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Indian Institute of Information Technology - Allahabad - Disputationes

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2nd Disputations on<br />

Future Technologies for Health<br />

Care<br />

<strong>Allahabad</strong> (India), 18-20 September 2011<br />

Diagnosis<br />

Through<br />

Gait Oscillations<br />

Pavan Chakraborty, Soumik<br />

Mondal, Anup Nandy, Saman<br />

Shahid and G. C. Nandi.<br />

<strong>Indian</strong> <strong>Institute</strong> <strong>of</strong> <strong>Information</strong> <strong>Technology</strong>, <strong>Allahabad</strong>,<br />

Deoghat, Jhalwa, <strong>Allahabad</strong> – 211 012 India<br />

E-mail: pavan@iiita.ac.in<br />

<strong>Indian</strong> <strong>Institute</strong> <strong>of</strong> <strong>Information</strong> <strong>Technology</strong> - <strong>Allahabad</strong>


Diagnosis Through Gait Oscillations<br />

Learning to walk is a daunting<br />

task for a human baby.<br />

It takes close to a year for a<br />

human baby to stand on its two<br />

legs, balance and then learn to<br />

walk.<br />

<strong>Indian</strong> <strong>Institute</strong> <strong>of</strong> <strong>Information</strong> <strong>Technology</strong> - <strong>Allahabad</strong>


<strong>Indian</strong> <strong>Institute</strong> <strong>of</strong> <strong>Information</strong> <strong>Technology</strong> - <strong>Allahabad</strong>


Locomotive<br />

Balance<br />

Static balance slower<br />

locomotion.<br />

Dynamic balance Faster locomotion.<br />

<strong>Indian</strong> <strong>Institute</strong> <strong>of</strong> <strong>Information</strong> <strong>Technology</strong> - <strong>Allahabad</strong>


Our biped locomotion<br />

was learned on Trees<br />

Orang-utan study suggests that upright<br />

walking may have started in the trees.<br />

--- Branch walking easier on biped,<br />

holding the branch above with hands.<br />

<strong>Indian</strong> <strong>Institute</strong> <strong>of</strong> <strong>Information</strong> <strong>Technology</strong> - <strong>Allahabad</strong>


Walking: A common yet<br />

complex process<br />

•Human walking is<br />

accomplished with a strategy<br />

called the double pendulum<br />

•During forward motion, the leg<br />

that leaves the ground swings<br />

forward from the hip<br />

•Leg strikes the ground with<br />

the heel and rolls through to<br />

the toe in a motion<br />

•Motion <strong>of</strong> the two legs is<br />

coordinated so that one foot or<br />

the other is always in contact<br />

with the ground<br />

<strong>Indian</strong> <strong>Institute</strong> <strong>of</strong> <strong>Information</strong> <strong>Technology</strong> - <strong>Allahabad</strong>


<strong>Indian</strong> <strong>Institute</strong> <strong>of</strong> <strong>Information</strong> <strong>Technology</strong> - <strong>Allahabad</strong>


<strong>Indian</strong> <strong>Institute</strong> <strong>of</strong> <strong>Information</strong> <strong>Technology</strong> - <strong>Allahabad</strong>


Foot<br />

Pressure<br />

Platform<br />

Animations<br />

Contact points <strong>of</strong> the sole <strong>of</strong> the foot during<br />

normal weight bearing.<br />

<strong>Indian</strong> <strong>Institute</strong> <strong>of</strong> <strong>Information</strong> <strong>Technology</strong> - <strong>Allahabad</strong>


<strong>Indian</strong> <strong>Institute</strong> <strong>of</strong> <strong>Information</strong> <strong>Technology</strong> - <strong>Allahabad</strong>


<strong>Indian</strong> <strong>Institute</strong> <strong>of</strong> <strong>Information</strong> <strong>Technology</strong> - <strong>Allahabad</strong>


Subject with reflective markers for motion analysis. Also<br />

seen are the electrodes for the telemetry EMG unit<br />

<strong>Indian</strong> <strong>Institute</strong> <strong>of</strong> <strong>Information</strong> <strong>Technology</strong> - <strong>Allahabad</strong>


Use <strong>of</strong> Sensor Network<br />

To Understand<br />

The Human Gait<br />

<strong>Indian</strong> <strong>Institute</strong> <strong>of</strong> <strong>Information</strong> <strong>Technology</strong> - <strong>Allahabad</strong>


Objective<br />

“The main objective <strong>of</strong> this research tends to develop a low<br />

cost, portable, non-invasive wearable sensor based<br />

biometric suit which could be applied to numerous different<br />

applications.” Like,<br />

• Human Identification<br />

• Human Robot Interaction<br />

• Gesture Classification<br />

• Human Computer Interaction<br />

• Diagnostic Gait Signature Detection<br />

• Find the effect on gait with different age, body weight and<br />

different diseases.<br />

• Analysis <strong>of</strong> abnormal gait signature etc.<br />

<strong>Indian</strong> <strong>Institute</strong> <strong>of</strong> <strong>Information</strong> <strong>Technology</strong> - <strong>Allahabad</strong>


The Degrees <strong>of</strong> Freedom<br />

3<br />

3 3<br />

1 1<br />

1<br />

1 1<br />

3 3<br />

1<br />

1<br />

2<br />

2<br />

<strong>Indian</strong> <strong>Institute</strong> <strong>of</strong> <strong>Information</strong> <strong>Technology</strong> - <strong>Allahabad</strong>


