Haptic human-human interaction: motor learning & haptic communication

Niek Beckers

    Research output: ThesisPhD Thesis - Research UT, graduation UT

    38 Downloads (Pure)

    Abstract

    Haptic interaction with a partner – interaction by exerting forces onto each other directly or through an object – plays an important role in our lives. It can help us to coordinate our actions and it can benefit learning of new motor tasks; for example, a therapist can physically support a patient during recovery of their motor functions after injury or disease. My research goal is to create a better understanding of whether haptic interaction between two humans improves individual motor learning and why haptic interaction would improve motor performance.

    We performed two experiments in which two partners learned novel motor tasks together: tracking a randomly-moving target in two novel environments. We haptically-connected the partners while they simultaneously learned a motor task. The partners were not made aware of the coupling. Although haptic interaction improved performance of both partners during interaction, this improvement was not retained when performing the task alone in both experiments. Hence, haptic interaction between humans does not improve individual motor learning in a collaborative motor task.

    Interestingly, we found that haptic interaction improved motor performance during interaction, even when being coupled to a worse-performing partner. To explain this result, we developed a computational model of the interaction in which we mechanically coupled two simulated partners who both independently performed the same motor task. The model assumed that the partners were unaware of the haptic connection. Hence, the simulated partners were only mechanically influenced by the interaction force; they did not exchange any information about each other or the task through the interaction force to improve their performance. This model accurately predicted the improvement due to interaction observed in the experimental data. Additional model analysis suggested that haptic interaction improved performance because the compliant connection partially compensated for each partner's motor output variability, which includes tracking errors such as overshoots. The worse-performing partners additionally benefited from the haptic guidance provided by their better-performing partners. Similarly, we observed that partners did not coordinate reaching movements through the interaction force in another experiment.

    In conclusion, our findings suggest that haptically-coupling two humans does not necessarily result in any exchange of information or motor coordination through the interaction force.
    Original languageEnglish
    QualificationDoctor of Philosophy
    Awarding Institution
    • University of Twente
    Supervisors/Advisors
    • van der Kooij, Herman , Supervisor
    • van Asseldonk, Edwin H.F., Co-Supervisor
    Award date12 Jul 2019
    Place of PublicationEnschede
    Publisher
    Print ISBNs978-90-365-4807-6
    DOIs
    Publication statusPublished - 12 Jul 2019

    Fingerprint

    Communication
    Experiments
    Recovery

    Cite this

    Beckers, Niek. / Haptic human-human interaction : motor learning & haptic communication. Enschede : University of Twente, 2019. 211 p.
    @phdthesis{581f2c09f929407aad0b5cc0eca5200c,
    title = "Haptic human-human interaction: motor learning & haptic communication",
    abstract = "Haptic interaction with a partner – interaction by exerting forces onto each other directly or through an object – plays an important role in our lives. It can help us to coordinate our actions and it can benefit learning of new motor tasks; for example, a therapist can physically support a patient during recovery of their motor functions after injury or disease. My research goal is to create a better understanding of whether haptic interaction between two humans improves individual motor learning and why haptic interaction would improve motor performance.We performed two experiments in which two partners learned novel motor tasks together: tracking a randomly-moving target in two novel environments. We haptically-connected the partners while they simultaneously learned a motor task. The partners were not made aware of the coupling. Although haptic interaction improved performance of both partners during interaction, this improvement was not retained when performing the task alone in both experiments. Hence, haptic interaction between humans does not improve individual motor learning in a collaborative motor task.Interestingly, we found that haptic interaction improved motor performance during interaction, even when being coupled to a worse-performing partner. To explain this result, we developed a computational model of the interaction in which we mechanically coupled two simulated partners who both independently performed the same motor task. The model assumed that the partners were unaware of the haptic connection. Hence, the simulated partners were only mechanically influenced by the interaction force; they did not exchange any information about each other or the task through the interaction force to improve their performance. This model accurately predicted the improvement due to interaction observed in the experimental data. Additional model analysis suggested that haptic interaction improved performance because the compliant connection partially compensated for each partner's motor output variability, which includes tracking errors such as overshoots. The worse-performing partners additionally benefited from the haptic guidance provided by their better-performing partners. Similarly, we observed that partners did not coordinate reaching movements through the interaction force in another experiment. In conclusion, our findings suggest that haptically-coupling two humans does not necessarily result in any exchange of information or motor coordination through the interaction force.",
    author = "Niek Beckers",
    year = "2019",
    month = "7",
    day = "12",
    doi = "10.3990/1.9789036548076",
    language = "English",
    isbn = "978-90-365-4807-6",
    publisher = "University of Twente",
    address = "Netherlands",
    school = "University of Twente",

    }

    Beckers, N 2019, 'Haptic human-human interaction: motor learning & haptic communication', Doctor of Philosophy, University of Twente, Enschede. https://doi.org/10.3990/1.9789036548076

    Haptic human-human interaction : motor learning & haptic communication. / Beckers, Niek.

