Miniaturized Wearable Ultrasound System for Simultaneous Prediction of Wrist Angle and Grip Force During Dynamic Reaching

Predicting grip force and wrist angle during dynamic hand movements is crucial for advancing upper-limb prosthetic systems, enabling simultaneous and proportional control of multiple degrees of freedom (DOFs). This study introduces a novel wearable ultrasound-based system that leverages M-mode data...

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Published inIEEE International Conference on Rehabilitation Robotics Vol. 2025; pp. 767 - 772
Main Authors Rima, Afsana Hossain, Taghizadeh, Zahra, Bashatah, Ahmed, Aher, Abhishek, Sikdar, Siddhartha
Format Conference Proceeding Journal Article
LanguageEnglish
Published United States IEEE 01.05.2025
Subjects
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ISSN1945-7901
1945-7901
DOI10.1109/ICORR66766.2025.11063113

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Abstract Predicting grip force and wrist angle during dynamic hand movements is crucial for advancing upper-limb prosthetic systems, enabling simultaneous and proportional control of multiple degrees of freedom (DOFs). This study introduces a novel wearable ultrasound-based system that leverages M-mode data from four single-element transducers placed on the forearm to capture muscle activity for the concurrent prediction of grip force and wrist angle. A multi-layer perceptron (MLP) regressor was utilized for the simultaneous prediction of both parameters, and a comparative analysis was conducted using a Gaussian process regressor (GPR), which is commonly adopted previously in similar studies. The system was validated on unseen data from five participants without limb loss. The MLP demonstrated superior performance compared to GPR, achieving \mathbf{R}^{\mathbf{2}} values of 0.85 \pm 0.06 for wrist angle prediction and 0.74 \pm 0.07 for grip force. These findings underscore the challenges of predicting simultaneous grip force and wrist angle during dynamic hand movements and highlight the need to address these issues for intuitive and practical prosthetic control in real-world scenarios.
AbstractList Predicting grip force and wrist angle during dynamic hand movements is crucial for advancing upper-limb prosthetic systems, enabling simultaneous and proportional control of multiple degrees of freedom (DOFs). This study introduces a novel wearable ultrasound-based system that leverages M-mode data from four single-element transducers placed on the forearm to capture muscle activity for the concurrent prediction of grip force and wrist angle. A multi-layer perceptron (MLP) regressor was utilized for the simultaneous prediction of both parameters, and a comparative analysis was conducted using a Gaussian process regressor (GPR), which is commonly adopted previously in similar studies. The system was validated on unseen data from five participants without limb loss. The MLP demonstrated superior performance compared to GPR, achieving \mathbf{R}^{\mathbf{2}} values of 0.85 \pm 0.06 for wrist angle prediction and 0.74 \pm 0.07 for grip force. These findings underscore the challenges of predicting simultaneous grip force and wrist angle during dynamic hand movements and highlight the need to address these issues for intuitive and practical prosthetic control in real-world scenarios.
Predicting grip force and wrist angle during dynamic hand movements is crucial for advancing upper-limb prosthetic systems, enabling simultaneous and proportional control of multiple degrees of freedom (DOFs). This study introduces a novel wearable ultrasound-based system that leverages M-mode data from four single-element transducers placed on the forearm to capture muscle activity for the concurrent prediction of grip force and wrist angle. A multi-layer perceptron (MLP) regressor was utilized for the simultaneous prediction of both parameters, and a comparative analysis was conducted using a Gaussian process regressor (GPR), which is commonly adopted previously in similar studies. The system was validated on unseen data from five participants without limb loss. The MLP demonstrated superior performance compared to GPR, achieving $\mathbf{R}^{\mathbf{2}}$ values of $0.85 \pm 0.06$ for wrist angle prediction and $0.74 \pm 0.07$ for grip force. These findings underscore the challenges of predicting simultaneous grip force and wrist angle during dynamic hand movements and highlight the need to address these issues for intuitive and practical prosthetic control in real-world scenarios.Predicting grip force and wrist angle during dynamic hand movements is crucial for advancing upper-limb prosthetic systems, enabling simultaneous and proportional control of multiple degrees of freedom (DOFs). This study introduces a novel wearable ultrasound-based system that leverages M-mode data from four single-element transducers placed on the forearm to capture muscle activity for the concurrent prediction of grip force and wrist angle. A multi-layer perceptron (MLP) regressor was utilized for the simultaneous prediction of both parameters, and a comparative analysis was conducted using a Gaussian process regressor (GPR), which is commonly adopted previously in similar studies. The system was validated on unseen data from five participants without limb loss. The MLP demonstrated superior performance compared to GPR, achieving $\mathbf{R}^{\mathbf{2}}$ values of $0.85 \pm 0.06$ for wrist angle prediction and $0.74 \pm 0.07$ for grip force. These findings underscore the challenges of predicting simultaneous grip force and wrist angle during dynamic hand movements and highlight the need to address these issues for intuitive and practical prosthetic control in real-world scenarios.
Author Bashatah, Ahmed
Taghizadeh, Zahra
Rima, Afsana Hossain
Aher, Abhishek
Sikdar, Siddhartha
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Snippet Predicting grip force and wrist angle during dynamic hand movements is crucial for advancing upper-limb prosthetic systems, enabling simultaneous and...
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SubjectTerms Adult
Biomechanical Phenomena - physiology
Computational modeling
dynamic movements
Dynamics
Female
Force
gaussian process regressor
Gaussian processes
Hand Strength - physiology
Hands
Humans
Male
multi-layer perceptron regressor
Proportional control
Prosthetics
simultaneous and proportional control
Transducers
Ultrasonic imaging
Ultrasonography - instrumentation
Ultrasonography - methods
Wearable Electronic Devices
wearable ultrasound
Wrist
Wrist - diagnostic imaging
Wrist - physiology
Title Miniaturized Wearable Ultrasound System for Simultaneous Prediction of Wrist Angle and Grip Force During Dynamic Reaching
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