θ<br />

Potentiometer<br />

Voltage Calibrated to Angle θ<br />

θ<br />

t<br />

<strong>Indian</strong> <strong>Institute</strong> <strong>of</strong> <strong>Information</strong> <strong>Technology</strong> - <strong>Allahabad</strong>


θ ( t)<br />

= −65.71<br />

V ( t)<br />

+ 122.9<br />

<strong>Indian</strong> <strong>Institute</strong> <strong>of</strong> <strong>Information</strong> <strong>Technology</strong> - <strong>Allahabad</strong>


The actual knee<br />

angle oscillation<br />

<strong>of</strong> a healthy<br />

human being<br />

measured using<br />

a potentiometer<br />

circuit. The top<br />

panel shows the<br />

noisy data over<br />

a multiple gait<br />

oscillations.<br />

Averaging multiple gaits and convolving it with a 3 value running<br />

average in 2 iterations removes the noise (shown in the lower<br />

panels).<br />

<strong>Indian</strong> <strong>Institute</strong> <strong>of</strong> <strong>Information</strong> <strong>Technology</strong> - <strong>Allahabad</strong>


8 Analog Inputs<br />

AVR Dev. Board<br />

ACD, Multiplexing &<br />

Parallel to Serial<br />

conversion.<br />

ATMEGA 32<br />

RF Module Tx<br />

RF Module Rx<br />

Max 232<br />

RS – 323 Port<br />

Serial Port<br />

S<strong>of</strong>tware<br />

<strong>Indian</strong> <strong>Institute</strong> <strong>of</strong> <strong>Information</strong> <strong>Technology</strong> - <strong>Allahabad</strong>


<strong>Indian</strong> <strong>Institute</strong> <strong>of</strong> <strong>Information</strong> <strong>Technology</strong> - <strong>Allahabad</strong>


The HGOD Suit consisting <strong>of</strong> 8 potentiometer sensors<br />

<strong>Indian</strong> <strong>Institute</strong> <strong>of</strong> <strong>Information</strong> <strong>Technology</strong> - <strong>Allahabad</strong>


<strong>Indian</strong> <strong>Institute</strong> <strong>of</strong> <strong>Information</strong> <strong>Technology</strong> - <strong>Allahabad</strong>


<strong>Indian</strong> <strong>Institute</strong> <strong>of</strong> <strong>Information</strong> <strong>Technology</strong> - <strong>Allahabad</strong>


Figure 6. Gait oscillations from 8 joints <strong>of</strong> the body. From the top (left and<br />

right): Left and right Shoulders, left and right elbows, left and right hips and<br />

left and write knees. The dotted line is a simple sine curve fit to the shoulder<br />

elbow and hip data. The knee oscillation is complex; therefore it has not been<br />

fitted.<br />

<strong>Indian</strong> <strong>Institute</strong> <strong>of</strong> <strong>Information</strong> <strong>Technology</strong> - <strong>Allahabad</strong>


Design…<br />

<strong>Indian</strong> <strong>Institute</strong> <strong>of</strong> <strong>Information</strong> <strong>Technology</strong> - <strong>Allahabad</strong>


Sensor and Interface<br />

Kit Specification<br />

• Phidget Rotation sensor (1109) which is being<br />

integrated with Phidget interface kit (1018).<br />

• Power supply voltage varies from 3.5VDC to 5 VDC with<br />

10kΏ output impedance<br />

• The rotation sensor has been opted for 0 to 300 degree<br />

resolution<br />

• Measurement <strong>of</strong> analog value from the rotation sensor<br />

and produces the digital counts as output between 0 to<br />

1000 ranges<br />

• Analog Input update rate is 65 samples/sec<br />

<strong>Indian</strong> <strong>Institute</strong> <strong>of</strong> <strong>Information</strong> <strong>Technology</strong> - <strong>Allahabad</strong>


Calibration Curve for Sensor<br />

• Phidget interface kit has<br />

Internal 10 bit ADC<br />

circuit<br />

• Equation depicting linear<br />

relationship between the<br />

observed data and<br />

calibrated data with least<br />

square fitting is : θ = 3.3335 x<br />

count (±0.020161)<br />

<strong>Indian</strong> <strong>Institute</strong> <strong>of</strong> <strong>Information</strong> <strong>Technology</strong> - <strong>Allahabad</strong>


Analysis <strong>of</strong> human gait<br />

oscillations<br />

• Initially, for each gait pattern <strong>of</strong> respective joint a<br />

zero correction has already been done by collecting<br />

α 0 represented in the form <strong>of</strong> digital counts.<br />

• The initial digital counts are subtracted from the<br />

current digital count which is being interpolated by<br />

joint angle values in degree for each oscillation.<br />

• The movement <strong>of</strong> each oscillation for a particular<br />

joint is manipulated in terms <strong>of</strong> degree which is<br />

being calculated by<br />

desired angle (degree)=(current digital count-initial<br />

count)x 300/1000.<br />

<strong>Indian</strong> <strong>Institute</strong> <strong>of</strong> <strong>Information</strong> <strong>Technology</strong> - <strong>Allahabad</strong>


Gait Patterns Obtained<br />

Gait pattern <strong>of</strong> both elbow joints<br />

Gait pattern <strong>of</strong> both knee joints<br />

<strong>Indian</strong> <strong>Institute</strong> <strong>of</strong> <strong>Information</strong> <strong>Technology</strong> - <strong>Allahabad</strong>


