specific diagnostic methods
• CPC Class Codes: A61B 5/389 Electromyography [EMG]
• CPC Class Codes: A61B 5/4519 Muscles A61B5/389, A61B5/224 take precedence
• CPC Class Codes: A61B 5/6831 Straps, bands or harnesses
• CPC Class Codes: A61B 5/6833 Adhesive patches
• CPC Class Codes: A61B 5/7257 using Fourier transforms
• CPC Class Codes: A61B 5/726 using Wavelet transforms
• CPC Class Codes: A63B 2024/0093 the load of the exercise apparatus being controlled by performance parameters, e.g. distance or speed
• CPC Class Codes: A63B 2071/063 Spoken or verbal instructions
• CPC Class Codes: A63B 22/0056 the pivoting movement being in a vertical plane, e.g. steppers with a horizontal axis platforms for rocking motion about a horizontal axis A63B22/16
• CPC Class Codes: A63B 22/0076 : Rowing machines for conditioning the cardio-vascular system seats moving during exercise A63B22/0087; training appliances for rowing or sculling on boats A63B69/06
• CPC Class Codes: A63B 22/0605 : performing a circular movement, e.g. ergometers
• CPC Class Codes: A63B 2220/30 : Speed
• CPC Class Codes: A63B 2220/34 : Angular speed
• CPC Class Codes: A63B 2220/40 : Acceleration
• CPC Class Codes: A63B 2220/44 : Angular acceleration
• CPC Class Codes: A63B 2220/51 : Force
• CPC Class Codes: A63B 2220/64 : Frequency, e.g. of vibration oscillation
• CPC Class Codes: A63B 2225/02 : Testing, calibrating or measuring of equipment
• CPC Class Codes: A63B 2230/085 : used as a control parameter for the apparatus
• CPC Class Codes: A63B 2230/60 : muscle strain, i.e. measured on the user
• CPC Class Codes: A63B 71/0622 : Visual, audio or audio-visual systems for entertaining, instructing or motivating the user
• CPC Class Codes: G16H 20/30 : relating to physical therapies or activities, e.g. physiotherapy, acupressure or exercising

Abstract

A device or a system for measuring muscle signals. A system may include at least one processor, memory including computer program code, the memory and the computer program code configured to, with the at least one processor, cause the system to perform at least the following: measure a signal from a muscle to obtain a muscle activation signal; carry out at least one transform on the muscle activation signal to obtain a muscle activation spectrum; and determine a muscle state indicator from the muscle activation spectrum by using signal characteristics from a first and a second band of the muscle activation spectrum.

Claims

1. A system for guiding a user in an exercise, the system comprising at least one processor, memory including computer program code, and at least one sensor configured to detect a signal from a muscle of the user, the memory and the computer program code configured to, with the at least one processor, cause the system to perform at least the following:

measure the signal from the muscle provided by the sensor to obtain a muscle activation signal during at least one contraction of said muscle;

convert said muscle activation signal from the time domain to the frequency domain to obtain a muscle activation spectrum;

determine a first band and a second band from the muscle activation spectrum measured during a maximum voluntary contraction of the muscle;

determine first reference power values for said first band and said second band from the muscle activation spectrum that is measured during the maximum voluntary contraction;

use said first reference power values in determining a ratio of signal characteristics from said first band and said second band of said muscle activation spectrum;

determine a muscle state indicator from said muscle activation spectrum by using said ratio of signal characteristics from the first band and the second band of said muscle activation spectrum; and

guide the exercise using the determined muscle state indicator.

2. The system according to claim 1, wherein said signal characteristics comprise a power of said signal on said first band and on said second band, wherein the memory and the computer program code are further configured to cause the system to perform at least the following:

form a ratio between said signal characteristics of said first band and said signal characteristics of said second band.

3. The system according to claim 1, wherein the first band and the second band of said muscle activation spectrum are partially non-overlapping in frequency or completely non-overlapping in frequency.

4. The system according to claim 1, wherein the first band and the second band are determined at different time instances and are at least partially overlapping in frequency.

5. The system according to claim 1, wherein a width of said first band of said muscle activation spectrum is approximately 25% of an upper end of said muscle activation spectrum, wherein the upper end of said muscle activation spectrum is a point wherein power of said muscle activation spectrum falls to approximately 5% of maximum power.

