Clinical Background

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Upper Limb Loss

Upper-Limb Loss

Upper-limb loss affects millions of individuals across the United States and globally. Whether caused by trauma, disease, or congenital conditions, the loss of an arm or hand dramatically impacts a person's ability to perform daily tasks. With approximately 200,000 potential users in the U.S. alone, the demand for effective, accessible prosthetic solutions is significant and growing.

Abandonment Rates

Abandonment Rates

Nearly half of all upper-limb prosthetic users eventually abandon their devices. The leading reasons include discomfort, poor functionality, lack of intuitive control, and high cost of maintenance. This alarming rate highlights a critical gap in current prosthetic design — devices that fail to meet the real-world needs of patients.

Functional Limitations

Functional Limitations

Current prosthetic technology still struggles to replicate the natural dexterity of the human hand. Fine motor tasks such as picking up small objects, typing, or buttoning a shirt remain difficult or impossible for many prosthetic users. Without intuitive, real-time control systems, prosthetics often feel unnatural and frustrating to use — directly contributing to high abandonment rates.

Needs Statement

Upper-limb amputees need a low-cost, intuitive, and non-invasive prosthetic arm that can accurately interpret muscle signals in real time to deliver natural, multi-gesture hand control. Current solutions are often prohibitively expensive, uncomfortable, or incapable of replicating the dexterity required for everyday tasks. EMBRACE addresses this gap by leveraging surface EMG sensors and machine learning to classify user intent and drive a 6-degree-of-freedom prosthetic arm — restoring functional independence through a system that is accessible, comfortable, and responsive to the needs of real patients.

Our Goals

High abandonment rates show that prosthetic technology still does not fully meet user needs. EMBRACE combines biomedical engineering, mechanical design, signal processing, and human-centered design to change that.

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Affordable

Design a sub-$1,200 open-source prosthetic accessible to a wider range of patients.

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Intuitive Control

Use EMG signals and real-time machine learning to enable natural, multi-gesture hand control.

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Custom Fit

Leverage 3D-printed components to create a comfortable, patient-specific prosthetic fit.

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Real-World Usability

Validate system performance to help users regain functional control and confidence in everyday tasks.