Gait Patterns Obtained…<br />

Gait pattern <strong>of</strong> both hip joints<br />

Gait pattern <strong>of</strong> both shoulder joints<br />

<strong>Indian</strong> <strong>Institute</strong> <strong>of</strong> <strong>Information</strong> <strong>Technology</strong> - <strong>Allahabad</strong>


Observations<br />

• Each gait oscillation consists <strong>of</strong> both swing and stance<br />

phase respectively.<br />

• The generated pattern for both left limb and right limb<br />

implies the variation <strong>of</strong> calibrated angle values over the<br />

period <strong>of</strong> oscillation<br />

• The period <strong>of</strong> each oscillation for a particular pattern can<br />

be calculated by<br />

Total no <strong>of</strong> samples in a particular oscillation 64(approx)<br />

T =<br />

=<br />

= 1sec(approx)<br />

sampling rate<br />

65<br />

<strong>Indian</strong> <strong>Institute</strong> <strong>of</strong> <strong>Information</strong> <strong>Technology</strong> - <strong>Allahabad</strong>


Correlation and coupling <strong>of</strong><br />

significant joints<br />

• Correlation and coupling <strong>of</strong> those joint<br />

oscillations, we have compared them with an<br />

oscillation equation <strong>of</strong> the form:<br />

X<br />

( t)<br />

= asin(<br />

ω 1t<br />

+ ϕ)<br />

Y<br />

( t)<br />

= bsin(<br />

ω 2t)<br />

<strong>Indian</strong> <strong>Institute</strong> <strong>of</strong> <strong>Information</strong> <strong>Technology</strong> - <strong>Allahabad</strong>


Coupling Observations<br />

It has been observe from the figures that phase difference φ from the fitting<br />

between two gait oscillation is |φ|=π and<br />

ω1 = ω 2 = ω = 2π<br />

/ T = 2π<br />

<strong>Indian</strong> <strong>Institute</strong> <strong>of</strong> <strong>Information</strong> <strong>Technology</strong> - <strong>Allahabad</strong>


Coupling Between Elbows<br />

The above figure shows an interesting oscillation <strong>of</strong> an envelope in the shape<br />

<strong>of</strong> an ‘L’. This indicates when one elbow oscillates the other is practically<br />

static. This happens because <strong>of</strong> the elbow locking in the reverse cycle.<br />

<strong>Indian</strong> <strong>Institute</strong> <strong>of</strong> <strong>Information</strong> <strong>Technology</strong> - <strong>Allahabad</strong>


Coupling Between Shoulder<br />

and Hips<br />

It is being noted from the above figures that the coupling between both<br />

shoulder and hip oscillations tends to an elliptical curve where phase<br />

difference |φ|= 5π/4 .<br />

<strong>Indian</strong> <strong>Institute</strong> <strong>of</strong> <strong>Information</strong> <strong>Technology</strong> - <strong>Allahabad</strong>


Coupling Between Shoulder<br />

and Elbows<br />

From the above figures it has been noticed that the movement <strong>of</strong><br />

shoulder oscillation arises in both directions where as the oscillation <strong>of</strong><br />

elbow joint belongs to in single direction<br />

<strong>Indian</strong> <strong>Institute</strong> <strong>of</strong> <strong>Information</strong> <strong>Technology</strong> - <strong>Allahabad</strong>


Creation <strong>of</strong> a Gait Data Base<br />

Gait Oscillations at Different Speed.<br />

With Different Carrying Weights.<br />

Other Biometric <strong>Information</strong> for Correlations:<br />

Male/Female,<br />

Weight<br />

Height<br />

Age<br />

Body Shape – Front and side view photo<br />

<strong>Indian</strong> <strong>Institute</strong> <strong>of</strong> <strong>Information</strong> <strong>Technology</strong> - <strong>Allahabad</strong>


<strong>Indian</strong> <strong>Institute</strong> <strong>of</strong> <strong>Information</strong> <strong>Technology</strong> - <strong>Allahabad</strong>


<strong>Indian</strong> <strong>Institute</strong> <strong>of</strong> <strong>Information</strong> <strong>Technology</strong> - <strong>Allahabad</strong>


List <strong>of</strong> Publications<br />

• Pavan Chakraborty, Anup Nandy and G. C. Nandi, 2007.<br />

• "Use <strong>of</strong> Sensor Network to Understand the Human Gait"<br />

• An Invited Oral Presentation WCSN-2007 International<br />

Conference held at IIIT-<strong>Allahabad</strong>.<br />

• Pavan Chakraborty, G. C. Nandi and Anup Nandy, 2008.<br />

• “Sensing the Human Locomotion”<br />

• An Invited Oral Presentation at the Multi Discipline Expert<br />

Panel Meeting held at ALIMCO Kanpur on January 30 and 31,<br />

2008.<br />

• Akshay K Singh, Ajit D Dhiwal, Pavan Chakraborty and G C<br />

Nandi. 2008. “Designing A Full Body Human Computer<br />

Interaction Device” Proceedings <strong>of</strong> the National Conference<br />

CSI-RDHS 2008 Research and Development in Hardware and<br />

Systems by Computer Society <strong>of</strong> India).<br />

<strong>Indian</strong> <strong>Institute</strong> <strong>of</strong> <strong>Information</strong> <strong>Technology</strong> - <strong>Allahabad</strong><br />

