Identifying time-varying neuromuscular response

Experimental evaluation of a RLS-based algorithm

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

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

6 Citations (Scopus)

Abstract

Methods for identifying neuromuscular response commonly assume time-invariant neuromuscular dynamics. However, neuromuscular dynamics are likely to change during realistic control scenarios. In a previous paper we presented a method for identifying time- varying neuromuscular dynamics based on a Recursive Least Squares (RLS) algorithm. To date, this method has only been validated in a Monte Carlo simulation study. This paper presents an experimental validation of the same method. In the experiment, three different disturbance-rejection tasks were performed: a position task with the human instructed to minimize the stick deection in front of an external force disturbance, a relax task with the instruction to relax the arm, and a time-varying task with the instruction to alternate between position and relax tasks. The position and relax tasks induce different time-invariant neuromuscular dynamics, whereas the time-varying task induces time-varying neuromuscular dynamics. The RLS-based method was used to estimate neuromuscular dynamics in the three tasks. The neuromuscular estimates were reliable both in time-invariant and time-varying tasks. These findings indicate that the RLS-based method can be used to estimate time-varying neuromuscular responses in human-in-the loop experiments.

Original languageEnglish
Title of host publicationAIAA Modeling and Simulation Technologies Conference, 2015
PublisherAmerican Institute of Aeronautics and Astronautics Inc.
ISBN (Electronic)9781624103438
Publication statusPublished - 2015
EventAIAA Modeling and Simulation Technologies Conference 2015 - Kissimmee, United States
Duration: 2015 Jan 52015 Jan 9

Other

OtherAIAA Modeling and Simulation Technologies Conference 2015
CountryUnited States
CityKissimmee
Period15/1/515/1/9

Fingerprint

Experimental Evaluation
Least Squares
Time-varying
Invariant
Estimate
Disturbance Rejection
Disturbance rejection
Least Square Algorithm
Experimental Validation
Recursive Algorithm
Alternate
Experiment
Monte Carlo Simulation
Disturbance
Experiments
Likely
Simulation Study
Minimise
Scenarios

ASJC Scopus subject areas

  • Aerospace Engineering
  • Modelling and Simulation

Cite this

Olivari, M., Nieuwenhuizen, F. M., Bulthoff, H., & Pollini, L. (2015). Identifying time-varying neuromuscular response: Experimental evaluation of a RLS-based algorithm. In AIAA Modeling and Simulation Technologies Conference, 2015 American Institute of Aeronautics and Astronautics Inc..

Identifying time-varying neuromuscular response : Experimental evaluation of a RLS-based algorithm. / Olivari, Mario; Nieuwenhuizen, Frank M.; Bulthoff, Heinrich; Pollini, Lorenzo.

AIAA Modeling and Simulation Technologies Conference, 2015. American Institute of Aeronautics and Astronautics Inc., 2015.

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

Olivari, M, Nieuwenhuizen, FM, Bulthoff, H & Pollini, L 2015, Identifying time-varying neuromuscular response: Experimental evaluation of a RLS-based algorithm. in AIAA Modeling and Simulation Technologies Conference, 2015. American Institute of Aeronautics and Astronautics Inc., AIAA Modeling and Simulation Technologies Conference 2015, Kissimmee, United States, 15/1/5.
Olivari M, Nieuwenhuizen FM, Bulthoff H, Pollini L. Identifying time-varying neuromuscular response: Experimental evaluation of a RLS-based algorithm. In AIAA Modeling and Simulation Technologies Conference, 2015. American Institute of Aeronautics and Astronautics Inc. 2015
Olivari, Mario ; Nieuwenhuizen, Frank M. ; Bulthoff, Heinrich ; Pollini, Lorenzo. / Identifying time-varying neuromuscular response : Experimental evaluation of a RLS-based algorithm. AIAA Modeling and Simulation Technologies Conference, 2015. American Institute of Aeronautics and Astronautics Inc., 2015.
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