mlsanityData to 14 Oct 2026

BIONIX: A Wireless, Low-Cost Prosthetic Arm with Dual-Signal EEG and EMG Control

arXiv 2512.16929 ↗First posted 7 Dec 2025cs.LG eess.SPcited by 0

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Abstract (arXiv)

Affordable upper-limb prostheses often lack intuitive control systems, limiting functionality and accessibility for amputees in low-resource settings. This project presents a low-cost, dual-mode neuro-muscular control system integrating electroencephalography (EEG) and electromyography (EMG) to enable real-time, multi-degree-of-freedom control of a prosthetic arm. EEG signals are acquired using the NeuroSky MindWave Mobile 2 and transmitted via ThinkGear Bluetooth packets to an ESP32 microcontroller running a lightweight classification model. The model was trained on 1500 seconds of recorded EEG data using a 6-frame sliding window with low-pass filtering, excluding poor-signal samples and using a 70/20/10 training--validation--test split. The classifier detects strong blink events, which toggle the hand between open and closed states. EMG signals are acquired using a MyoWare 2.0 sensor and SparkFun wireless shield and transmitted to a second ESP32, which performs threshold-based detection. Three activation bands (rest: 0--T1; extension: T1--T2; contraction: greater than T2) enable intuitive elbow control, with movement triggered only after eight consecutive frames in a movement class to improve stability. The EEG-controlled ESP32 actuates four finger servos, while the EMG-controlled ESP32 drives two elbow servos. A functional prototype was constructed using low-cost materials (total cost approximately 240 dollars), with most expense attributed to the commercial EEG headset. Future work includes transitioning to a 3D-printed chassis, integrating auto-regressive models to reduce EMG latency, and upgrading servo torque for improved load capacity and grip strength. This system demonstrates a feasible pathway to low-cost, biologically intuitive prosthetic control suitable for underserved and global health applications.

Key facts. No citing papers in the map yet (data through 14 Oct 2026). Builds on 4 of its 21 references that are in the map. First posted on arXiv 7 Dec 2025.

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4 of 21 references.

References · 4

  1. 2021Multimodal Fusion of EMG and Vision for Human Grasp Intent Inference in Prosthetic Hand Controlcited by 13
  2. 2024A Powered Prosthetic Hand with Vision System for Enhancing the Anthropopathic Graspcited by 3
  3. 2022Grasp-and-Lift Detection from EEG Signal Using Convolutional Neural Networkcited by 2
  4. 2020Inexpensive surface electromyography sleeve with consistent electrode placement enables dexterous and stable prosthetic control through deep learningcited by 1

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