In this research, an innovative smart wheelchair designed to enhance mobility and health monitoring for individuals with disabilities is introduced. The wheelchair incorporates a tri-wheel mechanism, enabling seamless navigation over various terrains, including stairs. This design addresses the common limitations of traditional wheelchairs by providing increased autonomy and flexibility to users. Central to the design is the integration of advanced sensor networks and Internet of Things (IoT) technology. The wheelchair is equipped with an Electroencephalography (EEG) system that allows users to control movements using neural impulses, providing a hands-free operation mode. This feature is particularly beneficial for users with severe physical impairments, enabling them to navigate more independently. In addition to mobility enhancements, the smart wheelchair features comprehensive health monitoring capabilities through continuously monitoring vital signs such as blood oxygen levels (SpO2), and electrocardiogram (ECG) data. These health metrics are regularly transmitted to healthcare providers via a secure IoT platform. In emergency situations, the system is programmed to automatically send alerts, including the patient’s location, to caregivers and emergency services. The study demonstrates that the smart wheelchair not only improves mobility for users but also significantly enhances their quality of life by integrating health monitoring and emergency response features. This innovation represents a step forward in developing assistive technologies that support independent living and proactive healthcare management in smart cities.
Previous Article in event
Previous Article in session
Next Article in event
Next Article in session
AN IOT-BASED SMART WHEELCHAIR WITH EEG CONTROL AND VITAL SIGN MONITORING
Published:
26 November 2024
by MDPI
in 11th International Electronic Conference on Sensors and Applications
session Sensor Networks, IoT, Smart Cities and Heath Monitoring
https://doi.org/10.3390/ecsa-11-20489
(registering DOI)
Abstract:
Keywords: Smart Stair-climbing wheelchair, EEG control, Internet of Things, Vital Sign Monitoring