# US 2021/0330211 A1 · Exercise management method and system using electromyography sensor

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- Number: US 2021/0330211 A1
- Document ID: US20210330211A1
- Status: Published application
- Kind: A1
- Application number: 16/317,525
- Filed: 2017-06-29
- Published: 2021-10-28
- Earliest claimed: 2016-07-12
- Assignees: Hhs Co., Ltd.
- Applicants: Hhs Co.,Ltd.
- Inventors: Hyung Seob HAN; Kyoung Young SONG; Oh Guk KWON; Tae Young KIM
- Web page: https://patentgrep.com/patent/US20210330211A1

## CPC

- A61B 5/397: Analysis of electromyograms
- A61B 5/7246: {using correlation, e.g. template matching or determination of similarity}
- A63B 24/0062: {Monitoring athletic performances, e.g. for determining the work of a user on an exercise apparatus, the completed jogging or cycling distance}
- G09B 5/02: with visual presentation of the material to be studied, e.g. using film strip
- G09B 19/0038: {Sports}
- G16H 20/30: relating to physical therapies or activities, e.g. physiotherapy, acupressure or exercising
- G16H 40/67: for remote operation
- G16H 50/30: for calculating health indices; for individual health risk assessment
- A61B 5/0022: {Monitoring a patient using a global network, e.g. telephone networks, internet}
- A61B 5/256: Wearable electrodes, e.g. having straps or bands
- A61B 2503/10: Athletes
- H04L 67/12: specially adapted for proprietary or special-purpose networking environments, e.g. medical networks, sensor networks, networks in vehicles or remote metering networks
- 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)
- G09B: EDUCATIONAL OR DEMONSTRATION APPLIANCES; APPLIANCES FOR TEACHING, OR COMMUNICATING WITH, THE BLIND, DEAF OR MUTE; MODELS; PLANETARIA; GLOBES; MAPS; DIAGRAMS (devices for psychotechnics or for testing reaction times A61B5/16; games, sports, amusements A63; projectors, projector screens G03B)
- G16H: HEALTHCARE INFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR THE HANDLING OR PROCESSING OF MEDICAL OR HEALTHCARE DATA
- H04L: TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION (arrangements common to telegraphic and telephonic communication H04M)

## Abstract

Disclosed is an exercise guidance system using an electromyography sensor, the system including: a control server receiving exercise information by working in conjunction with a monitoring module, in which an exercise guidance application is installed, over a wired/wireless communication network, the control server providing analysis information on user's exercise; and a signal processing module receiving detection signals from multiple electromyography sensors attached on a user body, calculating muscle activity by analyzing the detection signals, and providing a result of the calculation to the monitoring module. According to the embodiment, the cost burden of personal training is reduced, and the monotony of exercising along is reduced. Also, there is no limitation of place and time because exercise is possible anywhere. Also, the electromyography sensor works in conjunction with the smartphone to provide visualization of the user's exercise volume, the user's muscles, and the like, thereby facilitating efficient exercising.

## Claims

### Claim 1

An exercise guidance system using an electromyography sensor, the system comprising:
a control server receiving exercise information by working in conjunction with a monitoring module, in which an exercise guidance application is installed, over a wired/wireless communication network, the control server providing analysis information on a user's exercise; and
a signal processing module receiving detection signals from the multiple electromyography sensors attached on a user body, calculating muscle activity by analyzing the detection signals, and providing a result of the calculation to the monitoring module.

### Claim 2 (depends on 1)

The system of claim 1, wherein the signal processing module comprises:
a signal analysis unit analyzing the detection signals and selecting both an intrinsic mode function (IMF) equal to or larger than a threshold value and a subband with a maximum rate of change; and
a feature extraction unit calculating the muscle activity from the IMF and the subband with the maximum rate of change.

### Claim 3 (depends on 2)

The system of claim 2, wherein the muscle activity is calculated using muscular contraction tonus, muscle fatigue, and muscular contraction timing.

### Claim 4 (depends on 3)

The system of claim 3, wherein the muscular contraction tonus is calculated from RMS of the IMF and the subband with the maximum rate of change,
the muscle fatigue is calculated from a median frequency, and
the muscular contraction timing is calculated from a cross-correlation function between the multiple electromyography sensors.

### Claim 5

An exercise guidance method using an electromyography sensor, wherein exercise guidance is performed via the multiple electromyography sensors and an exercise guidance application of a monitoring module, the method comprising:
receiving exercise information from the monitoring module by working in conjunction therewith over a wired/wireless communication network, and receiving attachment position information of the electromyography sensors from the electromyography sensors;
receiving detection signals from the electromyography sensors when starting exercise;
calculating muscle activity by analyzing the detection signals, and providing a result of the calculation to the monitoring module; and
seeking an improvement plan by analyzing the exercise information and the muscle activity, and providing the improvement plan as feedback to the monitoring module.

### Claim 6 (depends on 5)

The method of claim 5, wherein the calculating of the muscle activity comprises:
analyzing the detection signals and selecting both an intrinsic mode function (IMF) equal to or larger than a threshold value and a subband with a maximum rate of change; and
calculating muscular contraction tonus from RMS of the IMF and the subband with the maximum rate of change, calculating muscle fatigue from a median frequency, and calculating muscular contraction timing from a cross-correlation function between channels so as to be provided as the muscle activity.