Wireless accelerometer sensor data filtering using Recursive Least Squares adaptive filter

Saman Shafigh; Tanveer Zia; Nesa Mouzehkesh Pirborj

doi:10.1109/ISSNIP.2013.6529766

Wireless accelerometer sensor data filtering using Recursive Least Squares adaptive filter

Saman Shafigh, Tanveer Zia, Nesa Mouzehkesh Pirborj

Research output: Book chapter/Published conference paper › Conference paper › peer-review

1 Citation (Scopus)

6 Downloads (Pure)

Abstract

One of the applications of wireless accelerometer sensors is to monitor the human body motion and orientation. Such applications range from medical observations, diagnostics and fall detection to game console and entertainment. In typical wireless accelerometer sensors the received data is affected by the nonlinear environmental noises leading to a decreased resolution and the accuracy of received data. In this paper, a Recursive Least Squares (RLS) adaptive filter is used to filter the three-axial wireless accelerometer sensor received data. We used the Shimmer 9DOF wireless sensor placed on a robotic arm which is created toperform a precise 3D movement and is controlled by a PC. In the proposed RLS filter the input data is defined by the Shimmer acceleration data and the desired data is defined by the robotic arm orientation. The obtained results from running the RSL filter on the wireless acceleration sensor data shows a reasonable accuracy compared to the unfiltered data.

Original language	English
Title of host publication	Proceedings of the 2013 IEEE Eighth International Conference on Intelligent Sensors, Sensor Networks and Information Processing
Editors	M. Palaniswami
Place of Publication	United States
Publisher	IEEE, Institute of Electrical and Electronics Engineers
Pages	66-70
Number of pages	5
ISBN (Electronic)	9781467354998
DOIs	https://doi.org/10.1109/ISSNIP.2013.6529766
Publication status	Published - 2013
Event	2013 IEEE Eighth International Conference on Intelligent Sensors, Sensor Networks and Information Processing - University of Melbourne, Melbourne, Australia Duration: 02 Apr 2013 → 05 Apr 2013 https://web.archive.org/web/20130207041834/http://www.issnip.org:80/2013/index.html (Archived page)

Conference

Conference	2013 IEEE Eighth International Conference on Intelligent Sensors, Sensor Networks and Information Processing
Country/Territory	Australia
City	Melbourne
Period	02/04/13 → 05/04/13
Internet address	https://web.archive.org/web/20130207041834/http://www.issnip.org:80/2013/index.html (Archived page)

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10.1109/ISSNIP.2013.6529766

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Shafigh, S., Zia, T., & Mouzehkesh Pirborj, N. (2013). Wireless accelerometer sensor data filtering using Recursive Least Squares adaptive filter. In M. Palaniswami (Ed.), Proceedings of the 2013 IEEE Eighth International Conference on Intelligent Sensors, Sensor Networks and Information Processing (pp. 66-70). IEEE, Institute of Electrical and Electronics Engineers. https://doi.org/10.1109/ISSNIP.2013.6529766

Shafigh, Saman ; Zia, Tanveer ; Mouzehkesh Pirborj, Nesa. / Wireless accelerometer sensor data filtering using Recursive Least Squares adaptive filter. Proceedings of the 2013 IEEE Eighth International Conference on Intelligent Sensors, Sensor Networks and Information Processing. editor / M. Palaniswami. United States : IEEE, Institute of Electrical and Electronics Engineers, 2013. pp. 66-70

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title = "Wireless accelerometer sensor data filtering using Recursive Least Squares adaptive filter",

abstract = "One of the applications of wireless accelerometer sensors is to monitor the human body motion and orientation. Such applications range from medical observations, diagnostics and fall detection to game console and entertainment. In typical wireless accelerometer sensors the received data is affected by the nonlinear environmental noises leading to a decreased resolution and the accuracy of received data. In this paper, a Recursive Least Squares (RLS) adaptive filter is used to filter the three-axial wireless accelerometer sensor received data. We used the Shimmer 9DOF wireless sensor placed on a robotic arm which is created toperform a precise 3D movement and is controlled by a PC. In the proposed RLS filter the input data is defined by the Shimmer acceleration data and the desired data is defined by the robotic arm orientation. The obtained results from running the RSL filter on the wireless acceleration sensor data shows a reasonable accuracy compared to the unfiltered data.",

keywords = "Accelerometers, Adaptive signal processing, Body sensor networks, Recursive Least Squares, Wireless sensor networks",

author = "Saman Shafigh and Tanveer Zia and {Mouzehkesh Pirborj}, Nesa",

note = "Imported on 03 May 2017 - DigiTool details were: publisher = United States: IEEE, 2013. editor/s (773b) = M Palaniswami; Event dates (773o) = 2-5 April 2013; Parent title (773t) = IEEE International Conference on Intelligent Sensors, Sensor Networks and Information Processing (ISSNIP).; 2013 IEEE Eighth International Conference on Intelligent Sensors, Sensor Networks and Information Processing ; Conference date: 02-04-2013 Through 05-04-2013",

