WO2018020513A1

WO2018020513A1 - A system for recognizing muscle activities and method thereof.

Info

Publication number: WO2018020513A1
Application number: PCT/IN2017/050308
Authority: WO
Inventors: Diwakar VAISH
Original assignee: Vaish Diwakar
Priority date: 2016-07-29
Filing date: 2017-07-27
Publication date: 2018-02-01

Abstract

This invention relates to a system (200) for controlling muscle activities and method (300) thereof. The system includes a stretch sensor (205) which is adapted to detect and measure a plurality of muscle strains of a user on a stimulation of a plurality of muscle fibers by stretching or relaxing of an encircled loop of the stretch sensor on a body part, a wearable means (210), i.e. adapted to store the stretch sensor (205) and encircles on a plurality of tension-generating sites within the plurality of muscle fibers on the body part of the user and a processing circuitry (220) communicatively coupled to the stretch sensor (205) and configured to receive a signal corresponding to the detected tension-generating sites within the muscle fibers. The plurality of muscle strains generates an input data in the form of a plurality of mechanical strains for the processing circuitry (220). Further, the processing circuitry (220) is configured to process the input data from the stretch sensor (205) for converting the plurality of mechanical strains into a digital signal via a controller.

Description

TITLE

A System for Recognizing Muscle Activities and Method Thereof.

FIELD OF THE INVENTION

The present invention relates to the field of the wearable means for recognizing the muscle activities. The invention, particularly relates to a system and method for recognizing the muscle activity of a user using a wearable means and a processing circuitry.

BACKGROUND OF THE INVENTION

In recent years, the various kinds of sensor are being used for making an article or system easier and precise for a particular output, these outputs might be ascended from the different conversion with respect to one another. These sensors are further used with a complex circuitry and other assemblies such that it can be auxiliary produced a user desired output. The sensor for muscle controlling activities is obvious in the market that detects for a muscle stimulation in the numerous muscle fibers of related parts of a user. The general sensors in use, works on the principle of the bioelectrical change in the muscle fibers and with the monitoring of the physical action of the associated body part of the user. The sensor helps the user in a certain kind of operation that can be triggered after attainment of a specific set of values, for example, sensor can set for providing tension on a specific part for a particular value of the sensing element and then the part corresponding acts as an actuation of further subsequent module of a device or any other instrument. In conventional, the use of the sensor is very realistic that the simple recognition of a position of the muscle strain generating site for the related body part of the user using an electromyography technology, which is arranged in direct contact of the spatial region on the body part of the user. These kinds of arrangements are very expensive and provides the unsolicited output with the muddle effect while the user like to perform many tasks.

There have been a number of solutions provided to recognize the muscle activities of a user, i.e. equipped with the Bioelectronics sensor such as electromyography and few of them have been discussed below:

US 8170656 B2 discloses a Wearable Electromyography-Based Controller provides a physical device, worn by or otherwise attached to a user that directly senses and decodes electrical signals produced by human muscular activity using surface Electromyography (sEMG) sensors. The resulting electrical signals provides a muscle-computer interface for use in controlling or interacting with one or more computing devices or other devices coupled to a computing device.

WO 2015090810 A1 discloses an arm band sensor that includes a hand sensor and a transmitter unit. The hand sensor is further adapted to detect the orientation and/or position of the hand in relation to the arm in order to provide a hand signal, and the transmitter unit is adapted to emit the hand signal via a wireless communication.

WO 2015110063 A1 relates to a method, apparatus, and device for information processing. The method includes an activation mode for a user gesture information as an input provided by the user to the device and apparatus, and based on that input, recognition of the gesture information of the user is determined, and this recognition of user intent on the basis of correlations between preset gesture information and operating instructions. The input modes comprise a keyboard input mode and a mouse input mode, thus providing the user to implement convenient control of a terminal in a familiar input mode environment by means of customary input operations, such as a click operation and a touch-and-slide operation. The invention enables a user for not memorizing multiple sets of correlations between gesture movements and operations, but need only pre-establish in a systematic correlation between basic operations to which the user is accustomed and standard keyboard and/or mouse operation events, thereby allowing the user to achieve the goal of controlling a terminal by means of customs operations.

The aforesaid documents and other similar solutions may strive to provide a system method for recognizing the muscle activities and/or gesture of the user that can be used with various predefined user activities; however, they still have a number of limitations and shortcomings such as, but not limited to, the use of various expensive modules such as, sensors, digital equipment, and other peripheral devices and further connection between them, requires due diligence. These kinds of system, however, often cause inaccurate mapping of the attributes that leads to the non-spontaneous result of the system and cause the user to have to pronate much more and at a greater degree of discomfort than normal. The above mentioned prior arts can only perform certain aspects say for example, provides a system and method that detects the gesture and muscle activity of the user with a predetermined value, to associate these values for a predefined user activity.

