VISVESVARAYA TECHNOLOGICAL UNIVERSITY

“Jnana Sangama”, Belagavi – 590 018, Karnataka State, India

PROJECT SYNOPSIS ON:

“MYO ARM BAND”

Submitted by Mr. Praveen b walishetti (1DB12EC436) Mr. Yogesh d biradar (1DB11EC091) Mr. Prashanth patil (1DB12EC435) Mr. Ravichandra maski (1DB12EC440

Under the guidance ofMr. Bhangya.b

Assistant ProfessorDept of E&C

DEPARTMENT OF ELECTRONICS AND COMMUNICATION ENGINEERINGDON BOSCO INSTITUTE OF TECHNOLOGY

KUMBALAGODU, MYSORE ROAD, BENGALURU – 560 074

2014-2015

Details of the Project Plan :

Team Mate 1

i. Name of the Student: Praveen b walishetti

ii. USN: 1DB12EC436

iii. Mobile no. & Email id of Student: 8880887121;praveenwalishetti007@gmail.com

iv. Name of the College : Don Bosco Institute Of Technology.

Team Mate 2

i. Name of the Student: yogesh biradar

ii. USN: 1DB11EC

iii. Mobile no. & Email id of Student:

iv. Name of the College : Don Bosco Institute Of Technology.

Team Mate 3

i. Name of the Student:

ii. USN:

iii. Mobile no. & Email id of Student:

iv. Name of the College : Don Bosco Institute Of Technology.

Team Mate 4

i. Name of the Student:

ii. USN:

iii. Mobile no. & Email id of Student:

iv. Name of the College : Don Bosco Institute Of Technology.

ABSTRACT

Electromyography (EMG) is a technique for evaluating and recording the activation signal of muscles. EMG is performed using an instrument called an electromyography, to produce a record called an electromyogram. An electromyography detects the electrical potential generated by muscle cells when these cells contract, and also when the cells are at rest. Electrical characteristics. The electrical source is the muscle membrane potential of about -70mV. Measured EMG potentials range between less than 50 μV and up to 20 to 30 mV, depending on the muscle under observation. Typical repetition rate of muscle unit firing is about 7–20 Hz, depending on the size of the muscle (eye muscles versus seat (gluteal) muscles), previous axonal damage and other factors. Damage to motor units can be expected at ranges between 450 and 780 mV. In this study, we proposed a hierarchical gesture recognition framework based on the combined use of multivariate Gaussian distribution and a set of rules for model and feature set selection, deriving from a detailed analysis of misclassified gestures in the confusion matrix. To illustrate the practical use of the framework, a gesture recognition experiment has been conducted on Predefined Sign Language gestures with two additional gestures representing space and a full stop. This proposed project will be helpful for the speech and hearing impaired disability people. The sensors sensed values will be sent to microcontroller where in pre assigned values of the sensors will be set in the program which will be passed to the motor controlled unit and the motor controller unit performs the necessary action. Low power wireless communication and computing embedded systems, in the main form of wireless sensor networks (WSN), have become a robust solution. Through hardware and software architectures, along with appropriate mechanisms e.g. for data collection and aggregation, wireless communication protocols and standards, they represent a valid solution in assuring continuous and reliable operation.

INTRODUCTION

As people age, they must often deal with decreased mobility.Such reductions may ultimately impair one’s abilityto perform essential activities of daily living (ADLs). Forthose wishing to age in place, a diminished capacity to conductADLs is frequently an indicator for diminished quality of life,decreased independence, increased caregiver burden, or institutionalization. With this population in mind, the authorsenvision a comprehensive system of adaptive architectural andRobotic components to support independent living for individualswhose capabilities and needs are changing over potentiallylong periods of time.

