Enabling Next-Generation Cloud-Connected Bionic Limbs Through 5G Connectivity

Despite the recent advancements in human-machine interfacing, contemporary assistive bionic limbs face critical challenges, including limited computational capabilities, high latency, and unintuitive control mechanisms, leading to suboptimal user experience and high abandonment rates. Addressing these challenges requires a shift toward intelligent, interconnected solutions powered by advances in Internet of Things systems, particularly wireless connectivity and edge/cloud computing. This article presents a conceptual approach to transform bionic limbs by harnessing the pervasive connectivity of 5and the significant computational power of cloud and edge servers, equipping them with capabilities not available hitherto. The system leverages a hierarchical distributed-computing architecture that integrates local, edge, and cloud computing layers. Time-critical tasks are handled by a local processing unit, while compute-intensive tasks are offloaded to edge and cloud servers, leveraging the high data rate, reliable and low latency capabilities of advanced cellular networks. We perform a proof-of-concept validation in a 5G testbed showing that such networks are capable of achieving data rates and fulfilling latency requirements for a natural prosthetic control, allowing for offloading of compute-intensive jobs to the edge/cloud servers. This is the first step towards the realization and real-world validation of cloud-connected bionic limb systems.

Authors

Institutions

Publication Details

Journal
IEEE Internet of Things Magazine
Published
2025-06-24
DOI
https://doi.org/10.1109/iotm.001.2400268
Citations
1
Primary Topic
Modular Robots and Swarm Intelligence
Type
article
Field-Weighted Citation Impact
0.71

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Enabling Next-Generation Cloud-Connected Bionic Limbs Through 5G Connectivity

Strahinja Došen, Čedomir Stefanović, Hossam Farag, Ozan Karaali
1 citations
IEEE Internet of Things Magazine
Modular Robots and Swarm Intelligence
0.71
article

Enabling Next-Generation Cloud-Connected Bionic Limbs Through 5G Connectivity

Strahinja Došen, Čedomir Stefanović, Hossam Farag, Ozan Karaali
article en
1 citations

Abstract

Despite the recent advancements in human-machine interfacing, contemporary assistive bionic limbs face critical challenges, including limited computational capabilities, high latency, and unintuitive control mechanisms, leading to suboptimal user experience and high abandonment rates. Addressing these challenges requires a shift toward intelligent, interconnected solutions powered by advances in Internet of Things systems, particularly wireless connectivity and edge/cloud computing. This article presents a conceptual approach to transform bionic limbs by harnessing the pervasive connectivity of 5and the significant computational power of cloud and edge servers, equipping them with capabilities not available hitherto. The system leverages a hierarchical distributed-computing architecture that integrates local, edge, and cloud computing layers. Time-critical tasks are handled by a local processing unit, while compute-intensive tasks are offloaded to edge and cloud servers, leveraging the high data rate, reliable and low latency capabilities of advanced cellular networks. We perform a proof-of-concept validation in a 5G testbed showing that such networks are capable of achieving data rates and fulfilling latency requirements for a natural prosthetic control, allowing for offloading of compute-intensive jobs to the edge/cloud servers. This is the first step towards the realization and real-world validation of cloud-connected bionic limb systems.

IEEE Internet of Things MagazineVol. 8(4)
Aalborg University (DK)
Danmarks Frie Forskningsfond
Affordable and clean energy
Openalex Percentile: Top 31%
Modular Robots and Swarm Intelligence
0.71
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.