Estimating Rotational Acceleration in Shoulder and Elbow Joints Using a Transformer Algorithm and a Fusion of Biosignals

In the present study, we used a transformer model and a fusion of biosignals to estimate rotational acceleration in elbow and shoulder joints. To achieve our study objectives, we proposed a mechanomyography (MMG) signal isolation technique based on a variational mode decomposition (VMD) algorithm. O...

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Bibliographic Details
Published in:Sensors (Basel, Switzerland) Switzerland), 2024-03, Vol.24 (6), p.1726
Main Authors: Bai, Yu, Guan, Xiaorong, He, Long, Wang, Zheng, Li, Zhong, Zhu, Meng
Format: Article
Language:English
Subjects:
Acceleration
Accuracy
Algorithms
Analysis
Bandwidths
Computational linguistics
Deep learning
Elbow
Elbow Joint
Electric transformers
Electromyography
estimation of human joint rotational acceleration
Exercise
Forecasts and trends
Language processing
Literature reviews
mechanomyography
Natural language
Natural language interfaces
Neural networks
Sensors
Shoulder
Signal processing
surface electromyography
transformer algorithm
Upper Extremity
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Summary:In the present study, we used a transformer model and a fusion of biosignals to estimate rotational acceleration in elbow and shoulder joints. To achieve our study objectives, we proposed a mechanomyography (MMG) signal isolation technique based on a variational mode decomposition (VMD) algorithm. Our results show that the VMD algorithm delivered excellent performance in MMG signal extraction compared to the commonly used technique of empirical mode decomposition (EMD). In addition, we found that transformer models delivered estimates of joint acceleration that were more precise than those produced by mainstream time series forecasting models. The average R values of transformer are 0.967, 0.968, and 0.935, respectively. Finally, we found that using a fusion of signals resulted in more precise estimation performance compared to using MMG signals alone. The differences between the average R values are 0.041, 0.053, and 0.043, respectively. Taken together, the VMD isolation method, the transformer algorithm and the signal fusion technique described in this paper can be seen as supplying a robust framework for estimating rotational acceleration in upper-limb joints. Further study is warranted to examine the effectiveness of this framework in other musculoskeletal contexts.
ISSN:1424-8220
1424-8220
DOI:10.3390/s24061726