Enhancing home area networks to facilitate telehealth services: Test-bed scenario with video-consultation-calls (VCC)

Shah, Mohib A.; Kim, Jin Man; Khadra, Mohamed; Feng, Dagan

doi:10.1109/icot.2014.6954671

Cited by 3 publications

(1 citation statement)

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“…In addition, real-time video compression schemes for users connected to access networks with high latency and different available bandwidth levels have been proposed [11]. In [12], authors present network traffic prioritization and load balancing schemes to enable Skype sessions over portable devices with satisfactory user experience for telehealth applications such as videoconsultation-call in a home area network. Our application design goals are different and we aim for video streams to be delivered without compression over wide-area network paths with low-latency characteristics, and take advantage of highspeed Gigabit networking between patient homes and a remote therapist clinic.…”

Section: Related Workmentioning

confidence: 99%

Synchronous Big Data analytics for personalized and remote physical therapy

Calyam

Mishra

Antequera

et al. 2016

Pervasive and Mobile Computing

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With gigabit networking becoming economically feasible and widely installed at homes, there are new opportunities to revisit in-home, personalized telehealth services. In this paper, we describe a novel telehealth eldercare service that we developed viz., "PhysicalTherapy-as-a-Service" (PTaaS) that connects a remote physical therapist at a clinic to a senior at home. The service leverages a high-speed, low-latency network connection through an interactive interface built on top of Microsoft Kinect motion sensing capabilities. The interface that is built using user-centered design principles for wellness coaching exercises is essentially a 'Synchronous Big Data' application due to its: (i) high data-in-motion velocity (i.e., peak data rate is ≈400 Mbps), (ii) considerable variety (i.e., measurements include 3D sensing, network health, user opinion surveys and video clips of RGB, skeletal and depth data), and (iii) large volume (i.e., several GB of measurement data for a simple exercise activity). The successful PTaaS delivery through this interface is dependent on the veracity analytics needed for correlation of the real-time Big Data streams within a session, in order to assess exercise balance of the senior without any bias due to network quality effects. Our experiments with PTaaS in an actual testbed involving senior homes in Kansas City with Google Fiber connections and our university clinic demonstrate the network configuration and time synchronization related challenges in order to perform online analytics. Our findings provide insights on how to: (a) enable suitable resource calibration and perform network troubleshooting for high user experience for both the therapist and the senior, and (b) realize a Big Data architecture for PTaaS and other similar personalized healthcare services to be remotely delivered at a large-scale in a reliable, secure and cost-effective manner.

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Section: Related Workmentioning

confidence: 99%