Human gesture may occur in various forms including handand arm gesticulation, pantomime, sign language, static posesof the hand and body, or language-like gestures that may replacewords during speech. Of these, hand and arm gesticulation accountfor some 90% of gestured communication. Hence,the exploration of gesture at this scale as a means of commandinteraction with robotics and computing is warranted. Efforts atautomated gesture recognition generally involve a common setof considerations and problems to be addressed. These include Some combination of sensor platform, data representation, patternrecognition, and machine learning.Automatic gesture recognition is a key component for the development of a gesture-based communication device. In general, most sign language postures can be recognized based on four distinctive features, namely shape, position, orientation, and motion sequence. With modern sensor technology, these main features can be captured and interpreted.

Electromyography (EMG) is a technique for evaluating and recording the electrical activity produced by skeletal muscles. EMG is performed using an instrument called an electromyograph, to produce a record called an electromyogram. An electromyograph detects the electrical potential generated by muscle cells, when these cells are electrically or neurologically activated. The signals can be analyzed to detect medical abnormalities, activation level, or recruitment order or to analyze the biomechanics of human or animal movement.

Myo can tell the difference between different finger movements and sense hand rotations and movements by measuring the different electrical-impulse patterns that your movements generate and by using an inertial sensor to understand movements. With the band on your arm, you can do things like mimic shooting a gun to control a firearm in a video game, or swipe a hand to move through slides in a presentation. This information is sent to a processor in the armband, and an algorithm translates it into commands, which are sent via low-power Bluetooth to the gadget you’re trying to control, such as a smartphone.

LITARETURE SURVEY Gesture recognition and pen computing:This computing not only going to reduce the hardware impact of the system but also it increases the range of usage of physical world object instead of digital object like keyboards, mouses. Using this we can implement and can create a new thesis of creating of new hardware no requirement of monitors too. This idea may lead us to the creation of holographic display. The term gesture recognition has been used to refer more narrowly to non-text-input handwriting symbols, such as inking on a graphics tablet, multi-touch gestures, and mouse gesture recognition. As for robotics, the big advantage of systems like Myo (or JPL's BioSleeve) is that it doesn't require external infrastructure or a controller that you have to hold onto, keep track of, and otherwise be careful with. With a wearable control system, you can keep it on all the time, and instantly activate it with a gesture. It's simple and intuitive and can be operated with a minimal amount of training, but at the same time, is versatile enough to control a wide variety of robots. But there's a trade-off: Neither the Myo or the BioSleeve might offer the extra-fine level of control that you can get with something more traditional (like a PS3 controller). As robotic autonomy increases, though, reliance on high-level commands will become the norm, and that's what things like the Myo are likely best at.

MOTIVATION :

The present methods and devices relate generally to human-electronics interfaces, and more speci?cally to wearable electronic devices that combine muscle activity sensor signals and inertial sensor signals to provide gesture-based control of electronic devices. Gesture control has come a long way since Microsoft released the Kinect in 2010—the first truly mass-market gesture-control system. With Myo (pronounced “my-oh”), technicians hopes a slew of recently enlisted developers will take things even further by building apps enabling the device to do everything from controlling virtual-reality systems to musical instruments and gadgets(these ideas, plus the aforementioned hands-free window-blind control, were suggested by developers keen to get their hands on the device).

OBJECTIVES OF PROJECT

The Myo armband interprets the electrical impulses generated by muscle movements in your forearm. it needs neither light nor a camera to operate. This, coupled with its relatively small size, could make it easier to use in darkened rooms or bright sunlight. Yet the initial use cases being contemplated -- controlling slides during a presentation and controlling media on a television -- can be managed with current technologies. Presenters continue to make do with remote controls on stage. Dealing with media being sent from a laptop or tablet to a TV presents a more complicated scenario Myo's gesture tracking offers some advantages as a way to interact with a computing device that's across the room.armband work with as many gadgets as possible. So far,

Applications: They can be used in biological sciences.

They can be used extensively for speech and hearing impaired disability persons.

Myo has been set up with devices including an iPhone, iPad, Mac and Windows .

