Identifying Time-Varying Neuromuscular Response

A Recursive Least-Squares Algorithm with Pseudoinverse

Mario Olivari, Frank M. Nieuwenhuizen, Heinrich Bulthoff, Lorenzo Pollini

Research output: Chapter in Book/Report/Conference proceedingConference contribution

2 Citations (Scopus)

Abstract

Effectiveness of hap tic guidance systems depends on how humans adapt their neuromuscular response to the force feedback. A quantitative insight into adaptation of neuromuscular response can be obtained by identifying neuromuscular dynamics. Since humans are likely to vary their neuromuscular response during realistic control scenarios, there is a need for methods that can identify time-varying neuromuscular dynamics. In this work an identification method is developed which estimates the impulse response of time-varying neuromuscular system by using a Recursive Least Squares (RLS) method. The proposed method extends the commonly used RLS-based method by employing the pseudo inverse operator instead of the inverse operator. This results in improved robustness to external noise. The method was validated in a human in-The-loop experiment. The neuromuscular estimates given by the proposed method were more accurate than those obtained with the commonly used RLS-based method.

Original languageEnglish
Title of host publicationProceedings - 2015 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2015
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages3079-3085
Number of pages7
ISBN (Print)9781479986965
DOIs
Publication statusPublished - 2016 Jan 12
EventIEEE International Conference on Systems, Man, and Cybernetics, SMC 2015 - Kowloon Tong, Hong Kong
Duration: 2015 Oct 92015 Oct 12

Other

OtherIEEE International Conference on Systems, Man, and Cybernetics, SMC 2015
CountryHong Kong
CityKowloon Tong
Period15/10/915/10/12

Fingerprint

Impulse response
Feedback
Experiments
Time-varying
Least squares
Operator

Keywords

  • Haptic AIDS
  • neuromuscular system
  • recursive least squares algorithm
  • timevarying identification

ASJC Scopus subject areas

  • Artificial Intelligence
  • Computer Networks and Communications
  • Energy Engineering and Power Technology
  • Information Systems and Management
  • Control and Systems Engineering

Cite this

Olivari, M., Nieuwenhuizen, F. M., Bulthoff, H., & Pollini, L. (2016). Identifying Time-Varying Neuromuscular Response: A Recursive Least-Squares Algorithm with Pseudoinverse. In Proceedings - 2015 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2015 (pp. 3079-3085). [7379667] Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/SMC.2015.535

Identifying Time-Varying Neuromuscular Response : A Recursive Least-Squares Algorithm with Pseudoinverse. / Olivari, Mario; Nieuwenhuizen, Frank M.; Bulthoff, Heinrich; Pollini, Lorenzo.

Proceedings - 2015 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2015. Institute of Electrical and Electronics Engineers Inc., 2016. p. 3079-3085 7379667.

