Monica Reggiani : Locomotion Modes Classification

Revision [273]

Last edited on 2011-11-01 16:24:15 by MonicaReggiani

Additions:

~- [[http://www.massimosartori.net Massimo Sartori]], //, Department of Neurorehabilitaion Engineering, Georg-August University, Göttingen, Germany//

Deletions:

~~~- [[http://www.massimosartori.net Massimo Sartori]], //Department of Information Engineering, Univ. of Padua, Italy//~~

Revision [225]

Edited on 2011-03-09 15:37:18 by MonicaReggiani

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~-[[http://www.dei.unipd.it/wdyn/index.php?IDsezione=81&IDutente=256&IDinsegnamento=&IDgruppo_pass=&preview= Zimi Sawacha]], //Department of Information Engineering, Univ. of Padua, Italy//

Deletions:

~~~-[[http://www.dei.unipd.it/wdyn/index.php?IDsezione=81&IDutente=256&IDinsegnamento=&IDgruppo_pass=&preview= Zimi Sawatcha]], //Department of Information Engineering, Univ. of Padua, Italy//~~

Revision [175]

Edited on 2011-03-08 16:24:04 by MonicaReggiani

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~-[[http://www.gest.unipd.it/it/personale/altro-personale-di-ricerca/ceseracciu-elena Elena Ceseracciu]], //Department of Management and Engineering, Univ. of Padua, Italy//
~- [[http://www.massimosartori.net Massimo Sartori]], //Department of Information Engineering, Univ. of Padua, Italy//
~-[[http://www.dei.unipd.it/wdyn/index.php?IDsezione=81&IDutente=256&IDinsegnamento=&IDgruppo_pass=&preview= Zimi Sawatcha]], //Department of Information Engineering, Univ. of Padua, Italy//

Deletions:

~-Elena Ceseracciu, University of Padua, Italy
~- [[http://www.massimosartori.net Massimo Sartori]], University of Padua, Italy
~-[[http://www.dei.unipd.it/wdyn/index.php?IDsezione=81&IDutente=256&IDinsegnamento=&IDgruppo_pass=&preview= Zimi Sawatcha]], University of Padua,Italy

Revision [174]

Edited on 2011-03-08 16:16:37 by MonicaReggiani

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~- E. Ceseracciu, M. Reggiani, Z. Sawacha, F. Spolaor, M. Sartori, E. Pagello, C. Cobelli. SVM-based classification of EMG signals for enhanced interfaces in lower extremities exoskeletons. In //Siamoc Conference 2010//, October 2010.

Deletions:

~- SVM-based classification of EMG signals for enhanced interfaces in lower extremities exoskeletons E. Ceseracciu, M. Reggiani, Z. Sawacha, F. Spolaor, M. Sartori, E. Pagello, C. Cobelli.Siamoc Conference 2010. Ferrara, October 4-7th 2010

Revision [173]

Edited on 2011-03-08 16:15:39 by MonicaReggiani

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Revision [172]

Edited on 2011-03-08 16:11:07 by MonicaReggiani

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{{image class="left" url="images/people/silviaSpolaore.png" width="90" alt="Silvia Spolaore" title="Silvia Spolaore"}}Silvia Spolaore
March 2011-
{{image class="left" url="images/people/fabioMolon.png" width="90" alt="Fabio Molon" title="Fabio Molon"}}Fabio Molon
June 2010-

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{{image class="left" url="images/people/silviaSpolare.jpg" width="50" alt="Silvia Spolaore" title="Silvia Spolaore"}}Silvia Spolaore
{{image class="left" url="images/people/fabioMolon.jpg" width="50" alt="Fabio Molon" title="Fabio Molon"}}Fabio Molon

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Edited on 2011-03-08 16:05:18 by MonicaReggiani

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===Current Students ===

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~~=== Students ===~~

Revision [170]

Edited on 2011-03-08 16:03:39 by MonicaReggiani

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Deletions:

{{image class="left" url="images/people/silviaSpolare.jpg" width="50" alt="unipd" title="unipd"}}Silvia Spolaore
{{image class="left" url="images/people/fabioMolon.jpg" width="50" alt="unipd" title="unipd"}}Fabio Molon

Revision [169]

Edited on 2011-03-08 16:02:57 by MonicaReggiani

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Deletions:

Silvia Spolaore
Fabio Molon
[[ClassificationSoftware Install the classification software]]

Revision [168]

Edited on 2011-03-08 16:01:29 by MonicaReggiani

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{{image class="left" url="images/research/logo_unipd_small.gif" width="50" alt="unipd" title="unipd"}}
University of Padua, [[http://www.gest.unipd.it DTG]] and BEM Laboratory@[[http://www.dei.unipd.it DEI]]

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{{image class="left" url="images/research/logo_unipd_small.gif" width="50" alt="unipd" title="unipd"}}University of Padua, [[http://www.gest.unipd.it DTG]] and BEM Laboratory@[[http://www.dei.unipd.it DEI]]

Revision [167]

Edited on 2011-03-08 16:00:55 by MonicaReggiani

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{{image class="left" url="images/research/logo_unipd_small.gif" width="50" alt="unipd" title="unipd"}}University of Padua, [[http://www.gest.unipd.it DTG]] and BEM Laboratory@[[http://www.dei.unipd.it DEI]]

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{{image class="left" url="images/research/unipd-logo-small.png" width="50" alt="unipd" title="unipd"}}University of Padua, [[http://www.gest.unipd.it DTG]] and BEM Laboratory@[[http://www.dei.unipd.it DEI]]