Continued………


List <strong>of</strong> Publications<br />

• “A framework for synthesis <strong>of</strong> human gait oscillation using intelligent gait<br />

oscillation detector (IGOD)” In: IC3 2010. CCIS, vol. 94, pp. 340–349.<br />

Springer, Heidelberg, 2010.<br />

• “Gait Based Personal Recognition System Using Rotation Sensor,”<br />

Submitted in IEEE Trans. On System, Man Cybernetics part: B (Under<br />

Review).<br />

• “Modeling a Central Pattern Generator to generate Biped Locomotion <strong>of</strong> a<br />

Bipedal Robot using Rayleigh Oscillators” – In the proceedings <strong>of</strong> S. Aluru<br />

et al. (Eds.): IC3 2011, CCIS 168, pp. 289–300, Springer-Verlag Berlin<br />

Heidelberg, 2011. (In press)<br />

• “A Central Pattern Generator based Nonlinear Controller to Simulate Biped<br />

Locomotion with a Stable Human Gait Oscillation” – In International Journal<br />

<strong>of</strong> Robotics and Automation (IJRA), vol. 2, issue 2, pp. 93-106, 2011.<br />

<strong>Indian</strong> <strong>Institute</strong> <strong>of</strong> <strong>Information</strong> <strong>Technology</strong> - <strong>Allahabad</strong>


<strong>Indian</strong> <strong>Institute</strong> <strong>of</strong> <strong>Information</strong> <strong>Technology</strong> - <strong>Allahabad</strong><br />

<strong>Indian</strong> <strong>Institute</strong> <strong>of</strong> <strong>Information</strong> <strong>Technology</strong> - <strong>Allahabad</strong>


<strong>Indian</strong> <strong>Institute</strong> <strong>of</strong> <strong>Information</strong> <strong>Technology</strong> - <strong>Allahabad</strong>


<strong>Indian</strong> <strong>Institute</strong> <strong>of</strong> <strong>Information</strong> <strong>Technology</strong> - <strong>Allahabad</strong>


<strong>Indian</strong> <strong>Institute</strong> <strong>of</strong> <strong>Information</strong> <strong>Technology</strong> - <strong>Allahabad</strong>


Conclusion<br />

• A biometric suit IGOD was build to make simultaneously measurement <strong>of</strong> the 8<br />

major joint oscillations that plays a crucial role during human biped locomotion.<br />

• The mechanical structure <strong>of</strong> IGOD was completed, fine-tuning and calibrations was<br />

done.<br />

• The concept <strong>of</strong> IGOD is extremely simple with significant biometric and robotics<br />

application.<br />

• Analysis <strong>of</strong> the data using correlation coupling between pair <strong>of</strong> left and right limbs<br />

will be an important diagnostics <strong>of</strong> the bio information.<br />

• The gait recognition study has been made using the IGOD data from various<br />

people.<br />

• The TS-LDA developed for the purpose provided promising results.<br />

<strong>Indian</strong> <strong>Institute</strong> <strong>of</strong> <strong>Information</strong> <strong>Technology</strong> - <strong>Allahabad</strong>


Conclusion…<br />

• The results were doubly checked with the well established ANN algorithm.<br />

• Interestingly in a different work on gesture based recognition TS-LDA did not<br />

work.<br />

• This made us analyze the capability <strong>of</strong> TS-LDA which is well tuned to detect small<br />

variations which is normally seen in gait recognition; it does not work well for large<br />

variation as seen in gesture recognition.<br />

<strong>Indian</strong> <strong>Institute</strong> <strong>of</strong> <strong>Information</strong> <strong>Technology</strong> - <strong>Allahabad</strong>


Pavan Chakraborty, Anup Nandy and G. C. Nandi, 2007.<br />

"Use <strong>of</strong> Sensor Network to Understand the Human Gait"<br />

An Invited Oral Presentation WCSN-2007 International Conference held<br />

at IIIT-<strong>Allahabad</strong>.<br />

Pavan Chakraborty, G. C. Nandi and Anup Nandy, 2008.<br />

“Sensing the Human Locomotion”<br />

An Invited Oral Presentation at the Multi Discipline Expert Panel Meeting<br />

held at ALIMCO Kanpur on January 30 and 31, 2008.<br />

Akshay K Singh, Ajit D Dhiwal, Pavan Chakraborty and G C Nandi.<br />

2008. “Designing A Full Body Human Computer Interaction Device”<br />

Proceedings <strong>of</strong> the National Conference CSI-RDHS 2008 Research and<br />

Development in Hardware and Systems by Computer Society <strong>of</strong> India).<br />

Pavan Chakraborty, Anup Nandy and G. C. Nandi,<br />

"HGOD A Multi Sensor Network to analyze Human Gait and its stability“<br />

Submitted to The Proceeding IEEE Conference.<br />

Raghvendra Jain, Pavan Chakraborty, and G. C. Nandi<br />

“Energy budgeting for a Humanoid Robot using physics properties”<br />

Raghvendra Jain, K.V.N. Pavan, Pavan Chakraborty, and G. C. Nandi,<br />

“Full body Human Robot real Time Gesture based interaction”<br />

<strong>Indian</strong> <strong>Institute</strong> <strong>of</strong> <strong>Information</strong> <strong>Technology</strong> - <strong>Allahabad</strong>


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The Degrees <strong>of</strong> Freedom<br />

3<br />

3 3<br />

1 1<br />

1<br />

1 1<br />

3 3<br />

1<br />

1<br />

2<br />

2<br />

<strong>Indian</strong> <strong>Institute</strong> <strong>of</strong> <strong>Information</strong> <strong>Technology</strong> - <strong>Allahabad</strong>