    Enschede : University of Twente, 2019. 211 p.

    Research output: ThesisPhD Thesis - Research UT, graduation UT

    TY - THES

    T1 - Haptic human-human interaction

    T2 - motor learning & haptic communication

    AU - Beckers, Niek

    PY - 2019/7/12

    Y1 - 2019/7/12

    N2 - Haptic interaction with a partner – interaction by exerting forces onto each other directly or through an object – plays an important role in our lives. It can help us to coordinate our actions and it can benefit learning of new motor tasks; for example, a therapist can physically support a patient during recovery of their motor functions after injury or disease. My research goal is to create a better understanding of whether haptic interaction between two humans improves individual motor learning and why haptic interaction would improve motor performance.We performed two experiments in which two partners learned novel motor tasks together: tracking a randomly-moving target in two novel environments. We haptically-connected the partners while they simultaneously learned a motor task. The partners were not made aware of the coupling. Although haptic interaction improved performance of both partners during interaction, this improvement was not retained when performing the task alone in both experiments. Hence, haptic interaction between humans does not improve individual motor learning in a collaborative motor task.Interestingly, we found that haptic interaction improved motor performance during interaction, even when being coupled to a worse-performing partner. To explain this result, we developed a computational model of the interaction in which we mechanically coupled two simulated partners who both independently performed the same motor task. The model assumed that the partners were unaware of the haptic connection. Hence, the simulated partners were only mechanically influenced by the interaction force; they did not exchange any information about each other or the task through the interaction force to improve their performance. This model accurately predicted the improvement due to interaction observed in the experimental data. Additional model analysis suggested that haptic interaction improved performance because the compliant connection partially compensated for each partner's motor output variability, which includes tracking errors such as overshoots. The worse-performing partners additionally benefited from the haptic guidance provided by their better-performing partners. Similarly, we observed that partners did not coordinate reaching movements through the interaction force in another experiment. In conclusion, our findings suggest that haptically-coupling two humans does not necessarily result in any exchange of information or motor coordination through the interaction force.

    AB - Haptic interaction with a partner – interaction by exerting forces onto each other directly or through an object – plays an important role in our lives. It can help us to coordinate our actions and it can benefit learning of new motor tasks; for example, a therapist can physically support a patient during recovery of their motor functions after injury or disease. My research goal is to create a better understanding of whether haptic interaction between two humans improves individual motor learning and why haptic interaction would improve motor performance.We performed two experiments in which two partners learned novel motor tasks together: tracking a randomly-moving target in two novel environments. We haptically-connected the partners while they simultaneously learned a motor task. The partners were not made aware of the coupling. Although haptic interaction improved performance of both partners during interaction, this improvement was not retained when performing the task alone in both experiments. Hence, haptic interaction between humans does not improve individual motor learning in a collaborative motor task.Interestingly, we found that haptic interaction improved motor performance during interaction, even when being coupled to a worse-performing partner. To explain this result, we developed a computational model of the interaction in which we mechanically coupled two simulated partners who both independently performed the same motor task. The model assumed that the partners were unaware of the haptic connection. Hence, the simulated partners were only mechanically influenced by the interaction force; they did not exchange any information about each other or the task through the interaction force to improve their performance. This model accurately predicted the improvement due to interaction observed in the experimental data. Additional model analysis suggested that haptic interaction improved performance because the compliant connection partially compensated for each partner's motor output variability, which includes tracking errors such as overshoots. The worse-performing partners additionally benefited from the haptic guidance provided by their better-performing partners. Similarly, we observed that partners did not coordinate reaching movements through the interaction force in another experiment. In conclusion, our findings suggest that haptically-coupling two humans does not necessarily result in any exchange of information or motor coordination through the interaction force.

    U2 - 10.3990/1.9789036548076

    DO - 10.3990/1.9789036548076

    M3 - PhD Thesis - Research UT, graduation UT

    SN - 978-90-365-4807-6

    PB - University of Twente

    CY - Enschede

    ER -