Wireless accelerometer sensor data filtering using Recursive Least Squares adaptive filter

Saman Shafigh, Tanveer Zia, Nesa Mouzehkesh Pirborj

Research output: Book chapter/Published conference paperConference paper

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 languageEnglish
Title of host publicationProceedings of the 2013 IEEE Eighth International Conference on Intelligent Sensors, Sensor Networks and Information Processing
EditorsM. Palaniswami
Place of PublicationUnited States
PublisherIEEE, Institute of Electrical and Electronics Engineers
Pages66-70
Number of pages5
ISBN (Electronic)9781467354998
DOIs
Publication statusPublished - 2013
Event2013 IEEE Eighth International Conference on Intelligent Sensors, Sensor Networks and Information Processing - University of Melbourne, Melbourne, Australia
Duration: 02 Apr 201305 Apr 2013
https://web.archive.org/web/20130207041834/http://www.issnip.org:80/2013/index.html (Archived page)

Conference

Conference2013 IEEE Eighth International Conference on Intelligent Sensors, Sensor Networks and Information Processing
CountryAustralia
CityMelbourne
Period02/04/1305/04/13
Internet address

Fingerprint

Adaptive filters
Accelerometers
Sensors
Robotic arms

Cite this

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). United States: 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
@inproceedings{0cd79274164f4110b9ec1aceb702e02c,
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).",
year = "2013",
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",
publisher = "IEEE, Institute of Electrical and Electronics Engineers",
address = "United States",

}

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, 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 paperConference paper

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

SP - 66

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

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 https://doi.org/10.1109/ISSNIP.2013.6529766