experiences in the creation of an electromyography database to help hand amputated persons

Experiences in the Creation of an

Electromyography Database

to Help Hand Amputated Persons

Manfredo Atzori, Arjan Gijsberts, Simone Heynen,

Anne-Gabrielle Mittaz Hager, Claudio Castellini,

Barbara Caputo, Henning Müller

Overview

• EMG and prosthetics

• Motivations and goals

• Acquisition setup and sensors

• Hand movements

• Results

– Electrodes

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Electromyography

• Electromyography (EMG) is the

measurement of electrical activity

that is created by muscle contractions

• The signal path

– Originates in a motor neuron

– Travels to the target muscle(s)

– Starts a series of electrochemical changes that lead

to an action potential

– Can be detected by one or more electrodes

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EMG controlled prosthetics

• 2-3 degrees of freedom

• Few programmed movements

• Very coarse force control

• No dexterous control

• No natural control

• Long training times

• This is in contrast to recent advances

in mechatronics!

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Motivation for the work

• NO large scale public sEMG databases, only

private ones

– (Fukuda, 2003; Tsuji 1993; Ferguson, 2002; Zecca,

2002; Chan, 2005; Sebelius, 2005; Castellini, 2008;

Jiang, 2009; Tenore, 2009; Castellini, 2009)

• NO common sEMG acquisition protocol

• NO common sEMG storage protocol

• NO Clinical Data Correlation Evaluation

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Goals

• Creation and refinement of an acquisition protocol

• Acquisition of a database

• Public release of the database

• Worldwide test of classification algorithms using the

same data and setup

– Improve quality of classification

– Transfer this knowledge to build better prostheses

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Acquisition setup

• Laptop: Dell Latitude E5520

• Digital Acquisition Card: National

Instruments 6023E

• sEMG Electrodes: 10 double-differential

Otto Bock 13E200

• Printed Circuit Board, Cables &

Connectors

• Data Glove 22 sensors Cyberglove II

(Cyberglove Systems)

• Inclinometer: Kübler 8.IS40.2341

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Sensor setup

• 8 equally spaced electrodes

• 2 electrodes on finger flexor and extensor muscles

• Two axes inclinometer

• Data glove

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Hand movements

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Hato, 2004

Sebelius, 2005

Farrel, 2008

Crawford, 2005

Exercise 1 12 movements

Exercise 2 17 movements

Training Training

More movements

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Feix, 2008 DASH Score

Exercise 3 23 movements

Objects are simple tools to make

the protocol easy to reproduce

everywhere.

Web-based database (http://ninapro.hevs.ch/)

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Data stored

• XML file with clinical and experimental information

• Unprocessed data (sEMG, Cyberglove,

Inclinometer, Movie)

• Preview picture for each exercise

• Picture of the arm without the acquisition setup

• Picture of the arm with the acquisition setup

• Currently stored: 27 intact subjects, 1 amputated

subject, several recordings for a few

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Gender 21 males 7 females

Handedness 26 right handed 2 left handed

Age 28.1 ± 3.4 years

Electrode experiences

• Double differential potential

– Good signal to noise ratio

• Excellent comfort (no cleaning/

shaving)

• Classification results in

accordance with the scientific

literature (~7-20%)

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Two types of electrodes tested

• Otto Bock 13E200

– Root mean square rectification

– High pass filtering

– Sampling frequency: 100 Hz

• Delsys Trigno

– Raw signal

– Sampling frequency: 2KHz

– Wi-fi

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L. F. Law et al., 2010

L. F. Law et al., 2010

Acquisition experiences (amputated)

• Dry the stump before the experiment

• Need of longer breaks between the exercises

• Modification of the instructions avoiding the concept

of an imaginary limb

• Elimination of a few movements from the protocol

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Acquisition experience (non amputated)

• Difficulty to place electrodes exactly in the same

position for subjects

– Need of spatial normalization as anatomy changes

and positions are not 100% stable

• Validation of the acquisition protocol with small

changes

– Function check of electrodes is required

– System needs to limit artifacts caused by users

• Removal of a few functional movements showing

high inter subject differences

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Conclusions

• Test and improvement of the acquisition setup

– Portable, based on research and industrial needs

• Test and improvement of the acquisition protocol

– Complete and easy to be reproduced

– Fixed several practical aspects

• Test and improvement of the hand movements

– 52, selected from robotics and medical literature

• Test of acquired sEMG signals (classification)

– Good SNR ratio

– Results in line with the scientific literature

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Questions, contacts?

• For more information:

• http://www.idiap.ch/project/ninapro/

• http://ninapro.hevs.ch

• Contacts:

• manfredo.atzori@gmail.com

• henning.mueller@hevs.ch

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