Accordingly, there remains a need in the prior art to have a system for recognizing muscle activities and method thereof, that must be economical for the user to purchase and also enables the user, having a dynamic learning that can be adapted by a self-learning circuitry and interfaces, therefore overcome the aforesaid problem and shortcomings. SUMMARY OF THE INVENTION

In the view of the foregoing disadvantages inherent in the known types of wearable means having various sensors for recognizing the muscle activities now present in the prior art, the present invention provides an improved system for recognizing muscle activities and method thereof. As such, the general purpose of the present invention, which will be described subsequently in greater detail, is to provide a new and improved system and method to recognize muscle activities with a self-learning programmed circuitry accordingly to the muscle activity of the user, which has all the advantages of the prior art and none of the disadvantages.

An object of the invention is to provide a system for recognizing muscle activities, i.e. having a wearable means adapted to store a stretch sensor and encircles on a plurality of tension-generating sites within the plurality of muscle fibers on the body part of the user.

It is another object of the present invention to provide the wearable means which is, a wearing item and preferably selected from an armband and the like. The armband can be adjusted accordingly on the body part of the user using a material such as, but not limited to, fabric hook, loop fastener, Velcro and the like.

It is another object of the present invention to provide the stretch sensor in which a conductive resilient and flexible material is used for reading the muscle strains and muscle fibers for the related body part of the user. Further, the stretch sensor generates a plurality of mechanical strains for each of the muscle strain and provided it, in the form of a plurality of analog signals to a processing circuitry. It is another object of the present invention to provide the processing circuitry that can convert the analog signal which is produced by the mechanical strains from the stretch sensor, into a digital signal for processing the data information, attained by the plurality of muscle strains and associated with the predefined user activities.

It is another object of the present invention to provide the processing circuitry which is a self-learning programmable processing circuitry to trigger the user predefined activities by calculating a plurality of values dynamically for the plurality of muscle strains with the plurality of user predefined activities.

It is another object of the present invention to provide the method for recognizing muscle activities that comprises the steps of: providing, a wearable means having a stretch sensor which encircles on a plurality of tension-generating sites within a plurality of muscle fibers on a body part of a user; detecting, a plurality of muscle strains from each of the tension- generating sites within the plurality of muscle fibers for the related body part of the user, by the stretch sensor; computing, a plurality of values dynamically for the plurality of muscle strains with a plurality of user predefined activities, by a processing circuitry; defining, the plurality of user predefined activities, associated with a particularly computed value for the plurality of muscle strains.

In this respect, before explaining at least one embodiment of the invention in detail, it is to be understood that the invention is not limited in its application to the details of construction and to the arrangements of the components set forth in the following description or illustrated in the drawings. The invention is capable of other embodiments and of being practiced and carried out in various ways. Also, it is to be understood that the phraseology and terminology employed herein are for the purpose of description and should not be regarded as limiting.

These together with other objects of the invention, along with the various features of novelty which characterize the invention, are pointed out with particularity in the disclosure. For a better understanding of the invention, its operating advantages and the specific objects attained by its uses, reference should be had to the accompanying drawings and descriptive matter in which there are illustrated preferred embodiments of the invention.

BRIEF DESCRIPTION OF THE DRAWINGS

The invention will be better understood and objects other than those set forth above will become apparent when consideration is given to the following detailed description thereof. Such description makes reference to the annexed drawings wherein:

Figure 1 shows a perspective view of a wearable device to recognize the muscle activities in accordance with an embodiment of the present invention.

Figure 2 shows a block diagram of the system for recognizing muscle activities in accordance with an embodiment of the present invention.

Figure 3 is a process flow diagram presenting a method to recognize muscle activities in accordance with an embodiment of the present invention. DETAILED DESCRIPTION OF THE INVENTION

In the following detailed description, reference is made to the accompanying drawings which form a part hereof, and in which is shown by way of illustration specific embodiments in which the invention may be practiced. These embodiments are described in sufficient detail to enable those skilled in the art to practice the invention, and it is to be understood that the embodiments may be combined, or that other embodiments may be utilized and that structural and logical changes may be made without departing from the spirit and scope of the present invention. The following detailed description is, therefore, not to be taken in a limiting sense, and the scope of the present invention is defined by the appended claims and their equivalents.

