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.

1. 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 of
Mr. Bhangya.b
Assistant Professor
Dept of E&C
DEPARTMENT OF ELECTRONICS AND COMMUNICATION ENGINEERING
DON BOSCO INSTITUTE OF TECHNOLOGY
KUMBALAGODU, MYSORE ROAD, BENGALURU – 560 074
2014-2015

2. Details of the Project Plan :
TeamMate 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.
TeamMate 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.
TeamMate 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.
TeamMate 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.

3. 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.

4. 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 and
Robotic 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.

5. 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).

6. 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

7. 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

8. BLOCK DIAGRAM OF MYO ARMBAND
Hardwarerequirement:
 Microcontroller- AT89S52
 Flex sensor
 3D accelerometer
 Power supply
 Bluetooth
 RS232
 Motor
Software used:
 Embedded C
 Kiel IDE
 Proload or flash magic

9. 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.

11. diagram of a Wireless communication system having a
Wireless myoelectric apparatus and a portable
electronic device.

12. 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 survey
on 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
.

13. schematic block diagram of electronic circuitry
of the Wireless myoelectric apparatus

14. Flowchart describing a method of processing control
signals Which may be carried out by the portable
electronic device

15. Flowchart describing a method of learning gestures Which
may be carried out by the Wireless myoelectric apparatus

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