ArticleMethodsX2025
Development and evaluation of a head-controlled wheelchair system for users with severe motor impairments.
Article in MethodsX, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
0 citing papers in PubMed.
No citing paper in PubMed yet.
Corrections and comments
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Authors and funding
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
This paper presents an innovative and accessible hands-free wheelchair control system designed for individuals with severe motor impairments, particularly tetraplegic users. Unlike traditional joystick-based systems, which are often unsuitable for users with quadriplegia, our system relies on intuitive head-motion detection to enhance autonomy and ease of use. The system consists of a wearable motion-sensing cap equipped with an MPU-6050 sensor which is a 6-axis Inertial Measurement Unit (IMU) to capture head gestures, processed by an ATmega328 microcontroller (a low-power 8-bit AVR microcontroller widely used in embedded systems) integrated on an Arduino Nano development board. Wireless commands are transmitted via a Bluetooth module (HC-05) to the wheelchair's control unit consisting of an Arduino Uno microcontroller and BTS7960 motor drivers - high-power H-bridge modules that enable bidirectional control of DC motors. The operational flow, including signal processing, gesture interpretation, and wireless transmission, is structured following a detailed flowchart-based design. Experimental results indicate a high response rate and directional accuracy of over 90 % using a 45° head tilt. The optimal safe speed was determined to be 1.87 km/h with a Pulse Width Modulation (PWM) value of 180. Rather than designing a mechanical chassis from scratch, a commercially available electric wheelchair was modified by removing its joystick interface, allowing seamless integration of the head-controlled system. These findings validate the system's usability and precision under real-world conditions. By eliminating manual input and emphasizing simplicity, the proposed solution holds strong potential as a scalable and low-cost mobility aid, especially in low-resource environments.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.