A Telepresence Wheelchair with 360-Degree Vision Using WebRTC

Abstract

This paper presents an innovative approach to develop an advanced 360-degree vision telepresence wheelchair for healthcare applications. The study aims at improving a wide field of view surrounding the wheelchair to provide safe wheelchair navigation and efficient assistance for wheelchair users. A dual-fisheye camera is mounted in front of the wheelchair to capture images which can be then streamed over the Internet. A web real-time communication (WebRTC) protocol was implemented to provide efficient video and data streaming. An estimation model based on artificial neural networks was developed to evaluate the quality of experience (QoE) of video streaming. Experimental results confirmed that the proposed telepresence wheelchair system was able to stream a 360-degree video surrounding the wheelchair smoothly in real-time. The average streaming rate of the entire 360-degree video was 25.83 frames per second (fps), and the average peak signal to noise ratio (PSNR) was 29.06 dB. Simulation results of the proposed QoE estimation scheme provided a prediction accuracy of 94%. Furthermore, the results showed that the designed system could be controlled remotely via the wireless Internet to follow the desired path with high accuracy. The overall results demonstrate the effectiveness of our proposed approach for the 360-degree vision telepresence wheelchair for assistive technology applications.

IoT-Based Technologies for Addressing the Unique Healthcare Needs of the Elderly Population

“…Assistive robots can undertake the position of a human presence for the elderly when it is connected with their actual caretakers and doctors virtually (Koceski and Koceska, 2016;Almeida et al, 2022;Orlandini et al, 2016). IoT robot technology and automation integrated with a wheelchair were made for real-time monitoring (Chatterjee and Roy, 2021); the system captured the environment with an array of cameras to achieve efficient and safe navigational capability (Ha et al, 2020). IoT-based wearables integrated with robotics can take in all the variables and process the data to understand in real-time the patients' needs and cater in a more adaptive manner (Loza-Matovelle et al, 2019;Luperto et al, 2022).…”

“…The commonly observed psychiatric and neurodegenerative disorders among the older population are Alzheimer's disease, Parkinson's disease, dementia, depression, and schizophrenia. Multiple studies have been done (Aljehani et al, 2018;Ha et al, 2020) that have used IoT-based technology concerning these conditions. Tanaka et al (2018), Faedda et al (2016), O'Brien et al (2017 have used IoT-based wrist-worn accelerometers to measure the physical activities of participants with major depressive disorders, bipolar disorders, borderline personality disorders, attention deficit hyperactivity disorders, and healthy controls to distinguish between the activity patterns.…”

Telepresence in the Recent Literature with a Focus on Robotic Platforms, Applications and Challenges

“…Tests conducted on the platform showed positive attitudes towards it and a willingness to use it. A wheelchair was also presented in [33] as a telepresence system with potential benefits for individuals with mobility challenges. It was designed to allow for safe navigation and aimed to provide two-way video communication and to allow for social interaction.…”

IoT-based Technologies for Addressing the Unique Healthcare Needs of the Elderly Population

“…Assistive robots can undertake the position of a human presence for the elderly when it is connected with their actual caretakers and doctors virtually [101][102][103]. IoT robot technology and automation integrated with a wheelchair were made for real-time monitoring [104]; the system captured the environment with an array of cameras to achieve efficient and safe navigational capability [105]. IoT-based wearables integrated with robotics can take in all the variables and process the data to understand in real-time the patients' needs and cater in a more adaptive manner [74,106].…”

“…The commonly observed psychiatric and neurodegenerative disorders among the older population are Alzheimer's disease, Parkinson's disease, dementia, depression, and schizophrenia. Multiple studies have been done [199,105] that have used IoT-based technology concerning these conditions. Tanaka [206], Faedda [207], [208] have used IoTbased wrist-worn accelerometers to measure the physical activities of participants with major depressive disorders, bipolar disorders, borderline personality disorders, attention deficit hyperactivity disorders, and healthy controls to distinguish between the activity patterns.…”