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Episode 19 From EMG to TLVs Picking the Right Occupational Exoskeleton with Dr Jason Gillette

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Manage episode 504022962 series 3598595
Content provided by Exoskeleton Report & Wearable Robotics Association, Exoskeleton Report, and Wearable Robotics Association. All podcast content including episodes, graphics, and podcast descriptions are uploaded and provided directly by Exoskeleton Report & Wearable Robotics Association, Exoskeleton Report, and Wearable Robotics Association or their podcast platform partner. If you believe someone is using your copyrighted work without your permission, you can follow the process outlined here https://podcastplayer.com/legal.

Dr. Sugar and I are proud to be able to share Episode 19 of the Exoskeletons and Wearable Robotics Podcast for ExR's Patreon Supporters! This time, we are lucky to have as a guest Dr. Jason Gillette, who shares his impressions of occupational exoskeletons. His Biomedical Engineering degree, decades of hands-on expertise in ergonomics and multiple industrial exo projects have given him a deep understanding of the field. During this conversation, he is happy to share his observations on evaluating and task-matching industrial exoskeletons and wearable devices. Together, we discuss tools and methodologies for recording and analyzing job sites, from simple phone recording to EMG sensor studies and everything in between. The conversation flows between biomechanics to simple observations, underlyning the importance of understanding objective and subjective data when running pilots.

Sample of Dr. Gillette's Work:
- Electromyography-based fatigue assessment of an upper body exoskeleton during automotive assembly - Cambridge University Press, 2022
- Artificial Intelligence for Injury Prevention (Professional Safety, Dec 2024): https://www.assp.org/docs/default-source/psj-articles/f1butleryounggillette_1224.pdf
Links:
Exoskeleton Report: http://exoskeletonreport.com
Wearable Robotics Association: https://wearablerobotics.com
If you enjoy this content, join the physical revolution on Patreon / exoskeletonreport
Special thanks to our Patreon supporters for helping make this episode a reality!

Support the show

  continue reading

Chapters

1. Introduction (00:00:00)

2. What are some tasks that make a lot of sense for occupational/industrial exoskeleton? (00:12:29)

3. Can we have a digital tool that helps with exoskeleton to task matching? (00:17:42)

4. TLV Equations (TLV = Threshold Limit Value, In this context it’s the Upper Limb Localized Fatigue TLV used to relate %MVC (percent of maximum voluntary contraction)) and duty cycle for raised-arm workand ways to calculate if a job is injury inducing? (00:22:35)

5. Lessons learned from trials at companies like Toyota and John Deere (00:30:36)

6. Additional hints or tips on exoskeleton to task matching. (00:36:11)

7. Current work on evaluationing occupational exoskeletons in a medical setting for patient handling. (00:40:12)

8. Observations on adoption of physical assistive technology. (00:49:05)

9. Call to action: be more open to sharing field and lab data. (00:55:01)

20 episodes

Artwork
iconShare
 
Manage episode 504022962 series 3598595
Content provided by Exoskeleton Report & Wearable Robotics Association, Exoskeleton Report, and Wearable Robotics Association. All podcast content including episodes, graphics, and podcast descriptions are uploaded and provided directly by Exoskeleton Report & Wearable Robotics Association, Exoskeleton Report, and Wearable Robotics Association or their podcast platform partner. If you believe someone is using your copyrighted work without your permission, you can follow the process outlined here https://podcastplayer.com/legal.

Dr. Sugar and I are proud to be able to share Episode 19 of the Exoskeletons and Wearable Robotics Podcast for ExR's Patreon Supporters! This time, we are lucky to have as a guest Dr. Jason Gillette, who shares his impressions of occupational exoskeletons. His Biomedical Engineering degree, decades of hands-on expertise in ergonomics and multiple industrial exo projects have given him a deep understanding of the field. During this conversation, he is happy to share his observations on evaluating and task-matching industrial exoskeletons and wearable devices. Together, we discuss tools and methodologies for recording and analyzing job sites, from simple phone recording to EMG sensor studies and everything in between. The conversation flows between biomechanics to simple observations, underlyning the importance of understanding objective and subjective data when running pilots.

Sample of Dr. Gillette's Work:
- Electromyography-based fatigue assessment of an upper body exoskeleton during automotive assembly - Cambridge University Press, 2022
- Artificial Intelligence for Injury Prevention (Professional Safety, Dec 2024): https://www.assp.org/docs/default-source/psj-articles/f1butleryounggillette_1224.pdf
Links:
Exoskeleton Report: http://exoskeletonreport.com
Wearable Robotics Association: https://wearablerobotics.com
If you enjoy this content, join the physical revolution on Patreon / exoskeletonreport
Special thanks to our Patreon supporters for helping make this episode a reality!

Support the show

  continue reading

Chapters

1. Introduction (00:00:00)

2. What are some tasks that make a lot of sense for occupational/industrial exoskeleton? (00:12:29)

3. Can we have a digital tool that helps with exoskeleton to task matching? (00:17:42)

4. TLV Equations (TLV = Threshold Limit Value, In this context it’s the Upper Limb Localized Fatigue TLV used to relate %MVC (percent of maximum voluntary contraction)) and duty cycle for raised-arm workand ways to calculate if a job is injury inducing? (00:22:35)

5. Lessons learned from trials at companies like Toyota and John Deere (00:30:36)

6. Additional hints or tips on exoskeleton to task matching. (00:36:11)

7. Current work on evaluationing occupational exoskeletons in a medical setting for patient handling. (00:40:12)

8. Observations on adoption of physical assistive technology. (00:49:05)

9. Call to action: be more open to sharing field and lab data. (00:55:01)

20 episodes

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