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Olivari, M, Nieuwenhuizen, FM, Bulthoff, H & Pollini, L 2016, Identifying Time-Varying Neuromuscular Response: A Recursive Least-Squares Algorithm with Pseudoinverse. in Proceedings - 2015 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2015., 7379667, Institute of Electrical and Electronics Engineers Inc., pp. 3079-3085, IEEE International Conference on Systems, Man, and Cybernetics, SMC 2015, Kowloon Tong, Hong Kong, 15/10/9. https://doi.org/10.1109/SMC.2015.535
Olivari M, Nieuwenhuizen FM, Bulthoff H, Pollini L. Identifying Time-Varying Neuromuscular Response: A Recursive Least-Squares Algorithm with Pseudoinverse. In Proceedings - 2015 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2015. Institute of Electrical and Electronics Engineers Inc. 2016. p. 3079-3085. 7379667 https://doi.org/10.1109/SMC.2015.535
Olivari, Mario ; Nieuwenhuizen, Frank M. ; Bulthoff, Heinrich ; Pollini, Lorenzo. / Identifying Time-Varying Neuromuscular Response : A Recursive Least-Squares Algorithm with Pseudoinverse. Proceedings - 2015 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2015. Institute of Electrical and Electronics Engineers Inc., 2016. pp. 3079-3085
@inproceedings{55804a12476a41af87652f5c07971d2c,
title = "Identifying Time-Varying Neuromuscular Response: A Recursive Least-Squares Algorithm with Pseudoinverse",
abstract = "Effectiveness of hap tic guidance systems depends on how humans adapt their neuromuscular response to the force feedback. A quantitative insight into adaptation of neuromuscular response can be obtained by identifying neuromuscular dynamics. Since humans are likely to vary their neuromuscular response during realistic control scenarios, there is a need for methods that can identify time-varying neuromuscular dynamics. In this work an identification method is developed which estimates the impulse response of time-varying neuromuscular system by using a Recursive Least Squares (RLS) method. The proposed method extends the commonly used RLS-based method by employing the pseudo inverse operator instead of the inverse operator. This results in improved robustness to external noise. The method was validated in a human in-The-loop experiment. The neuromuscular estimates given by the proposed method were more accurate than those obtained with the commonly used RLS-based method.",
keywords = "Haptic AIDS, neuromuscular system, recursive least squares algorithm, timevarying identification",
author = "Mario Olivari and Nieuwenhuizen, {Frank M.} and Heinrich Bulthoff and Lorenzo Pollini",
year = "2016",
month = "1",
day = "12",
doi = "10.1109/SMC.2015.535",
language = "English",
isbn = "9781479986965",
pages = "3079--3085",
booktitle = "Proceedings - 2015 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2015",
publisher = "Institute of Electrical and Electronics Engineers Inc.",

}

TY - GEN

T1 - Identifying Time-Varying Neuromuscular Response

T2 - A Recursive Least-Squares Algorithm with Pseudoinverse

AU - Olivari, Mario

AU - Nieuwenhuizen, Frank M.

AU - Bulthoff, Heinrich

AU - Pollini, Lorenzo

PY - 2016/1/12

Y1 - 2016/1/12

N2 - Effectiveness of hap tic guidance systems depends on how humans adapt their neuromuscular response to the force feedback. A quantitative insight into adaptation of neuromuscular response can be obtained by identifying neuromuscular dynamics. Since humans are likely to vary their neuromuscular response during realistic control scenarios, there is a need for methods that can identify time-varying neuromuscular dynamics. In this work an identification method is developed which estimates the impulse response of time-varying neuromuscular system by using a Recursive Least Squares (RLS) method. The proposed method extends the commonly used RLS-based method by employing the pseudo inverse operator instead of the inverse operator. This results in improved robustness to external noise. The method was validated in a human in-The-loop experiment. The neuromuscular estimates given by the proposed method were more accurate than those obtained with the commonly used RLS-based method.

AB - Effectiveness of hap tic guidance systems depends on how humans adapt their neuromuscular response to the force feedback. A quantitative insight into adaptation of neuromuscular response can be obtained by identifying neuromuscular dynamics. Since humans are likely to vary their neuromuscular response during realistic control scenarios, there is a need for methods that can identify time-varying neuromuscular dynamics. In this work an identification method is developed which estimates the impulse response of time-varying neuromuscular system by using a Recursive Least Squares (RLS) method. The proposed method extends the commonly used RLS-based method by employing the pseudo inverse operator instead of the inverse operator. This results in improved robustness to external noise. The method was validated in a human in-The-loop experiment. The neuromuscular estimates given by the proposed method were more accurate than those obtained with the commonly used RLS-based method.

KW - Haptic AIDS

KW - neuromuscular system

KW - recursive least squares algorithm

KW - timevarying identification

UR - http://www.scopus.com/inward/record.url?scp=84964467107&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=84964467107&partnerID=8YFLogxK

U2 - 10.1109/SMC.2015.535

DO - 10.1109/SMC.2015.535

M3 - Conference contribution

SN - 9781479986965

SP - 3079

EP - 3085

BT - Proceedings - 2015 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2015

PB - Institute of Electrical and Electronics Engineers Inc.

ER -