Development and evaluation of a novel force myography (FMG) based human-machine interface for transradial prosthetics: A comparative study with electromyography (EMG) techniques

Human-Machine Interfaces (HMIs) must bridge human skills with machine control, notably in active prosthesis. Electromyography (EMG) is the most popular prosthesis actuation method. However, researchers need new HMIs for active prosthesis development. This research introduces Forcemyography (FMG) based HMI using force- sensitive resistors (FSRs) to capture myoelectric data. A particularly constructed case with two integral parts—an internal and an exterior component—is FMG. This FMG enclosure adapts effortlessly to the user's limb and shape for best performance and comfort. FMG and sEMG were compared in the experimental evaluation. Stability, forecast accuracy, hair and sweat resistance, wearability, and cost-effectiveness were examined. FMG signals outperformed sEMG signals in this comprehensive examination. FMG outperformed sEMG in stability and prediction accuracy. FMG produced outstanding results right from capture without post-processing, a unique advantage. The specialised enclosure protected FSRs from outside interference and delivered precise signals. The Forcemyography (FMG)-based HMI is a breakthrough in active prosthesis technology. Its versatility, consistent signal acquisition, and user-centric design promise improved human-machine interactions. FMG leads the way to smooth, intuitive, and efficient humanmachine interface.

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Publication Details

Journal
Mehran University Research Journal of Engineering and Technology
Published
2024-10-01
DOI
https://doi.org/10.22581/muet1982.2948
Citations
1
Primary Topic
Muscle activation and electromyography studies
Type
article
Field-Weighted Citation Impact
0.18
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article

Development and evaluation of a novel force myography (FMG) based human-machine interface for transradial prosthetics: A comparative study with electromyography (EMG) techniques

Ihtisham Ul Haq, Muhammad Anas, Ghassan Husnain, Waqas Ahmad et al.
1 citations
Mehran University Research Journal of Engineering and Technology
Muscle activation and electromyography studies
0.18
article

Development and evaluation of a novel force myography (FMG) based human-machine interface for transradial prosthetics: A comparative study with electromyography (EMG) techniques

Ihtisham Ul Haq, Muhammad Anas, Ghassan Husnain, Waqas Ahmad, Azam Jan
article en
1 citations

Abstract

Human-Machine Interfaces (HMIs) must bridge human skills with machine control, notably in active prosthesis. Electromyography (EMG) is the most popular prosthesis actuation method. However, researchers need new HMIs for active prosthesis development. This research introduces Forcemyography (FMG) based HMI using force- sensitive resistors (FSRs) to capture myoelectric data. A particularly constructed case with two integral parts—an internal and an exterior component—is FMG. This FMG enclosure adapts effortlessly to the user's limb and shape for best performance and comfort. FMG and sEMG were compared in the experimental evaluation. Stability, forecast accuracy, hair and sweat resistance, wearability, and cost-effectiveness were examined. FMG signals outperformed sEMG signals in this comprehensive examination. FMG outperformed sEMG in stability and prediction accuracy. FMG produced outstanding results right from capture without post-processing, a unique advantage. The specialised enclosure protected FSRs from outside interference and delivered precise signals. The Forcemyography (FMG)-based HMI is a breakthrough in active prosthesis technology. Its versatility, consistent signal acquisition, and user-centric design promise improved human-machine interactions. FMG leads the way to smooth, intuitive, and efficient humanmachine interface.

Mehran University Research Journal of Engineering and TechnologyVol. 43(4)
Iqra National University (PK), University of Calabria (IT), Swinburne University of Technology (AU), University of Engineering and Technology Peshawar (PK)
Openalex Percentile: Top 52%
Muscle activation and electromyography studies
0.18
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