Myo can also controls the helicopter,vehicles and a Parrot AR.Drone etc

Myo can control features on gadgets like mobile, ipad, tablet,computer,TV, and many more electrical and electronic equipment etc

METHODOLOGY

It is an armband that monitors electrical signals in the wearer's arm muscles and converts them into roll, pitch, and yaw (movement along the x, y, and z axes) to track motion in three dimensions

The way the Myo works is quite ingenuous, there are receptors in the arm band that are able to detect the electrical impulses that pass through individual muscle groups in the lower arm. Through extensive study, the movements of the arm and hand have been mapped to an extent that when the user makes a designated hand or arm movement, the Myo is able to interpret it and translate it into a digital response. This unique product has the potential to revolutionise the overlap between the digital world and the real world.

PROBLEM FORMULATION Using this mayo armband You'll be able to map gestures to commands on your computer just like a keyboard: in a video game context, for example, instead of using your mouse button to fire a gun, you can use your trigger finger. Or instead of hitting "R" to reload, you can raise your arm and make a physical gun reloading motion. For extra degrees of freedom, wear a second Myo on your other arm.also u can control wireless helicopter,home equipment by just moving hand that assigned particular symbol for particular device controls

Overview of myo armband

BLOCK DIAGRAM OF MYO ARMBAND

Hardware requirement: Microcontroller- AT89S52 Flex sensor 3D accelerometer Power supply Bluetooth RS232 Motor

Software used: Embedded C Kiel IDE Proload or flash magic

Advantages:

Output sensitivity is stable.

It provides an alternate solution for dumb and deaf people to interact.

Excellent linearity over their dynamic range

Will provide scope to enhance the features of various devices.

Low power consumption

accurate detection and positioning

Myo can work with virtual-reality headset Oculus Rift and Google Glass

easier to use in darkened rooms or bright sunligh

Disadvantages: Complexity of the circuit increases as the number of sensors increase.

Initial cost is high.

diagram of a Wireless communication system having a Wireless myoelectric apparatus and a portableelectronic device.

REFERENCE

1.R. van Kranenburg, The Internet of Things: A Critique of Ambient Technology and the All-Seeing Network of RFID. Institute of Network Cultures, 2008.

2.R. van Kranenburg, E. Anzelmo, A. Bassi, D. Caprio, S. Dodson, and M. Ratto, “The Internet of things,” in Proceedings of 1st Berlin Symposium on Internet and Society, pp. 25-27, 2011.

3. Y. Li, M. Hou, H. Liu, Y. Liu,”Towards a theoretical framework of strategic decision, supporting capability and information sharing under the context of IoT,” Information Technology and Management,

4. L. Tan, and N. Wang, “Future internet: The Internet of Things,” in Proceedings of the 3rd International Conference on Advanced Computer Theory and Engineering (ICACTE),

5. I.F. Akyildiz, W. Su, Y. Sankarasubramaniam and E. Cayirci, “A surveyon sensor networks”, IEEE Commun

6. United States Patent Application Publication ; Pub. No.: US 2014/0240103 A1 Lake et al.; Pub. Date: Aug. 28, 2014

7. United States Patent Hill et al.; Patent N0.: US 6,244,873 B1 Date of Patent: Jun. 12, 2001

WEBSITES

1.WWW.THALMIC.COM

2.WWW.EXTREMETECH.COM

3.SUPPORT.GETMYO.COM

4.WWW.TECHNOLOGYREVIEW.COM

5.WWW.TECHCRUNCH.COM

6WWW.GOOGLE.COM

7.WWW.WIKIPEDIA.COM

8.WWW.DIGITALTREND.COM.

schematic block diagram of electronic circuitryof the Wireless myoelectric apparatus

Flow chart describing a method of processing control signals Which may be carried out by the portable electronic device

Flow chart describing a method of learning gestures Which

may be carried out by the Wireless myoelectric apparatus

Flowchart describing a method of processing myoelectric sensor signals Which may be carried out by the Wireless myoelectric apparatus