Towards a real time kinect signature based human activity assessment at home

Gaddi Blumrosen; Yael Miron; Meir Plotnik; Nathan Intrator

doi:10.1109/bsn.2015.7299359

Towards a real time kinect signature based human activity assessment at home

Gaddi Blumrosen, Yael Miron, Meir Plotnik, Nathan Intrator

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

3 Scopus citations

Abstract

Tracking Human activity at home plays a growing factor in fields of security, and of bio-medicine. Microsoft Kinect is a non-wearable sensor that aggregate depth images with traditional optical video frames to estimate individuals' joints' location for kinematic analysis. When the subject of interest is out of Kinect coverage, or not in line of sight, the joints' estimations are distorted, which reduce the estimation accuracy, and can lead, in a scenario of multiple subjects, to erroneous estimations' assignment. In this work we derive features from Kinect joints and form a Kinect Signature (KS). This signature is used to identify different patients, differentiate them from others, exclude artifacts and derive the tracking quality. The suggested technology has the potential to assess human kinematics at home, reduce the cost of the patient traveling to the hospital, and improve the medical treatment follow-up.

Original language	English
Title of host publication	2015 IEEE 12th International Conference on Wearable and Implantable Body Sensor Networks, BSN 2015
Publisher	Institute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)	9781467372015
DOIs	https://doi.org/10.1109/bsn.2015.7299359
State	Published - 15 Oct 2015
Externally published	Yes
Event	12th IEEE International Conference on Wearable and Implantable Body Sensor Networks, BSN 2015 - Cambridge, United States Duration: 9 Jun 2015 → 12 Jun 2015

Publication series

Name	2015 IEEE 12th International Conference on Wearable and Implantable Body Sensor Networks, BSN 2015

Conference

Conference	12th IEEE International Conference on Wearable and Implantable Body Sensor Networks, BSN 2015
Country/Territory	United States
City	Cambridge
Period	9/06/15 → 12/06/15

Bibliographical note

Publisher Copyright:
© 2015 IEEE.

Keywords

Gait analsyis
Kinect
Motion tracking
Parkinson Diseases
Sensor Network

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

Access to Document

10.1109/bsn.2015.7299359

Cite this

Blumrosen, G., Miron, Y., Plotnik, M., & Intrator, N. (2015). Towards a real time kinect signature based human activity assessment at home. In 2015 IEEE 12th International Conference on Wearable and Implantable Body Sensor Networks, BSN 2015 Article 7299359 (2015 IEEE 12th International Conference on Wearable and Implantable Body Sensor Networks, BSN 2015). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/bsn.2015.7299359

Blumrosen, Gaddi ; Miron, Yael ; Plotnik, Meir et al. / Towards a real time kinect signature based human activity assessment at home. 2015 IEEE 12th International Conference on Wearable and Implantable Body Sensor Networks, BSN 2015. Institute of Electrical and Electronics Engineers Inc., 2015. (2015 IEEE 12th International Conference on Wearable and Implantable Body Sensor Networks, BSN 2015).

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abstract = "Tracking Human activity at home plays a growing factor in fields of security, and of bio-medicine. Microsoft Kinect is a non-wearable sensor that aggregate depth images with traditional optical video frames to estimate individuals' joints' location for kinematic analysis. When the subject of interest is out of Kinect coverage, or not in line of sight, the joints' estimations are distorted, which reduce the estimation accuracy, and can lead, in a scenario of multiple subjects, to erroneous estimations' assignment. In this work we derive features from Kinect joints and form a Kinect Signature (KS). This signature is used to identify different patients, differentiate them from others, exclude artifacts and derive the tracking quality. The suggested technology has the potential to assess human kinematics at home, reduce the cost of the patient traveling to the hospital, and improve the medical treatment follow-up.",

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Blumrosen, G, Miron, Y, Plotnik, M & Intrator, N 2015, Towards a real time kinect signature based human activity assessment at home. in 2015 IEEE 12th International Conference on Wearable and Implantable Body Sensor Networks, BSN 2015., 7299359, 2015 IEEE 12th International Conference on Wearable and Implantable Body Sensor Networks, BSN 2015, Institute of Electrical and Electronics Engineers Inc., 12th IEEE International Conference on Wearable and Implantable Body Sensor Networks, BSN 2015, Cambridge, United States, 9/06/15. https://doi.org/10.1109/bsn.2015.7299359

Towards a real time kinect signature based human activity assessment at home. / Blumrosen, Gaddi; Miron, Yael; Plotnik, Meir et al.
2015 IEEE 12th International Conference on Wearable and Implantable Body Sensor Networks, BSN 2015. Institute of Electrical and Electronics Engineers Inc., 2015. 7299359 (2015 IEEE 12th International Conference on Wearable and Implantable Body Sensor Networks, BSN 2015).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

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Blumrosen G, Miron Y, Plotnik M, Intrator N. Towards a real time kinect signature based human activity assessment at home. In 2015 IEEE 12th International Conference on Wearable and Implantable Body Sensor Networks, BSN 2015. Institute of Electrical and Electronics Engineers Inc. 2015. 7299359. (2015 IEEE 12th International Conference on Wearable and Implantable Body Sensor Networks, BSN 2015). doi: 10.1109/bsn.2015.7299359

Towards a real time kinect signature based human activity assessment at home

Abstract

Publication series

Conference

Bibliographical note

Keywords

UN SDGs

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