Hardware innovations are continuing to dissolve the boundaries between human and machine. Our bodies are being placed front and center as a new form of input within the Internet of Things. Emerging haptic technologies have applications that stretch across contextual wearable computer devices, human-computer interactions (HCI), entertainment, video games, virtual reality, industrial, military, and much more!

In todays post, learn how Appmethod gives your Connected Apps new reach with the Myo Gesture Control Armband. Find out how easy it is to get the C++ SDK provided by Thalmic Labs loaded into Appmethod and deployed as a Windows Connected App.

Gesture Control and the Internet of Things

What makes the Internet of Things such an anticipated frontier is not just the Gadgets and Devices or the applications they talk to, but rather the experiences created by the interplay between them. Things need to be categorized by their capability to create new forms of user experiences. Gesture, as a property of Things, enables a user to bridge the human computer interface with body in motion.

Designing Internet of Things driven experiences will become the next logical step following traditional multi-device based UX/UI design. What kind of new design restrictions need to be considered with dealing with gesture based input?  What does it mean when your users can suddenly control your connected app by waving their hands around in free space?  
 
The age of implemented Science Fiction is upon us and connected apps should transform users into superhero's.      

Meet the Myo Gesture Control Armband from Thalmic Labs

The Myo Gesture Control Armband from Thalmic Labs enables the wearer to use natural arm movements and hand gestures to control and interact with Devices, Gadgets, and Connected Apps. The Myo is a sort of bracelet, worn just below the elbow, that interprets electrical signals produced by muscle contractions in the forearm. Eight banded segments containing  electrical sensors measure the electrical signals traveling across the user's skin.  

Making different kinds of fists creates unique muscle contractions in the forearm. These muscle contraction patterns are read by the Myo and are translated into specific commands. For example a closed fist is one state while pressing the pinky to the thumb is another. The Myo is currently capable of detecting the following fist patterns: wave left, wave right, spread fingers, closed fist, and thumb-to-pinky.

The Myo also has built in motion detection that tracks yaw, pitch and roll.  
 
The Myo communicates over Bluetooth Smart 4.0 on Windows, Mac, Android and iOS. Thalmic Labs provides a USB dongle for platforms without built in Bluetooth Smart support.

Appmethod and the Myo SDK

Combining the Myo SDK with Appmethod makes it possible to extend connected apps to process gesture input.

Hello Myo! A Sample Demo App Built with Appmethod

#define _USE_MATH_DEFINES
#include <cmath>
#include <iostream>
#include <iomanip>
#include <stdexcept>
#include <string>
#include <algorithm>

void print()
{
    Form2->Memo1->Lines->Clear();
    if ( onArm ) {
        Form2->Memo1->Lines->Add( String().sprintf(L"[ Arm: %c ]", ( whichArm == myo::armLeft ? 'L' : 'R' )  ) );
        std::string poseString = currentPose.toString();
        Form2->Memo1->Lines->Add( poseString.c_str() );
        if ( poseString == "fist" ) {
            Form2->Rectangle1->Scale->X = 2;
            Form2->Rectangle1->Scale->Y = 2;
        }
        else {
            Form2->Rectangle1->Scale->X = 1;
            Form2->Rectangle1->Scale->Y = 1;
        }
    }
    Form2->Memo1->Lines->Add( String().sprintf( L"roll_w: %d",  roll_w ) );
    Form2->Memo1->Lines->Add( String().sprintf( L"pitch_w: %d", pitch_w ) );
    Form2->Memo1->Lines->Add( String().sprintf( L"yaw_w: %d", yaw_w ) );
    Form2->Rectangle1->RotationAngle  = ( roll_w )*36;
    Form2->Rectangle1->Position->X   -= ( yaw_w - 8 );
    Form2->Rectangle1->Position->Y   += ( pitch_w - 8 );
}

DataCollector collector; 
myo::Hub hub("com.example.hello-myo");

__fastcall TForm2::TForm2(TComponent* Owner)
    : TForm(Owner)
{
    try {
        Memo1->Lines->Add( "Trying to find the Myo" );
        hub.addListener( &collector );
        Timer1->Enabled = true;
    } catch (const std::exception& e) {
        Memo1->Lines->Add( String().sprintf( L"Error connecting to Myo:  %d", e.what() ) );
    }
}

void __fastcall TForm2::Timer1Timer(TObject *Sender)
{
    hub.run( 1000/20 );
    collector.print();
}