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doi = "10.1109/ISSNIP.2013.6529766",

language = "English",

pages = "66--70",

editor = "M. Palaniswami",

booktitle = "Proceedings of the 2013 IEEE Eighth International Conference on Intelligent Sensors, Sensor Networks and Information Processing",

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Shafigh, S, Zia, T & Mouzehkesh Pirborj, N 2013, Wireless accelerometer sensor data filtering using Recursive Least Squares adaptive filter. in M Palaniswami (ed.), Proceedings of the 2013 IEEE Eighth International Conference on Intelligent Sensors, Sensor Networks and Information Processing. IEEE, Institute of Electrical and Electronics Engineers, United States, pp. 66-70, 2013 IEEE Eighth International Conference on Intelligent Sensors, Sensor Networks and Information Processing, Melbourne, Victoria, Australia, 02/04/13. https://doi.org/10.1109/ISSNIP.2013.6529766

Wireless accelerometer sensor data filtering using Recursive Least Squares adaptive filter. / Shafigh, Saman; Zia, Tanveer; Mouzehkesh Pirborj, Nesa.
Proceedings of the 2013 IEEE Eighth International Conference on Intelligent Sensors, Sensor Networks and Information Processing. ed. / M. Palaniswami. United States: IEEE, Institute of Electrical and Electronics Engineers, 2013. p. 66-70.

Research output: Book chapter/Published conference paper › Conference paper › peer-review

TY - GEN

T1 - Wireless accelerometer sensor data filtering using Recursive Least Squares adaptive filter

AU - Shafigh, Saman

AU - Zia, Tanveer

AU - Mouzehkesh Pirborj, Nesa

N1 - Imported on 03 May 2017 - DigiTool details were: publisher = United States: IEEE, 2013. editor/s (773b) = M Palaniswami; Event dates (773o) = 2-5 April 2013; Parent title (773t) = IEEE International Conference on Intelligent Sensors, Sensor Networks and Information Processing (ISSNIP).

PY - 2013

Y1 - 2013

N2 - One of the applications of wireless accelerometer sensors is to monitor the human body motion and orientation. Such applications range from medical observations, diagnostics and fall detection to game console and entertainment. In typical wireless accelerometer sensors the received data is affected by the nonlinear environmental noises leading to a decreased resolution and the accuracy of received data. In this paper, a Recursive Least Squares (RLS) adaptive filter is used to filter the three-axial wireless accelerometer sensor received data. We used the Shimmer 9DOF wireless sensor placed on a robotic arm which is created toperform a precise 3D movement and is controlled by a PC. In the proposed RLS filter the input data is defined by the Shimmer acceleration data and the desired data is defined by the robotic arm orientation. The obtained results from running the RSL filter on the wireless acceleration sensor data shows a reasonable accuracy compared to the unfiltered data.

AB - One of the applications of wireless accelerometer sensors is to monitor the human body motion and orientation. Such applications range from medical observations, diagnostics and fall detection to game console and entertainment. In typical wireless accelerometer sensors the received data is affected by the nonlinear environmental noises leading to a decreased resolution and the accuracy of received data. In this paper, a Recursive Least Squares (RLS) adaptive filter is used to filter the three-axial wireless accelerometer sensor received data. We used the Shimmer 9DOF wireless sensor placed on a robotic arm which is created toperform a precise 3D movement and is controlled by a PC. In the proposed RLS filter the input data is defined by the Shimmer acceleration data and the desired data is defined by the robotic arm orientation. The obtained results from running the RSL filter on the wireless acceleration sensor data shows a reasonable accuracy compared to the unfiltered data.

KW - Accelerometers

KW - Adaptive signal processing

KW - Body sensor networks

KW - Recursive Least Squares

KW - Wireless sensor networks

U2 - 10.1109/ISSNIP.2013.6529766

DO - 10.1109/ISSNIP.2013.6529766

M3 - Conference paper

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EP - 70

BT - Proceedings of the 2013 IEEE Eighth International Conference on Intelligent Sensors, Sensor Networks and Information Processing

A2 - Palaniswami, M.

PB - IEEE, Institute of Electrical and Electronics Engineers

CY - United States

T2 - 2013 IEEE Eighth International Conference on Intelligent Sensors, Sensor Networks and Information Processing

Y2 - 2 April 2013 through 5 April 2013

ER -

Shafigh S, Zia T, Mouzehkesh Pirborj N. Wireless accelerometer sensor data filtering using Recursive Least Squares adaptive filter. In Palaniswami M, editor, Proceedings of the 2013 IEEE Eighth International Conference on Intelligent Sensors, Sensor Networks and Information Processing. United States: IEEE, Institute of Electrical and Electronics Engineers. 2013. p. 66-70 doi: 10.1109/ISSNIP.2013.6529766

Wireless accelerometer sensor data filtering using Recursive Least Squares adaptive filter

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