Comparison of synergy patterns between the right and left hand while performing postures and object grasps

Shenoy, Prajwal; Gupta, Anurag; S.K.M., Varadhan

doi:10.1038/s41598-023-47620-9

Cited by 2 publications

(1 citation statement)

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“…The identified synergies frequently correspond to common grip types such as power grips or precision grips, as well as finer adjustments for object manipulation [ 51 ]. By flexibly combining these synergies, the neuromuscular system can generate a wide repertoire of hand postures and movements required for dexterous object interactions [ 52 , 54 ]. The choice of the set of gestures presented in this paper is based on a variety of hand exercises, wherein the participant is required to apply grasping, flexion, and extension force in order to maintain these gestures, which present varying degrees of difficulty.…”

Section: Methodsmentioning

confidence: 99%

Comparative Study of sEMG Feature Evaluation Methods Based on the Hand Gesture Classification Performance

Hellara,

Barioul,

Sahnoun

et al. 2024

Sensors

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Effective feature extraction and selection are crucial for the accurate classification and prediction of hand gestures based on electromyographic signals. In this paper, we systematically compare six filter and wrapper feature evaluation methods and investigate their respective impacts on the accuracy of gesture recognition. The investigation is based on several benchmark datasets and one real hand gesture dataset, including 15 hand force exercises collected from 14 healthy subjects using eight commercial sEMG sensors. A total of 37 time- and frequency-domain features were extracted from each sEMG channel. The benchmark dataset revealed that the minimum Redundancy Maximum Relevance (mRMR) feature evaluation method had the poorest performance, resulting in a decrease in classification accuracy. However, the RFE method demonstrated the potential to enhance classification accuracy across most of the datasets. It selected a feature subset comprising 65 features, which led to an accuracy of 97.14%. The Mutual Information (MI) method selected 200 features to reach an accuracy of 97.38%. The Feature Importance (FI) method reached a higher accuracy of 97.62% but selected 140 features. Further investigations have shown that selecting 65 and 75 features with the RFE methods led to an identical accuracy of 97.14%. A thorough examination of the selected features revealed the potential for three additional features from three specific sensors to enhance the classification accuracy to 97.38%. These results highlight the significance of employing an appropriate feature selection method to significantly reduce the number of necessary features while maintaining classification accuracy. They also underscore the necessity for further analysis and refinement to achieve optimal solutions.

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Section: Methodsmentioning

confidence: 99%

Comparative Study of sEMG Feature Evaluation Methods Based on the Hand Gesture Classification Performance

Hellara,

Barioul,

Sahnoun

et al. 2024

Sensors

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Task demands modulate distal limb handedness: A comparative analysis of prehensile synergies of the dominant and non-dominant hand

Shenoy,

2024

Sci Rep

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The dynamic dominance hypothesis of handedness suggests a distinct control strategy for the dominant and the non-dominant limb. The hypothesis demonstrated that the dominant proximal limb is tuned for optimal trajectory control while the non-dominant limb is tuned for a stable grasp. Whether the hypothesis can be extended to distal segments like fingers, especially during a five-fingered grasp, has been studied little. To examine this, an attempt was made to compare the prehensile synergies and force magnitudes of the dominant (DOM) and non-dominant hands (NDOM) during a 5-fingered prehension task. Participants traced a trapezoidal and inverse trapezoidal path with their thumbs on a sliding platform while holding a handle in static equilibrium. The DOM hand performed better only in the inverse trapezoid condition, exhibiting a reduced grip force and increased synergy index aligning with the dynamic dominance hypothesis. No differences were observed for the trapezoid condition, likely due to reduced task demands. The study also explored changes in anticipatory synergy adjustments between the DOM and NDOM hands, but the differences were non-significant. Overall, the DOM hand demonstrated better force coordination than the NDOM hand in challenging conditions. Applications of the study in the objective assessment of handedness were proposed.

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Comparison of synergy patterns between the right and left hand while performing postures and object grasps

Cited by 2 publications

References 34 publications

Comparative Study of sEMG Feature Evaluation Methods Based on the Hand Gesture Classification Performance

Comparative Study of sEMG Feature Evaluation Methods Based on the Hand Gesture Classification Performance

Task demands modulate distal limb handedness: A comparative analysis of prehensile synergies of the dominant and non-dominant hand

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