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Edited on 2011-03-08 15:55:56 by MonicaReggiani

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Revision [165]

Edited on 2011-03-08 15:53:32 by MonicaReggiani

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With respect to previous researches, we plan to develop more sophisticated sensor systems to capture a broader set of parameters and provide proper input for the orthosis control unit. We are currently investigating the possibility to use advanced machine learning techniques for the identification of locomotion intentions from surface electromyography (sEMG) data. Current implementations have already demonstrated good accuracy during preliminary experiments on healthy subjects.
{{image class="left" url="images/research/unipd-logo-small.png" width="50" alt="unipd" title="unipd"}}University of Padua, [[http://www.gest.unipd.it DTG]] and BEM Laboratory [[http://www.dei.unipd.it DEI]]

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With respect to previous researches, we plan to develop more sophisticated sensor systems to capture a broader set of parameters and provide proper input for the orthosis control unit. We are currently investigating the possibility to use advanced machine learning techniques for the identification of locomotion intentions from surface electromyography (sEMG) data. Current implementations has already demonstrated good accuracy during preliminary experiments on healthy subjects.

University of Padua, IASLab and BEM Laboratories

Revision [164]

Edited on 2011-03-08 15:50:17 by MonicaReggiani

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{{image class="right" url="images/research/classification.jpg" width="350" alt="Classification, preliminary results" title="Classification, preliminary results"}}

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~~{{image class="right" url="images/research/classification..jpg" alt="Classification, preliminary results" title="Classification, preliminary results"}}~~

Revision [163]

Edited on 2011-03-08 15:47:59 by MonicaReggiani

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{{image class="right" url="images/research/classification..jpg" alt="Classification, preliminary results" title="Classification, preliminary results"}}
~- [[http://www.massimosartori.net Massimo Sartori]], University of Padua, Italy

Deletions:

~~~-[[http://www.massimosartori.net Massimo Sartori]], University of Padua, Italy~~

Revision [162]

Edited on 2011-03-08 15:30:21 by MonicaReggiani

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Second-cycle degree course (MSc level) in ""BioEngineering""

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~~Second-cycle degree course (MSc level) in BioEngineering~~

Revision [161]

Edited on 2011-03-08 15:29:20 by MonicaReggiani

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Next generation of tools for rehabilitation robotics will require advanced human-robot interfaces able to activate the device as soon as patient's motion intention is raised. Although great progress has been made in the century long effort to design and implement robotic exoskeletons and powered orthoses, many design challenges still remain. One of the factor limiting current exoskeletons and orthoses is the lack of direct information exchange between the human wearer's nervous system and the wearable device.
With respect to previous researches, we plan to develop more sophisticated sensor systems to capture a broader set of parameters and provide proper input for the orthosis control unit. We are currently investigating the possibility to use advanced machine learning techniques for the identification of locomotion intentions from surface electromyography (sEMG) data. Current implementations has already demonstrated good accuracy during preliminary experiments on healthy subjects.
=== Students ===
Silvia Spolaore
Second-cycle degree course (MSc level) in BioEngineering
University of Padua
Fabio Molon
Second-cycle degree course (MSc level) in Mechatronic Engineering
University of Padua

Deletions:

Next generation of tools for rehabilitation robotics will require advanced human-robot interfaces able to activate the device as soon as patient's motion intention is raised. Although great progress has been made in the century long effort to designa nd implement robotic exoskeletons and powered orthoses, many design challenges still remain. One of the factor limiting current exoskeletons and orthoses is the lack of direct information exchange between the human wearer's nervous system and the wearable device.
The focus of our resaerch is on the development of supporting devices for lower limbs, as restoring movement and functional abilities has a great impact on quality of life, simplifying the creation of social interaction. Additioanlly, there is a lack of research on such machiens compared to the advancements on upper extremity exoskeletons. With respect to previous researches, we plan to develop more sophisticated sensor system to capture a broader set of parameters and provide proper input for the orthosis control unit. We are currently investigating the possibility to use advanced machine learning techniques for the identification of locomotion intentions from surface electromyography (sEMG) data. Current implementations has already demonstrated good accuracy on preliminary experiments on healthy subjects.

Revision [160]

Edited on 2011-03-08 15:22:57 by MonicaReggiani

Additions:

Next generation of tools for rehabilitation robotics will require advanced human-robot interfaces able to activate the device as soon as patient's motion intention is raised. Although great progress has been made in the century long effort to designa nd implement robotic exoskeletons and powered orthoses, many design challenges still remain. One of the factor limiting current exoskeletons and orthoses is the lack of direct information exchange between the human wearer's nervous system and the wearable device.
The focus of our resaerch is on the development of supporting devices for lower limbs, as restoring movement and functional abilities has a great impact on quality of life, simplifying the creation of social interaction. Additioanlly, there is a lack of research on such machiens compared to the advancements on upper extremity exoskeletons. With respect to previous researches, we plan to develop more sophisticated sensor system to capture a broader set of parameters and provide proper input for the orthosis control unit. We are currently investigating the possibility to use advanced machine learning techniques for the identification of locomotion intentions from surface electromyography (sEMG) data. Current implementations has already demonstrated good accuracy on preliminary experiments on healthy subjects.

Revision [141]

Edited on 2011-02-25 16:03:48 by MonicaReggiani

Additions:

[[ClassificationSoftware Install the classification software]]

Deletions:

~~[[ClassificationSoftware Setup your classification software]]~~

Revision [139]

The oldest known version of this page was created on 2011-02-25 16:01:51 by MonicaReggiani