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Extraction of spatial information for low-bandwidth telerehabilitation applications

This study introduces a novel method to extract depth information from 2D video using Microsoft Kinect sensor and open-source tools. By plotting this data alongside images, more accurate rehabilitation assessments can be made without relying on challenging 3D video transmission. The framework presented offers a practical solution for situations where network bandwidth is limited, providing valuable spatial resolution for telerehabilitation applications.

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Extraction of spatial information for low-bandwidth telerehabilitation applications

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  1. Extraction of spatial information for low-bandwidth telerehabilitationapplications Kok Kiong Tan, PhD; Arun Shankar Narayanan; Choon Huat Koh, PhD; Kevin Caves; Helen Hoenig, MD, PhD

  2. Aim • Introduce innovative ways to use information about the depth of selected objects with 2-dimensional (2D) video for telerehabilitation applications. • Relevance • Rehabilitation assessments may require spatial information to accurately assess patients. • Sending 3-dimensional (3D) video data over low-bandwidth networks is extremely challenging.

  3. Method • Used Microsoft Kinect sensor together with opensource color detection and tracking library package to extract desired depth data from image. • Plotted extracted depth data on graph that was then displayed alongside images to allow sensible conclusions about patient’s condition. • Presented examples of rehabilitation assessments for which spatial information is required as well as solutions to leverage the proposed approach.

  4. Results Example: Tracking a single object. Example: Tracking body joints in cane height assessment.

  5. Conclusion • Effectiveness was shown for a framework to extract information about depth and transmit it with 2D images for use in rehabilitation. • This framework should prove very useful for providing information about spatial resolution when limited network bandwidth hinders conventional 3D video transmission.

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