The present invention generally provides a system (200) and method (300) for recognizing muscle activities. The system comprises a stretch sensor (205), a wearable means (210) and a processing circuitry (220). The stretch sensor (205) adapted to detect and measure a plurality of muscle strains of a user on a stimulation of a plurality of muscle fibers by stretching or relaxing of an encircled loop of the stretch sensor (205) on a body part. The wearable means (210) adapted to store the stretch sensor (205) and encircles on a plurality of tension-generating sites within the plurality of muscle fibers of the body part of the user. The communicatively coupled to the stretch sensor (205) and configured to receive a signal corresponding to the detected tension-generating sites within the muscle fibers.

Referring now to the drawings, there is illustrated, in FIG. 1 , a perspective view of the wearable means (210) to recognize the muscle activities utilized in this embodiment, a plurality of muscle strains from various muscle activities generates an input data in the form of a plurality of analog signals for the processing circuitry (220); and further, the processing circuitry (220) is configured to process the input data from the stretch sensor (205) for converting the plurality of analog signal into the digital signal via a controller. Preferably, but not limited to, a forearm band in accordance with one exemplary embodiment of the present invention, although any other suitable wearable means (210) can also be used by the producer.

In accordance with an embodiment of the present invention, the processing circuitry (220) comprises, but not limited to, at least one analog pin, a controller, and a memory module. The processing circuitry (220) is communicatively coupled to the stretch sensor (205) and configured to receive a signal corresponding to the detected tension-generating sites within the muscle fibers.

In accordance with an embodiment of the present invention, the processing circuitry (220) is a self-learning programmable processing circuitry (220) to trigger a user predefined activities. The self-learning program is adapted to learn and calculate a plurality of values dynamically for the plurality of muscle strains, i.e. associated with the plurality of user predefined activities by the processing circuitry (220) for each different user while wearable on the body part of that user for the first time.

In accordance with an embodiment of the present invention, the stretch sensor (205) is placed in the wearable means (210) such as an armband, and further the encircling loop of the armband can be adjusted, according to the body part of the user using a material such as fabric hook (215), loop fastener, Velcro and the like. The stretch sensor (205) is communicatively coupled to the processing circuitry (220) for actuating the user predefined activities for a certain set of value and each value is calculated dynamically by the self- learning program, which is installed in the memory of the processing circuitry (220).

Referring to FIG. 2, a block diagram of the system (200) for recognizing muscle activities, i.e. adapted to sense the muscle activities of a user by the stretch sensor (205). The stretch sensor (205) generates a plurality of analog signals and illustrates these signals with the variability in the resistance caused by stretching and relaxing of the stretch sensor (205).

In accordance with an embodiment of the present invention, the stretch sensor (205) is constructed from, but not limited to, a conductive resilient and flexible material such as carbon-black impregnated rubber.

In accordance with an embodiment of the present invention, the processing circuitry (220) comprises, but not limited to, a processor, at least one analog pin, a controller (235), an analog to digital converter (230) and a memory module (225), although the circuit (220) is provided with various other electronic components as per the need of the producer. The power supply is provided to the system by a power generating unit (250) which is resided in the processing circuitry (220) for producing the plurality of user predefined set of activities (240).

FIG. 3 is a process flow diagram (300) presenting a method to recognize muscle activities of a user in accordance with yet another preferred embodiment of the present invention.

At step 301 , a wearable means (210) is provided with a stretch sensor (205) that encircles on a plurality of tension-generating sites within a plurality of muscle fibers on a body part of the user. Preferably, the wearable means (210) can be an armband having an adjustable means such as fabric hook (215), loop fastener, Velcro and the like for adjusting the size of the wearable means according to the user.

At step 303, the muscle contraction of the human body is detected by the stretch sensor (205). The stretch sensor (205) is a carbon-black impregnated rubber which is made of resilient and flexible material and further, provides the variable resistance value while stretching and relaxing of the muscle fibers of the related body part of the user.

In accordance with an embodiment of the present invention, the stretch sensor (205) is responsible for converting muscle strains into a mechanical strain which further, converted into the analog signal and provides the set of values for every change in resistance value to the analog pins of the processing circuitry (220).

At step 305, the plurality of values of change in resistance of the stretch sensor (205) is dynamically computed for each muscle activity with a plurality of user defined activities (240), by a processing circuitry (220). The processing circuitry (220) is communicatively coupled to the stretch sensor (205) and further configured to receive a signal corresponding to the detected tension-generating sites within each of the muscle fibers.

In accordance with an embodiment of the present invention, the processing circuitry (220) is designed to convert the plurality of muscle strains into a digital signal from the plurality of analog signals for a particular mechanical strain using a self-learning module. The pattern of various outputs is generated by the digital signal, accordingly to the set of value provided by the stretch sensor (205). Each pattern is specifically related to a predefined user activity (240) that is recognized after a related muscular activity of the user. At step 307, the plurality of user defined activities is defined and associated with a particularly computed value for the plurality of muscle activities. The user can perform a predefined task on the receiving of a related input by the stretch sensor (205) to the processing circuitry (220). The processing circuitry (220) is having a self-learning program that actuates the wearable means (210) dynamically for the predetermined activities for associated value provided by the stretch sensor (205).

