TY - GEN
T1 - Cancelling biodynamic feedthrough requires a subject and task dependent approach
AU - Venrooij, Joost
AU - Mulder, Mark
AU - Van Paassen, Marinus M.
AU - Abbink, David A.
AU - Bülthoff, Heinrich H.
AU - Mulder, Max
PY - 2011
Y1 - 2011
N2 - Vehicle accelerations may feed through the human body, causing involuntary limb motions which may lead to involuntary control inputs. This phenomenon is called biodynamic feedthrough (BDFT). Signal cancellation is a possible way of mitigating biodynamic feedthrough. It makes use of a BDFT model to estimate the involuntary control inputs. The BDFT effects are removed by subtracting the modeled estimate of the involuntary control input from the total control signal, containing both voluntary and involuntary components. The success of signal cancellation hinges on the accuracy of the BDFT model used. In this study the potential of signal cancellation is studied by making use of a method called optimal signal cancellation. Here, an identified BDFT model is used off-line to generate an estimate of the involuntary control inputs based on the accelerations present. Results show that reliable signal cancellation requires BDFT models that are both subject and task dependent. The task dependency is of particular importance: failing to adapt the model to changes in the operator's neuromuscular dynamics dramatically decreases the quality of cancellation and can even lead to an increase in unwanted effects. As a reliable and fast on-line identification method of the neuromuscular dynamics of the human operator currently does not exist, real-time signal cancellation is currently not feasible.
AB - Vehicle accelerations may feed through the human body, causing involuntary limb motions which may lead to involuntary control inputs. This phenomenon is called biodynamic feedthrough (BDFT). Signal cancellation is a possible way of mitigating biodynamic feedthrough. It makes use of a BDFT model to estimate the involuntary control inputs. The BDFT effects are removed by subtracting the modeled estimate of the involuntary control input from the total control signal, containing both voluntary and involuntary components. The success of signal cancellation hinges on the accuracy of the BDFT model used. In this study the potential of signal cancellation is studied by making use of a method called optimal signal cancellation. Here, an identified BDFT model is used off-line to generate an estimate of the involuntary control inputs based on the accelerations present. Results show that reliable signal cancellation requires BDFT models that are both subject and task dependent. The task dependency is of particular importance: failing to adapt the model to changes in the operator's neuromuscular dynamics dramatically decreases the quality of cancellation and can even lead to an increase in unwanted effects. As a reliable and fast on-line identification method of the neuromuscular dynamics of the human operator currently does not exist, real-time signal cancellation is currently not feasible.
KW - Biodynamic feedthrough
KW - model-based cancellation
KW - signal cancellation
UR - http://www.scopus.com/inward/record.url?scp=83755177827&partnerID=8YFLogxK
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U2 - 10.1109/ICSMC.2011.6083911
DO - 10.1109/ICSMC.2011.6083911
M3 - Conference contribution
AN - SCOPUS:83755177827
SN - 9781457706523
T3 - Conference Proceedings - IEEE International Conference on Systems, Man and Cybernetics
SP - 1670
EP - 1675
BT - 2011 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2011 - Conference Digest
T2 - 2011 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2011
Y2 - 9 October 2011 through 12 October 2011
ER -