Statically stable walking: The projection <strong>of</strong> the robot’s<br />

center <strong>of</strong> gravity always lies within the footprint or the area<br />

between the two footprints <strong>of</strong> the robot.<br />

The locomotion is quite easier to perform but is very slow.<br />

Dynamic walking: The robot’s center <strong>of</strong> gravity outside the<br />

footprints. Corrections must be done at all times to maintain<br />

the robot on his feet.<br />

To achieve stability, it is mandatory to know about the robot’s<br />

dynamics (speed and inertia <strong>of</strong> each <strong>of</strong> its parts).<br />

This method is without a doubt the more efficient in<br />

terms <strong>of</strong> velocity but is very tricky to implement.<br />

<strong>Indian</strong> <strong>Institute</strong> <strong>of</strong> <strong>Information</strong> <strong>Technology</strong> - <strong>Allahabad</strong>


Passive walking: No actuators are used and the robot uses its<br />

own weight and dynamics to walk down a slope without external<br />

input or control.<br />

The system has a stable limit cycle and the robots are even<br />

able to deal with small perturbations. We can also mention the<br />

concept <strong>of</strong> passive dynamic walkers. In this case small<br />

power sources on their ankles and/or hips are included to<br />

simulate gravity,<br />

which allows the robots to walk on a level ground without<br />

control servos.<br />

This approach is very important since it allows to learn many<br />

features <strong>of</strong> robot’s dynamics that are also useful for other kind<br />

<strong>of</strong> locomotion [5, 4].<br />

<strong>Indian</strong> <strong>Institute</strong> <strong>of</strong> <strong>Information</strong> <strong>Technology</strong> - <strong>Allahabad</strong>


Discussion<br />

• According to our research works we can conclude that for distance based human<br />

identification using gait not only depends upon the leg feature. Here hand<br />

movement is also an important factor.<br />

• Both the methods gives us 100% accuracy.<br />

• This system can not be use for surveillance security purpose.<br />

• This can be used in personal identification purpose where walker full cooperation is<br />

needed.<br />

• In this system mainly we are trying to find out what are the basic features to<br />

recognize the different human walking for identification and research.<br />

<strong>Indian</strong> <strong>Institute</strong> <strong>of</strong> <strong>Information</strong> <strong>Technology</strong>, <strong>Allahabad</strong><br />

<strong>Indian</strong> <strong>Institute</strong> <strong>of</strong> <strong>Information</strong> <strong>Technology</strong> - <strong>Allahabad</strong><br />

5


Future Work<br />

• Interaction between humanoid robot and human being (Imitation<br />

Learning).<br />

• Classification <strong>of</strong> Gestures for Human Robot Interaction.<br />

• Tuning up the mechanical design and making IGOD wires free will<br />

improve the freedom, flexibility and movability <strong>of</strong> the subject wearing<br />

IGOD.<br />

• Use the suit for medical applications.<br />

• We are also trying to train our system by the suit data and test the<br />

system by image data for giving the freedom <strong>of</strong> walker and use this<br />

system as a gait based human identifier.<br />

<strong>Indian</strong> <strong>Institute</strong> <strong>of</strong> <strong>Information</strong> <strong>Technology</strong>, <strong>Allahabad</strong><br />

<strong>Indian</strong> <strong>Institute</strong> <strong>of</strong> <strong>Information</strong> <strong>Technology</strong> - <strong>Allahabad</strong><br />

5


List <strong>of</strong> My Publications…<br />

• “Classification <strong>of</strong> <strong>Indian</strong> Sign Language In Real Time” - In the proceedings <strong>of</strong> International Journal<br />

on Computer Engineering and <strong>Information</strong> <strong>Technology</strong> (IJCEIT), Vol. 10, No.15, pp. 52-57, January<br />

- February 2010.<br />

• “Recognition <strong>of</strong> Isolated <strong>Indian</strong> Sign Language gesture in Real Time” – In the proceeding <strong>of</strong><br />

Springer LNCS-CCIS 70, pp. 102-107, March 2010.<br />

• “Recognizing & Interpreting <strong>Indian</strong> Sign Language Gesture for Human Robot Interaction” - In the<br />

proceeding <strong>of</strong> ICCCT’10, IEEE Xplore Digital Library, pp. 712-717, September 2010.<br />

• “Gesture based imitation learning for Human Robot Interaction” – In the proceeding <strong>of</strong> ICACCN’11,<br />

pp. 287-292, 2011.<br />

<strong>Indian</strong> <strong>Institute</strong> <strong>of</strong> <strong>Information</strong> <strong>Technology</strong>, <strong>Allahabad</strong><br />

<strong>Indian</strong> <strong>Institute</strong> <strong>of</strong> <strong>Information</strong> <strong>Technology</strong> - <strong>Allahabad</strong><br />

5


Pavan Chakraborty<br />

<strong>Indian</strong> <strong>Institute</strong> <strong>of</strong> <strong>Information</strong> <strong>Technology</strong>, <strong>Allahabad</strong>.<br />

A Project funded by DST,<br />

P.I. : Pr<strong>of</strong>. M.D. Tiwari, Director, IIIT-<strong>Allahabad</strong><br />

The Working Team: Pr<strong>of</strong> G. C. Nandi (Head Robotics and AI Lab),<br />

Mr. Anup Nandi and Advitiya Saxena (Research Scholars) & Myself.<br />

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S5<br />

S6<br />

S7<br />

S8<br />

S3<br />

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Classification <strong>of</strong> eight regions over<br />

a gait cycle<br />

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Gait oscillation with noise Vs gait<br />

oscillation with filtering noise<br />

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AVR 40 Pin Development board<br />

