Voice-controlled Wheelchair with Heart Rate and Location Monitoring
Keywords:Electric-powered wheelchair, People with disability, Voice recognition module V3, Arduino Uno, Heart rate, Location, Voice command
Nowadays, various control methods have been implemented to the existing electric-powered wheelchair (EPW). For example, controllers using joysticks, hands, and heads are already available at a high cost. Unfortunately, disabled people with upper limb disabilities do not benefit from these control methods. The risk of injury to wheelchair users while navigating the wheelchair alone is very concerning. In outdoor settings involving urban traffic, wheelchair users still face a high risk of injuries or health issues. Therefore, a voice-controlled wheelchair system aims to provide independent and self-guided mobility for people with disability (PWD) who suffered limited freedom of movement while using a wheelchair. This paper presents a prototype of a voice-controlled wheelchair with a heart rate and location monitoring system, where users can navigate their wheelchair using voice commands. The general health status and real-time location of the wheelchair user can be tracked via mobile phone application via Wi-Fi. Voice recognition module V3 is used to detect the user’s command. The signal from the voice module is transmitted to the Arduino Uno to control the wheelchair. Arduino Uno directs the motor driver to move the wheels in the desired direction. The joystick controller is also available as a second option to navigate the wheelchair’s direction. The wheelchair system also offers obstacle avoidance using the ultrasonic sensor to ensure the wheelchair user’s safety. The mobile phone application also has been created using Blynk IoT, which offers a remote monitoring system that allows the user and caregiver to monitor general health status and real-time location. The voice recognition control system can detect 96.69
% of the voice command under an ideal environment based on the experimental result. The heart rate sensor and GPS module used in this prototype can provide reliable data for general health status and location, yet not suitable for clinical use. Therefore, this wheelchair prototype-controlled system can be integrated into an actual wheelchair and operated in a real-world environment. Furthermore, the heart rate sensor can be replaced with a more accurate sensor, such as an ECG sensor to detect the heart rate.