The above-mentioned system for recognizing muscle activities and method thereof, is compatible without any specialized training of the user, while the user wear the device for the first time, the muscle activities are recognized by the stretch sensor and provides the input to the processing circuitry. The processing circuitry further recognizes that what activities user like to perform by a related output, which is generated by a particularly identifying a pattern in the self-learning programmed circuit when it enters the real time classification mode. In addition the size and dimension of whole parts of the system can be manufactured as per the requirement of the user. The system can be easily adapted on the various muscle fibers for actuating the related function and very economical in use.

It is to be understood that the above description is intended to be illustrative, and not restrictive. For example, the above-discussed embodiments may be used in combination with each other. Many other embodiments will be apparent to those of skill in the art upon reviewing the above description.

The benefits and advantages which may be provided by the present invention have been described above with regard to specific embodiments. These benefits and advantages, and any elements or limitations that may cause them to occur or to become more pronounced are not to be construed as critical, required, or essential features of any or all of the embodiments.

While the present invention has been described with reference to particular embodiments, it should be understood that the embodiments are illustrative and that the scope of the invention is not limited to these embodiments. Many variations, modifications, additions and improvements to the embodiments described above are possible. It is contemplated that these variations, modifications, additions and improvements fall within the scope of the invention.

Claims

I claim:

1. A system (200) for recognizing muscle activities, comprising:

a stretch sensor (205) adapted to detect and measure a plurality of muscle strains of a user on a stimulation of a plurality of muscle fibers by stretching or relaxing of an encircled loop of the stretch sensor (205) on a body part;

a wearable means (210) adapted to store the stretch sensor (205) and encircles on a plurality of tension-generating sites within the plurality of muscle fibers on the body part of the user;

a processing circuitry (220) communicatively coupled to the stretch sensor (205) and configured to receive a signal corresponding to the detected tension- generating sites within the muscle fibers;

wherein the stretch sensor (205) generates an input data in the form of a plurality of analog signals for the processing circuitry (220);

wherein the processing circuitry (220) comprises at least one analog pin, a controller (235), an analog to digital converter (230), and a memory module (225); and

wherein the processing circuitry (205) is configured to process the input data from the stretch sensor (205) for converting the plurality of analog signals into a plurality of user predefined activities via a controller (235).

2. The system as claimed in claim 1 , wherein the processing circuitry (220) is a self- learning programmable processing circuitry to trigger the plurality of user predefined activities.

3. The system as claimed in claim 2, wherein the self-learning programmable processing circuitry calculates a plurality of values dynamically for the plurality of muscle strains with the plurality of user predefined activities.

4. The system as claimed in claim 1 , wherein the plurality of user predefined activities is associated with a particularly calculated value for each of the muscle strains.

5. The system as claimed in claim 1 , wherein each of the calculated value is stored in a memory (225) of the processing circuitry (220) for the associated muscle strains.

6. The system as claimed in claim 5, wherein the stretch sensor (205) is constructed from a conductive resilient and flexible material.

7. The system as claimed in claim 1 , wherein the wearable means (210) is adjusted according to the body part of the user using a material such as fabric hook, loop fastener, Velcro and the like.

8. The system as claimed in claim 1 , wherein the wearable means (210) is a wearing item such as an arm band and the like.

9. A method for recognizing muscle activities, comprising the steps of: providing, a wearable means (210) having a stretch sensor (205) that encircles on a plurality of tension-generating sites within a plurality of muscle fibers on a body part of a user;

detecting, a plurality of muscle strains from each of the tension-generating sites within the plurality of muscle fibers for the related body part of the user, by the stretch sensor (205);

computing, a plurality of values dynamically for the plurality of muscle strains with a plurality of user predefined activities, by a processing circuitry (220);

defining, the plurality of user predefined activities, associated with a particularly computed value for the plurality of muscle strains;

wherein the processing circuitry (220) is communicatively coupled with the stretch sensor (205) and further configured to receive a signal corresponding to the detected tension-generating sites within each of the muscle fibers;

wherein the processing circuitry (220) is adapted to a self-learning interface for computing the plurality of values.

10. The method as claimed in claim 9, wherein the plurality of muscle strains generates a plurality of mechanical strains in the form of analog signal for the stretch sensor (205).

11. The method as claimed in claim 9, wherein the plurality of muscle strains is converted into a digital signal from the plurality of mechanical strains via the processing circuitry (220).

12. The method as claimed in claim 9, wherein the wearable means (210) is selected from a wearing item such as an arm band and the like.