IoT Based Smart Wheelchair for Elderly Healthcare Monitoring

Objective: Development of a prototype wheelchair system that uses internet of thing (IoT) biophysical sensors for AI healthcare monitoring and assistive technology to support the independence of elderly patients. Algorithms are applied to analyse sensor data to provide feedback in real-time to the user and clinicians on risk factors. Methods: The system incorporated multiple sources of vital signs including body temperature, blood pressure, heart rate, oxygen saturation with AI in an integrated user interface and an autonomously navigated wheelchair. Results: A prototype of the assistive powered wheelchair was developed. Biophysical sensors were embedded in the wheelchair to collect patients' vital signs in real-time over ten seconds intervals and wirelessly uploaded to a cloud every forty seconds. A user interface was developed to record, visualise, and analyse patients' data for doctors and caregivers. Conclusion: The smart wheelchair will help patients drive autonomously within a predefined area. Vital sign signals from patients can be collected and analysed remotely. Further improvements can include use of different biophysical sensors, including for monitoring of falls and posture, and further development of algorithms to allow better management of patients' chronic condition.