Medical Informatics Europe - MIE 2012, Pisa, 26-29.08.2012

1. 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

2. Overview
• EMG and prosthetics
• Motivations and goals
• Acquisition setup and sensors
• Hand movements
• Results
– Electrodes
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3. 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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4. 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! 4

5. 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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6. 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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7. 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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8. Sensor setup
• 8 equally spaced electrodes
• 2 electrodes on finger flexor and extensor muscles
• Two axes inclinometer
• Data glove
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9. Hand movements
Training
Hato, 2004
Exercise 1 Sebelius, 2005
12 movements
Farrel, 2008
Crawford, 2005
Exercise 2
17 movements
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10. More movements
Exercise 3
23 movements
Feix, 2008 DASH Score
Objects are simple tools to make
the protocol easy to reproduce
everywhere.
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11. Web-based database (http://ninapro.hevs.ch/)
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12. 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
Gender 21 males 7 females
Handedness 26 right handed 2 left handed
Age 28.1 ± 3.4 years 12

13. 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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14. Two types of electrodes tested
• Otto Bock 13E200
– Root mean square rectification
– High pass filtering
– Sampling frequency: 100 Hz
L. F. Law et al., 2010
• Delsys Trigno
– Raw signal
– Sampling frequency: 2KHz
– Wi-fi L. F. Law et al., 2010
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15. 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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16. 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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17. 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 17

18. 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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