6. The system according to claim 1, wherein a width of said second band of said muscle activation spectrum is approximately 40 Hz around a maximum power peak of said muscle activation spectrum.

7. The system according to claim 1, wherein said first band and said second band of said muscle activation spectrum are determined using a scale factor and the bands of a muscle activation spectrum of another muscle.

8. The system according to claim 1, the memory and the computer program code further configured to cause the system to perform at least the following:

determine first reference power values for said first band and said second band during the maximum voluntary contraction;

determine updated reference power values for said first reference power values during the exercise, wherein said updated reference power values are higher than said first reference power values; and

use said updated reference power values in determining the ratio of signal characteristics from said first band and said second band of said muscle activation spectrum.

9. The system according to claim 1, the memory and the computer program code further configured to cause the system to perform at least the following:

determine a time constant from a decay of a measured muscle signal power level; and

compute an estimate of recovery time based on said time constant.

10. The system according to claim 1, the memory and the computer program code further configured to cause the system to perform at least the following:

receive a type of exercise as an input, wherein said type of exercise is one or more of strength, speed or endurance;

determine at least one threshold value for guiding said exercise; and

guide said type of exercise using said muscle activation spectrum and said at least one threshold value.

11. The system according to claim 1, the memory and the computer program code further configured to cause the system to perform at least the following:

determine a type of exercise based on said muscle activation spectrum;

determine at least one threshold value for guiding said exercise; and

guide said type of exercise using said muscle activation spectrum and said at least one threshold value.

12. The system according to claim 10, the memory and the computer program code further configured to cause the system to perform at least the following:

determine at least one measurement result according to said type of exercise; and

display said at least one measurement result to the user.

13. The system according to claim 11, the computer program code further configured to cause the system to perform at least the following:

determine at least one measurement result according to said type of exercise; and

display said at least one measurement result to the user.

14. The system according to claim 1, further comprising at least one exercise device and the memory and the computer program code further causes the system to perform at least the following:

control said at least one exercise device based on said muscle state indicator.

15. The system according to claim 14, the memory and the computer program code further configured to cause the system to perform at least the following:

control resistance of said at least one exercise device based on said muscle state indicator.

16. The system according to claim 14, the memory and the computer program code further configured to cause the system to perform at least the following:

guiding the user of said at least one exercise device to control resistance of said at least one exercise device based on said muscle state indicator.

17. The system according to claim 15, the memory and the computer program code further causes the system to perform at least the following:

guiding the user of said at least one exercise device to control resistance of said at least one exercise device based on said muscle state indicator.

18. A computer program product embodied on a non-transitory computer readable medium, comprising computer program code configured to, when executed on at least one processor, cause an apparatus or a system to:

measure a signal from a muscle to obtain a muscle activation signal during at least one contraction of said muscle;

convert said muscle activation signal from the time domain to the frequency domain to obtain a muscle activation spectrum;

determine a first band and a second band from the muscle activation spectrum measured during a maximum voluntary contraction of the muscle;

determine first reference power values for said first band and said second band from the muscle activation spectrum that is measured during the maximum voluntary contraction;

use said first reference power values in determining a ratio of signal characteristics from said first band and said second band of said muscle activation spectrum;

determine a muscle state indicator from said muscle activation spectrum by using said ratio of signal characteristics from the first band and the second band of said muscle activation spectrum; and

guide the exercise using the determined muscle state indicator.

19. A method for determining a state of a muscle of a user and guiding the user in an exercise based on the determined state, the method comprising using a device that includes at least one processor, a memory including computer program code, and at least one sensor configured to detect a signal from the muscle, wherein execution of the computer program code by the processor is configured to cause the device to:

measure the signal from the muscle detected by the sensor using the processor to obtain a muscle activation signal during at least one contraction of said muscle;

convert said muscle activation signal from the time domain to the frequency domain to obtain a muscle activation spectrum;

determine a first band and a second band from the muscle activation spectrum measured during a maximum voluntary contraction of the muscle;

determine first reference power values for a first band and a second band from the muscle activation spectrum that is measured during a maximum voluntary contraction of the muscle;

use said first reference power values in determining a ratio of signal characteristics from said first band and said second band of said muscle activation spectrum;

determine a muscle state indicator from said muscle activation spectrum by using said ratio of signal characteristics from the first band and the second band of said muscle activation spectrum; and

guide the exercise based on the determined muscle state indicator.