5G-Enabled Smart Prosthetic Hand: Connectivity Analysis and Assessment
Ozan Karaali, Hossam Farag, Strahinja Dosen, Cedomir Stefanovic

TL;DR
This paper presents a proof-of-concept for a 5G-enabled prosthetic hand system that demonstrates low-latency connectivity and environmental perception, highlighting the feasibility of edge-connected bionic prosthetics.
Contribution
It introduces a novel framework integrating 5G connectivity with a smart prosthetic hand and evaluates its latency, establishing the first feasibility analysis of such a system.
Findings
Latency below 125 ms in realistic scenarios
Feasibility of 5G-enabled prosthetic control demonstrated
Edge computing effectively supports environmental inference
Abstract
In this paper, we demonstrate a proof-of-concept implementation of a framework for the development of edge-connected prosthetic systems. The framework is composed of a bionic hand equipped with a camera and connected to a Jetson device that establishes a wireless connection to the edge server, processing the received video stream and feeding back the inferred information about the environment. The hand-edge server connection is obtained either through a direct 5G link, where the edge server also functions as a 5G base station, or through a WiFi link. We evaluate the latency of closing the control loop in the system, showing that, in a realistic usage scenario, the connectivity and computation delays combined are well below 125 ms, which falls into the natural control range. To the best of our knowledge, this is the first analysis showcasing the feasibility of a 5G-enabled prosthetic…
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
Taxonomy
TopicsNeuroscience and Neural Engineering · Muscle activation and electromyography studies · Advanced Sensor and Energy Harvesting Materials
MethodsBalanced Selection