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RF Module<br />

• An RF modulator<br />

(for radio<br />

frequency<br />

modulator) is a<br />

device that takes a<br />

baseband input<br />

• signal and outputs<br />

a radio frequencymodulated<br />

signal.<br />

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Hierarchical<br />

SENSE PLAN ACT<br />

Reactive<br />

Hybrid deliberative / reactive<br />

PLAN<br />

PLAN<br />

SENSE<br />

ACT<br />

SENSE<br />

ACT<br />

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2nd Disputations on<br />

Future Technologies for Health Care<br />

<strong>Allahabad</strong> (India), 18-20 September 2011<br />

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· Frames 1 - 3: The robot's momentum causes the robot to rise on its standing leg and<br />

a motor moves the swinging leg into position<br />

· Frame 3: The stretch sensor <strong>of</strong> the swinging leg is activated, which triggers the knee<br />

joint to straighten<br />

· Frames 3 - 6: The robot falls forward naturally, with no motor functions being used,<br />

and catches itself on the next standing leg<br />

· Frame 6: As the swinging leg touches the ground, the ground contact sensor in the<br />

foot triggers the hip extensor and the knee joint <strong>of</strong> the standing leg and the hip and knee<br />

joints <strong>of</strong> the swinging leg to swap roles<br />

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Activation<br />

<strong>of</strong> the calf<br />

muscle<br />

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M.R. Damper<br />

A typical Magneto-Rheological<br />

(MR) fluid consists <strong>of</strong> 20-40% by<br />

volume <strong>of</strong> relatively pure, 3-10<br />

micron diameter iron particles,<br />

suspended in a carrier liquid such<br />

as mineral oil, synthetic oil, water<br />

or glycol.<br />

Iron particles in suspension align and develop a yield strength<br />

in the presence <strong>of</strong> a magnetic field. The change from a freeflowing<br />

liquid to a semi-solid when a magnetic field is applied is<br />

rapid and reversible.<br />

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11.5mm<br />

35mm<br />

Bearings<br />

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11.5mm<br />

35mm<br />

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Bearings


Joint surfaces move with respect to one another by<br />

simultaneously (1) rolling, (2) gliding, and (3) spinning.<br />

When the concave surface is<br />

fixed and the convex surface<br />

moves on it, the convex surface<br />

rolls and glides in opposite<br />

directions.<br />

When the convex surface is fixed<br />

and the concave surface moves<br />

on it, the concave surface rolls<br />

and glides in the same direction.<br />

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Hardware Circuit<br />

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T<br />

ϕ<br />

Assumptions:<br />

•The period <strong>of</strong> the hip cycle is the same as that <strong>of</strong> the knee.<br />

•The phase difference between the hip and knee oscillation<br />

is constant.<br />

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Measurement <strong>of</strong> Period T <strong>of</strong><br />

the Hip Oscillation<br />

• The period <strong>of</strong> oscillation could be determined from the<br />

gap between 2 maxima <strong>of</strong> consecutive oscillations<br />

θi<br />

V i<br />

by the POT<br />

V i<br />

V 0<br />

t<br />

pj−1<br />

t<br />

pj<br />

T<br />

j<br />

= t − t<br />

pj pj<br />

−1<br />

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Measurement <strong>of</strong> Period T <strong>of</strong><br />

the Hip Oscillation<br />

V = ∑ j<br />

V i<br />

, VT = ∑ j<br />

Vi<br />

⋅ti,<br />

i<br />

i<br />

for<br />

V i<br />

> V 0<br />

t<br />

pj<br />

=<br />

VT<br />

V<br />

= ∑V<br />

⋅t<br />

i<br />

i<br />

i<br />

∑<br />

i<br />

V<br />

i<br />

T j<br />

T<br />

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j<br />

= t − t<br />

pj pj<br />

The period , is the time gap between consecutive<br />

peaks j and j-1.<br />

T j<br />

⇒ T 0<br />

−1


Check for Threshold<br />

T −<br />

j<br />

≥ ∂<br />

0<br />

T t<br />

2<br />

Check if<br />

threshold is crossed, then<br />

provide new period for damping pr<strong>of</strong>ile ( T = T j<br />

).<br />

0<br />

We take<br />

8 sections.<br />

∂t = T 0<br />

8<br />

since we divide the gait cycle into<br />

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Classification <strong>of</strong> eight<br />

regions over a gait cycle,<br />

superposed over the actual<br />

data <strong>of</strong> the knee angle.


RF Module<br />

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RF Module<br />

• An RF modulator<br />

(for radio<br />

frequency<br />

modulator) is a<br />

device that takes a<br />

baseband input<br />

• signal and outputs<br />

a radio frequencymodulated<br />

signal.<br />

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Why did nature never invent<br />

