# US 10,244,976 B2 · Device for measuring muscle signals

> Agents: this data is available as JSON from the patentgrep API and MCP server — see https://patentgrep.com/llms.txt

- Number: US 10,244,976 B2
- Document ID: US10244976B2
- Status: Granted
- Kind: B2
- Application number: 15/738,920
- Filed: 2015-06-22
- Published: 2018-06-28
- Granted: 2019-04-02
- Earliest claimed: 2015-06-22
- Assignees: Fibrux Oy
- Applicants: Fibrux Oy
- Inventors: Mika Herrala; Markku Vimpari; Pasi Tavi; Juha Lampela
- Web page: https://patentgrep.com/patent/US10244976B2

## CPC

- G16H 20/30: relating to physical therapies or activities, e.g. physiotherapy, acupressure or exercising
- A61B 5/0004: {characterised by the type of physiological signal transmitted}
- A61B 5/222: {combined with detection or measurement of physiological parameters, e.g. heart rate}
- A61B 5/224: {Measuring muscular strength}
- A61B 5/296: for electromyography [EMG]
- A61B 5/397: Analysis of electromyograms
- A61B 5/4519: {Muscles (measuring muscular strength A61B5/224; using electromyography [EMG] A61B5/389)}
- A61B 5/7257: {using Fourier transforms}
- A63B 22/0605: {performing a circular movement, e.g. ergometers}
- A63B 71/0622: {Visual, audio or audio-visual systems for entertaining, instructing or motivating the user}
- A61B 5/0024: {for multiple sensor units attached to the patient, e.g. using a body or personal area network}
- A61B 5/1108: {of excised organs, e.g. muscle preparations}
- A61B 5/6831: {Straps, bands or harnesses}
- A61B 5/6833: {Adhesive patches}
- A61B 5/726: {using Wavelet transforms}
- A61B 2503/10: Athletes
- A61B 2505/09: Rehabilitation or training
- A61B 2560/0443: Modular apparatus
- A61B 2560/0462: Apparatus with built-in sensors
- 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)}
- 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)}
- A63B 2024/0093: {the load of the exercise apparatus being controlled by performance parameters, e.g. distance or speed}
- A63B 2071/063: {Spoken or verbal instructions}
- A63B 2220/30: Speed
- A63B 2220/34: Angular speed
- A63B 2220/40: Acceleration
- A63B 2220/44: Angular acceleration
- A63B 2220/51: Force
- A63B 2220/64: Frequency, e.g. of vibration oscillation
- A63B 2225/02: Testing, calibrating or measuring of equipment
- A63B 2230/085: used as a control parameter for the apparatus
- A63B 2230/60: muscle strain, i.e. measured on the user
- G16H: HEALTHCARE INFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR THE HANDLING OR PROCESSING OF MEDICAL OR HEALTHCARE DATA
- A61B: DIAGNOSIS; SURGERY; IDENTIFICATION (usefulness limited to only animals A61D)
- A63B: APPARATUS FOR PHYSICAL TRAINING, GYMNASTICS, SWIMMING, CLIMBING, OR FENCING; BALL GAMES; TRAINING EQUIPMENT (apparatus for passive exercising, massage A61H)

## 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

### Claim 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.

### Claim 2 (depends on 1)

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.

### Claim 3 (depends on 1)

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.

### Claim 4 (depends on 1)

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.

### Claim 5 (depends on 1)

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.

### Claim 6 (depends on 1)

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.

### Claim 7 (depends on 1)

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.

### Claim 8 (depends on 1)

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.

### Claim 9 (depends on 1)

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.

### Claim 10 (depends on 1)

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.

### Claim 11 (depends on 1)

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.

### Claim 12 (depends on 10)

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.

### Claim 13 (depends on 11)

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.

### Claim 14 (depends on 1)

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.

### Claim 15 (depends on 14)

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.

### Claim 16 (depends on 14)

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.

### Claim 17 (depends on 15)

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.

### Claim 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.

### Claim 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.
