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Course I  -  SIAMOC-SISMES joint session

Wearable sensors for motion analysis in sport and rehabilitation: a guide to their use and informed interpretation

Sports sector is constantly evolving and changing rapidly also thanks to the recent opportunities offered by technological development. Taking advantage of increasingly miniaturized and wearable hardware solutions, large computing and data storage capacities, better network connection potential, nowadays the use of wearable sensors for movement analysis in sport is a reality and is expected to transform both the amateur and professional sports world. Individual athletes, sports teams, coaches and healthcare professionals can already make use of technological solutions in the field and can obtain large amounts of data to support their sports monitoring activities both for optimizing performance and for reducing the risk of injury. With this joint pre-congress course, SIAMOC and SISMES as scientific societies wishes to combine their skills and experience in the analysis of movement using wearable technologies and in functional evaluation in sport to offer a theoretical-practical insight into the conscious use of these technologies in sport. The event will be organized according to the following schedule:

Joseph Vannozzi

Antonio Tessitore

Foro Italico University of Rome

Introduction to the course: what the field asks and what the technology can offer

Pietro Picerno 

eCampus University

Mark Good

Campus Biomedical University

Movement analysis methodologies and protocols for sports performance assessment

Injury risk assessment and the management of the injured athlete

Joseph Vannozzi

Antonio Tessitore

Foro Italico University of Rome

Final summary: potential and challenges on the use of wearable sensors in sport

Course II

Francesca Sylos Labini

Germana Cappellini

Saint Lucia Foundation
Rome Italy

Surface electromyography:
from single muscle to spinal maps

Daniel Borzelli

University of Messina, Italy

- What is EMG signal
- Acquisition methods
(surface, needle, arrays, etc.)
- Preparation of the subject, positioning of the electrodes and muscle identification
- Acquisition of the signal
(synchronization with systems, pre-amplification, etc.)
- Signal pre-processing (artifact filtering and identification)
- Signal analysis(averaging, normalization, frequency analysis)
- Muscle synergies
  • decomposition algorithms and methods
     _cc781905-5cde-3194-bb3b-136bad5 cf58d_ (spatial, temporal, space-time, space-by-time)
  • remuscles of spectral coherence (muscle networks)
  • identification of the number of modules
  • clustering and comparison between different groups/subjects
  • practical examples
- Spinal maps
  • theory
  • types of myotomal charts
(Sharrard and Kendall)
  • from EMGs to spinal maps
  • practical examples
- EMG arrays
  • limitations of bipolar EMG
  • information from the hosts
  • decomposition of motor units
  • motor units and muscle synergies
  • practical examples
- Practical part
  • recording and processing of emg in different muscles and in different conditions

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