the wheel<br />

• Well, Nature has exploited circular objects and<br />

surfaces in many <strong>of</strong> its designs. Many<br />

mammalian joints follow the classic ball-andsocket<br />

design that allows circumduction (full 360<br />

degree range <strong>of</strong> movement).<br />

• When we try to mimic nature<br />

(Legged motion) we get in to a lot<br />

<strong>of</strong> problems related to stability and<br />

energy efficiency.<br />

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Legged locomotion<br />

• Adaptability and maneuvrability in rough<br />

terrain.<br />

• Mechanical complexity.<br />

• Less efficient in energy.<br />

• Complexity in control.<br />

• Nature has usually preferred legs.<br />

• Stability is a problem.<br />

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Monoped locomotion<br />

• Makes continuous<br />

adjustments to leg<br />

angle to control<br />

the body attitude<br />

and velocity.<br />

• Dynamic balance<br />

only.<br />

(Stability)<br />

http://www.ai.mit.edu/projects/leglab/<br />

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Biped locomotion<br />

• Static balance is available in a small range.<br />

Dynamic stability required for movement.<br />

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Outline<br />

Objective<br />

Contribution up to now<br />

Design <strong>of</strong> IGOD<br />

Analysis <strong>of</strong> human gait oscillations<br />

Application<br />

Conclusion and Future Work<br />

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9


The dotted line is a simple sine curve fit to the shoulder elbow<br />

and hip oscillations.<br />

θ<br />

L<br />

= θ<br />

L<br />

sin( ωt + δ<br />

L<br />

)<br />

i 0i<br />

i<br />

R<br />

R<br />

0i<br />

θ = sin( +<br />

θ ωt δ<br />

i<br />

As expected, we notice that the periods <strong>of</strong> oscillation for the fitted joints are<br />

the same ( T = 2 π ω =1. 57 sec). It is essential for the stability that all limbs<br />

should oscillate at the same frequency. We also notice as expected that the<br />

phase difference between the corresponding left and right limb is<br />

∆δ = δ −δ<br />

=<br />

i<br />

L<br />

i<br />

for the shoulder and hip joints. To check the correlation and coupling<br />

between the left and right <strong>of</strong> the body during a stable gait, and the<br />

consistency <strong>of</strong> the data, we plot the left with the right limb oscillations<br />

L<br />

i<br />

π<br />

R<br />

i<br />

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)


Degrees <strong>of</strong> Freedom (DOF)<br />

The arrows represent<br />

the unidirectional<br />

coupling <strong>of</strong> this first<br />

model. The values on<br />

the arrows correspond<br />

to the phase<br />

differences we<br />

imposed between the<br />

different oscillators.<br />

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Figure 7. Correlations and coupling between the left and right<br />

limbs. In this figure, the fitted sine functions (in Fig. 6),<br />

describe a Lissajous curve, shown in thick lines.<br />

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Contribution up to now<br />

• Rotation sensor based biometric wearable suit has been made<br />

for capturing different human gait oscillations for analysis<br />

and different applications.<br />

• Introduce rotation sensor base biometric wearable suit for<br />

human identification.<br />

• Personal recognition system which can applicable to real<br />

world situation.<br />

• Better feature selection procedure which can help us to<br />

recognize the person with giving 100% accuracy.<br />

• Choose the real time pattern<br />

compatible with our feature.<br />

recognition algorithm<br />

• Better accuracy<br />

approaches.<br />

has been achieved rather existing<br />

• Introduce Tree Structured LDA (TS-LDA) classification<br />

algorithm.<br />

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Application<br />

1. Gait Based Personal Recognition<br />

System<br />

2. Biological controller<br />

development for biped robot to<br />

generate biped locomotion<br />

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1


Gait Based Personal Recognition<br />

System<br />

To recognize different human walking in real time<br />

for Identification and research.<br />

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1


Recognition Procedure<br />

Person<br />

Movement<br />

Rotation sensors<br />

based suit<br />

( IGOD)<br />

Capture Joint<br />

Angle values<br />

Create Feature<br />

Matrix<br />

Choose 60%<br />

sample for<br />

training<br />

Recognition<br />

using ANN/TS-<br />

LDA<br />

After training rest<br />

<strong>of</strong> data taken for<br />

testing<br />

Result<br />

106<br />

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Data collection and<br />

Feature Extraction<br />

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Data collection<br />

1. We have taken 30 (25 male and 5 female) different humans 30sec<br />

normal walking data and the data was taken in 10 different sessions.<br />

2. The age <strong>of</strong> our volunteers is 20-30 years.<br />

3. According to our different volunteers point <strong>of</strong> view the suit does not<br />

affect their natural walking.<br />

4. In each session we have taken just 30 sec <strong>of</strong> walking step in order to<br />

<strong>of</strong>fer some amount <strong>of</strong> freedom to their normal walking. It leads to an<br />

assumption that if we put any constraint such as only 4 gait cycle<br />

needs to be accounted while capturing walking pattern, it will affect<br />

tremendously from his/her natural gait pattern.<br />

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1


Phases <strong>of</strong> the gait cycle<br />

Stance Phase<br />

• Initial Double Support<br />

• Single Support<br />

• Terminal Double Support<br />

Swing Phase<br />

• Initial Swing<br />

• Terminal Swing<br />

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Feature vector<br />

• Data Folding is used for creating feature<br />

vector.<br />

• Minimum and Maximum angle value <strong>of</strong><br />

each joints within a particular Gait Cycle.<br />

• Time taken by the Gait Cycle.<br />

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Feature vector…<br />

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Feature vector…<br />

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Gait Recognition<br />

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Method Used<br />

• Artificial Neural Network (ANN)<br />

• Tree Structured Linear Discriminant<br />

Analysis (TS-LDA)<br />

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LDA<br />

• For detecting the variables that allow the<br />

researcher to discriminate between different<br />

(naturally occurring) groups.<br />

• For classifying cases into different groups with a<br />

better accuracy.<br />

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1


LDA Numerical Example<br />

Factory “ABC” produces very expensive and high quality chip rings that heir qualities are<br />

measured in term <strong>of</strong> curvature and diameter. Result <strong>of</strong> quality control by experts is given in<br />

