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Telerehabilitation (TR) is getting ever more popular because it is effective in bringing rehabilitation services to rural populations by means of audiovisual systems and its initial implementation studies presented encouraging results. TR is proven to be helpful, with benefits in terms of reduced travel time, cost, and availability of specialists’ support in local communities. However, TR systems that are usable under low-bandwidth network environments are rare. This article introduces the development of a TR system with customized consultation categories for users to choose from, depending on requirements. Each category, with its preset parameter values, is discussed in detail by demonstrating relevant rehabilitation exercises. A novel bandwidth adaptation algorithm is also presented for optimal utilization of the dynamic network conditions, which ensures the system functionality even under narrow-bandwidth environments. Experiment results show that the system is able to perform effectively in each consultation category while the rehabilitation exercises are being performed. The proposed algorithm is also verified for its ability to adapt the content quality and effectively utilize the network under constrained conditions. A survey conducted on the video quality of the system under low-bandwidth conditions shows encouraging results for a large-scale deployment of the application. [ABSTRACT FROM AUTHOR]

Telemedicine applications, based on two-dimensional (2D) video conferencing technology, have been around for the past 15 to 20 yr. They have been demonstrated to be acceptable for face-to-face consultations and useful for visual examination of wounds and abrasions. However, certain telerehabilitation assessments need the use of spatial information in order to accurately assess the patient’s condition and sending three-dimensional video data over low-bandwidth networks is extremely challenging. This article proposes an innovative way of extracting the key spatial information from the patient’s movement during telerehabilitation assessment based on 2D video and then presenting the extracted data by using graph plots alongside the video to help physicians in assessments with minimum burden on existing video data transfer. Some common rehabilitation scenarios are chosen for illustrations, and experiments are conducted based on skeletal tracking and color detection algorithms using the Microsoft Kinect sensor. Extracted data are analyzed in detail and their usability discussed. [ABSTRACT FROM AUTHOR]

In-circuit impedance extraction of a time-variant electrical system is essential for real-time condition monitoring purpose. This paper looks into the design consideration of real-time in-circuit monitoring for a time-variant system based on inductive coupling approach and discrete Fourier transform in a moving window. By using two clamped-on-type inductive probes, the proposed setup eliminates the need of voltage sensors to measure the terminal voltages of system-under-monitoring (SUM) and, hence, eliminates direct electrical contact with the SUM. Therefore, it facilitates ease of mounting and disassembly. Experimental results show that with careful design consideration, the proposed method has the ability to measure the in-circuit impedance of a time-variant system in real time, which facilitates useful inputs for early detection of abnormality of the monitored electrical system that is time variant in nature. [ABSTRACT FROM AUTHOR]