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Synergistic Control Technology: Muscle Activation-Based Intention Estimation and Vision-aid Assistance in Upper Limb Prosthetics

Project description

Synergistic control technology for upper limb prosthetics

The demand for prosthetic devices and assistive technologies is rising due to increased amputation rates from accidents and an ageing population. Advancements in prosthetics enhance healthcare, rehabilitation, and workforce participation for amputees, benefiting society and the economy. Supported by the Marie Skłodowska-Curie Actions programme, the SynConT project will develop a novel Synergetic SPC (SSPC) framework to improve accuracy, robustness, and interactivity. It will address current model limitations with a signal processing algorithm for muscle activation detection, a machine learning model for intention estimation, and a vision-aided real-time grasping assistance algorithm for upper limb prosthetics. Offline simulations and clinical trials will support the development of this Synergistic Control Technology.

Objective

Prosthetic devices and their assistive technologies (ATs) have been socially demanded by several factors, including higher rates of traumatic amputations from accidents and an aging population. Regarding upper limb prosthetics, the amputation statistics show that the major cause is traumatic incidents, such as workplace or road accidents, particularly affecting the working-age population. The demand also has accelerated while human life expectancy increases, and society enters an aging demographic. By 2070, the share of the population aged 65 and over is expected to grow from 20% in 2019 to nearly 30%. The Global incidence of traumatic amputations has increased including upper-limb amputation around 16.4%. To this demand, the European orthopedic prosthetics market is projected to grow (Compound annual growth rate (CAGR): 5.4%) from 2024 to 2030 and over 75000 prosthetists are required globally to support individuals with traumatic amputations1. Advancements in upper-limb prosthetics improve healthcare, rehabilitation, daily life, and workforce participation for amputees, benefiting society and boosting economic growth.
In this proposal, A Synergetic SPC (SSPC) based novel framework is proposed and it will offer highly accurate, robust, and object interactive advantages. SSPC will overcome LMs by 1) Design a signal processing algorithm for the acquisition of muscle unit activation and Machine learning (ML)-based intention estimation model by spatial and temporal signal consideration, 2) Vision-aid real-time grasping assistance algorithm, and 3) Design SSPC framework. (a) Offline simulation analysis and (b) Real-time clinical trials will be conducted as solid support of Synergistic Control Technology: Muscle Activation-Based Intention Estimation and Vision-aid Assistance in Upper Limb Prosthetics (SynConT). It will contribute to prosthetics technology beyond the state of the art and bring it to daily life.

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HORIZON-TMA-MSCA-PF-EF - HORIZON TMA MSCA Postdoctoral Fellowships - European Fellowships

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Call for proposal

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(opens in new window) HORIZON-MSCA-2024-PF-01

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Coordinator

IMPERIAL COLLEGE OF SCIENCE TECHNOLOGY AND MEDICINE
Net EU contribution

Net EU financial contribution. The sum of money that the participant receives, deducted by the EU contribution to its linked third party. It considers the distribution of the EU financial contribution between direct beneficiaries of the project and other types of participants, like third-party participants.

€ 260 347,92
Address
SOUTH KENSINGTON CAMPUS EXHIBITION ROAD
SW7 2AZ London
United Kingdom

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Region
London Inner London — West Westminster
Activity type
Higher or Secondary Education Establishments
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Total cost

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