Integrating computer vision into powered prosthetic devices is garnering attention as a potential avenue for enhancing functionality. These methodologies have been introduced to address challenges such as prosthetic abandonment, which can be attributed to the unreliability and lack of intuitiveness of myoelectric control. This paper provides insights into the current state, challenges, and future directions of integrating computer vision into prosthetic limb control systems. To this aim, a literature review was conducted, identifying 50 relevant studies (33 on upper-limb and 17 on lower-limb prostheses), sourced from Scopus, PubMed, and IEEE Xplore, with the search updated to May 2025. The hardware implementation aspects, including camera sensor positioning and computational units, were synthesized, as well as the computer vision approaches implemented with a specific emphasis on their implications for limb functional performance. The review identified strengths and suggested areas for improvement, emphasizing the need for studies on optimal camera placement and the feasibility of embedded computational units for real-world testing. Even if the reported results are promising, the performed analysis outlined the need to conduct usability studies and introduce vision-based approaches into lower-limb prosthesis control, which should be tested in real-world scenarios. Validation in real settings is crucial for these technologies to move beyond laboratory settings. • Literature review of vision-based control strategies for prosthetic limbs. • Identify gaps in real-world testing and multimodal integration for prosthetic control. • Guide future research on vision-based strategies for prosthetic control.
Cirelli et al. (2026) studied this question.