the table below.<br />

Curvature Diameter Quality Control Result<br />

2.95 6.63 Passed<br />

2.53 7.79 Passed<br />

3.57 5.65 Passed<br />

3.16 5.47 Passed<br />

2.58 4.46 Not Passed<br />

2.16 6.22 Not Passed<br />

3.27 3.52 Not Passed<br />

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1


Solution<br />

X= features (or independent variables) <strong>of</strong> all data. Each row (denoted by) represents<br />

one object; each column stands for one feature.<br />

Y= group <strong>of</strong> the object (or dependent variable) <strong>of</strong> all data. Each row represents one<br />

object and it has only one column.<br />

In our example, and<br />

2.95 6.63<br />

2.53 7.79<br />

X= 3.57 5.65 Y=<br />

3.16 5.47<br />

2.58 4.46<br />

2.16 6.22<br />

3.27 3.52<br />

1<br />

1<br />

1<br />

1<br />

2<br />

2<br />

2<br />

1<br />

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Solution…<br />

X i = features data for group i. Each row represents one object; each<br />

column stands for one feature. We separate X into several groups<br />

based on the number <strong>of</strong> category in Y.<br />

2.95 6.63<br />

2.53 7.79<br />

X 1 = X 2 =<br />

3.57 5.65<br />

3.16 5.47<br />

2.58 4.46<br />

2.16 6.22<br />

3.27 3.52<br />

μ i = mean <strong>of</strong> features in group i, which is average <strong>of</strong> X i<br />

μ 1 = μ 2 =<br />

3.05 6.38 2.67 4.73<br />

μ = global mean vector, that is mean <strong>of</strong> the whole data set.<br />

μ =<br />

2.88 5.676<br />

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Solution…<br />

X’ i = mean corrected data, that is the features data for group<br />

i => X i , minus the global mean vector μ .<br />

0.06 0.951<br />

- 0.357 2.109<br />

X’ 1 = X’ 2 =<br />

0.679 - 0.025<br />

0.269 - 0.209<br />

- 0.305 - 1.218<br />

- 0.732 0.547<br />

0.386 - 2.155<br />

C i = [(X’ i ) T * X’ i ] / n i = covariance matrix <strong>of</strong> group i.<br />

C 1 = C 2 =<br />

0.166 - 0.192<br />

- 0.192 1.349<br />

0.259 - 0.286<br />

-0.286 2.142<br />

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Solution…<br />

= pooled within group<br />

covariance matrix. It is calculated for each entry (r, s) in the matrix. In<br />

our example,<br />

C =<br />

0.206 - 0.233<br />

- 0.233 1.689<br />

The inverse <strong>of</strong> the pooled covariance matrix is<br />

C -1 =<br />

5.745 0.791<br />

0.791 0.701<br />

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Solution…<br />

P i = prior probability vector (each row represent prior probability <strong>of</strong><br />

group i ). If we do not know the prior probability, we just assume it<br />

is equal to total sample <strong>of</strong> each group divided by the total samples,<br />

that is P i = n i / N<br />

P =<br />

4 / 7<br />

3 / 7<br />

Discriminant function<br />

f i = μ i C -1 X k<br />

T<br />

– (μ i C -1 μ i<br />

T<br />

) / 2 +ln ( P i )<br />

We should assign object k to group i that has maximum f i<br />

<strong>Indian</strong> <strong>Institute</strong> <strong>of</strong> <strong>Information</strong> <strong>Technology</strong>, <strong>Allahabad</strong><br />

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Solution…<br />

The discriminant function is our classification rules to assign the object into<br />

separate group. If we input the new chip rings that have curvature 2.81 and<br />

diameter 5.46, reveal that it does not pass the quality control.<br />

Transforming all data into discriminant function (f 1 , f 2 ) we can draw<br />

the training data and the prediction data into new coordinate.<br />

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Recognition Procedure with TS-<br />

LDA<br />

X<br />

R 1 R 2<br />

Max (f 1 , f 2 ) = f 1<br />

R 3 R 4<br />

Max (f 3 , f 4 ) = f 4<br />

X<br />

R 1 R 4<br />

X<br />

Max (f 1 , f 4 ) = f 4<br />

X is recognized<br />

as class 4<br />

123<br />

<strong>Indian</strong> <strong>Institute</strong> <strong>of</strong> <strong>Information</strong> <strong>Technology</strong>, <strong>Allahabad</strong><br />

<strong>Indian</strong> <strong>Institute</strong> <strong>of</strong> <strong>Information</strong> <strong>Technology</strong> - <strong>Allahabad</strong>


Result analysis<br />

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<strong>Indian</strong> <strong>Institute</strong> <strong>of</strong> <strong>Information</strong> <strong>Technology</strong>, <strong>Allahabad</strong><br />

<strong>Indian</strong> <strong>Institute</strong> <strong>of</strong> <strong>Information</strong> <strong>Technology</strong> - <strong>Allahabad</strong><br />

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Performance Evaluation<br />

No. <strong>of</strong> Subjects<br />

Performance<br />

Gafurov et al. [3][10] 21 5%-13% EER<br />

Nakajima et al. [4] 10 85% RR<br />

Middleton et al. [5] 15 80% RR<br />

Derawi et al. [7], [8] 60 5.7%-20% EER<br />

Rong et al. [9] 35 6.7% EER<br />

Pan et al. [18] 30 96.7% RR<br />

Moustakidis et al. [19] 40 72.89% - 98.21% RR<br />

Our approach 30 100% RR<br />

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