Identifying Time-Varying Neuromuscular Response: A Recursive Least-Squares Algorithm with Pseudoinverse

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

doi:10.1109/SMC.2015.535

Identifying Time-Varying Neuromuscular Response: A Recursive Least-Squares Algorithm with Pseudoinverse

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

Department of Brain and Cognitive Engineering

Research output: Chapter in Book/Report/Conference proceeding › Conference 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 language	English
Title of host publication	Proceedings - 2015 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2015
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	3079-3085
Number of pages	7
ISBN (Print)	9781479986965
DOIs	https://doi.org/10.1109/SMC.2015.535
Publication status	Published - 2016 Jan 12
Event	IEEE International Conference on Systems, Man, and Cybernetics, SMC 2015 - Kowloon Tong, Hong Kong Duration: 2015 Oct 9 → 2015 Oct 12

Other

Other	IEEE International Conference on Systems, Man, and Cybernetics, SMC 2015
Country/Territory	Hong Kong
City	Kowloon Tong
Period	15/10/9 → 15/10/12

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

UN SDGs

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

Access to Document

10.1109/SMC.2015.535

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 et al.
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 proceeding › Conference 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

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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.

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Identifying Time-Varying Neuromuscular Response: A Recursive Least-Squares Algorithm with Pseudoinverse

Abstract

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Keywords

ASJC Scopus subject areas

UN SDGs

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