Design and Development of a Hand Movement Controlled Wheelchair with NRF24 Module to Enhance Mobility for Individuals with Disabilities

Muhammad Huseini Lubis; Muhammad Muhammad; Fakhruddin Ahmad Nasution; Selamat Meliala; Salahuddin Salahuddin

doi:10.24036/voteteknika.v13i1.133170

Design and Development of a Hand Movement Controlled Wheelchair with NRF24 Module to Enhance Mobility for Individuals with Disabilities

Muhammad Huseini Lubis⁽¹⁾, Muhammad Muhammad⁽²⁾, Fakhruddin Ahmad Nasution⁽³⁾, Selamat Meliala⁽⁴⁾, Salahuddin Salahuddin⁽⁵⁾,
(1) Universitas Malikussaleh

Indonesia
(2) Universitas Malikussaleh

Indonesia
(3) Universitas malikussaleh

Indonesia
(4) Universitas Malikussaleh

Indonesia
(5) Universitas Malikussaleh

Indonesia

Corresponding Author

DOI : https://doi.org/10.24036/voteteknika.v13i1.133170

Full Text:

Language : id

Abstract

This study aims to design and develop a hand movement-controlled wheelchair system using NRF24L01 wireless technology to enhance the mobility of individuals with physical disabilities. This research employs a Research and Development (R&D) approach, consisting of design, implementation, and testing phases. The system integrates ADXL345 and MPU6050 accelerometer sensors to detect the user's hand movements, which are then translated into wheelchair control commands via NRF24L01 wireless communication. The test results indicate that the system achieves a response accuracy of over 95%, with an average response time of 0.3–0.5 seconds, and can operate up to 100 meters in an open environment. However, in areas with multiple obstacles, the communication range is reduced to 20–30 meters, and the system occasionally experiences interference from other devices operating on the 2.4 GHz frequency. Additionally, the accelerometer sensors may produce less accurate readings when subjected to excessive vibrations from uneven surfaces. The main contribution of this research is to provide a more intuitive, efficient, and user-friendly wheelchair control alternative compared to conventional methods such as joysticks or voice commands. Future developments could include artificial intelligence (AI) integration to improve movement detection accuracy, as well as additional sensors such as LiDAR for obstacle detection, thereby enhancing the safety and convenience of users.

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