MyoVibe: Vibration Based Wearable Muscle Activation Detection in High Mobility Exercises

Publication/Creation Date
September 9 2015
MyoVibe (creator)
Frank Mokaya (creator)
Roland Lucas (creator)
Hae Young Noh (creator)
Pei Zhang (creator)
Carnegie Mellon University (contributor)
Lucas Physical Therapy Fitness (contributor)
Media Type
Journal Article
Persuasive Intent
Skeletal muscles are activated to generate the force needed for movement in most high motion sports and exercises. However, incorrect skeletal muscle activation during these sports and exercises, can lead to sub-optimal performance and injury. Existing techniques are susceptible to motion artifacts, particularly when used in high motion sports (e.g. jumping, cycling, etc.). They require limited body movement, or experts to manually interpret results making them unsuitable in sports scenarios. This paper presents MyoVibe, a wearable system for determining muscle activation in high motion exercise scenarios. MyoVibe senses muscle vibration signals obtained from a wearable network of accelerometers to determine muscle activation. By modeling the characteristics of muscles and high motion noise using extreme value analysis, MyoVibe can reduce noise due to high mobility exercises. Our system can predict muscle activation with greater than 97% accuracy in isometric low motion exercise cases, up to 90% accuracy in high motion exercises.

Presented at the Novel Sensing Techniques Panel Session, UBICOMP 2015.
HCI Platform
Discursive Type
Location on Body

Date archived
October 2 2015
Last edited
March 9 2020
How to cite this entry
MyoVibe, Frank Mokaya, Roland Lucas, Hae Young Noh, Pei Zhang. (September 9 2015). "MyoVibe: Vibration Based Wearable Muscle Activation Detection in High Mobility Exercises". 2015 ACM International Joint Conference on Pervasive and Ubiquitous Computing (UbiComp 2015). International Joint Conference On Pervasive And Ubiquitous Computing. Fabric of Digital Life.