2023
Journal Articles
Ivanova, Ekaterina; Peña-Pérez, Nuria; Eden, Jonathan; Yip, Yammi; Burdet, Etienne
Dissociating haptic feedback from physical assistance does not improve motor performance Journal Article
In: Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference, vol. 2023, pp. 1–5, 2023, ISSN: 2694-0604.
Abstract | Links | BibTeX | Tags: Feedback, Haptic Technology, Humans, Learning, Sensory, Sports
@article{ivanova_dissociating_2023,
title = {Dissociating haptic feedback from physical assistance does not improve motor performance},
author = { Ekaterina Ivanova and Nuria Peña-Pérez and Jonathan Eden and Yammi Yip and Etienne Burdet},
doi = {10.1109/EMBC40787.2023.10340983},
issn = {2694-0604},
year = {2023},
date = {2023-07-01},
journal = {Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference},
volume = {2023},
pages = {1–5},
abstract = {In robots for motor rehabilitation and sports training, haptic assistance typically provides both mechanical guidance and task-relevant information. With the natural human tendency to minimise metabolic cost, mechanical guidance may however prevent efficient short term learning and retention. In this work, we explore the effect of providing haptic feedback to the not active hand during a tracking task. We test four types of haptic feedback: task- or error-related information, no information and irrelevant information. The results show that feedback provided to the hand not carrying out the tracking task did not improve task performance. However, irrelevant information to the task worsened performance, and negatively influenced the participants' perception of helpfulness, assistance, likability and predictability.},
keywords = {Feedback, Haptic Technology, Humans, Learning, Sensory, Sports},
pubstate = {published},
tppubtype = {article}
}
Jiang, Ziyi; Huang, Yanpei; Eden, Jonathan; Ivanova, Ekaterina; Cheng, Xiaoxiao; Burdet, Etienne
A virtual reality platform to evaluate the effects of supernumerary limbs' appearance Journal Article
In: Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference, vol. 2023, pp. 1–5, 2023, ISSN: 2694-0604.
Abstract | Links | BibTeX | Tags: Extremities, Humans, Pilot Projects, Robotics, Virtual reality
@article{jiang_virtual_2023,
title = {A virtual reality platform to evaluate the effects of supernumerary limbs' appearance},
author = { Ziyi Jiang and Yanpei Huang and Jonathan Eden and Ekaterina Ivanova and Xiaoxiao Cheng and Etienne Burdet},
doi = {10.1109/EMBC40787.2023.10340197},
issn = {2694-0604},
year = {2023},
date = {2023-07-01},
journal = {Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference},
volume = {2023},
pages = {1–5},
abstract = {Supernumerary robot limbs (SL) can expand the ability of users by increasing the number of degrees of freedom that they control. While several SLs have been designed and tested on human participants, the effect of the limb's appearance on the user's acceptance, embodiment and device usage is not yet understood. We developed a virtual reality platform with a three-arm avatar that enabled us to systematically investigate the effect of the supernumerary limb's appearance on their perception and motion control performance. A pilot study with 14 participants exhibited similar performance, workload and preference in human-like or robot-like appearance with a trend of preference for the robotic appearance.},
keywords = {Extremities, Humans, Pilot Projects, Robotics, Virtual reality},
pubstate = {published},
tppubtype = {article}
}
Ofner, Patrick; Lee, Meng-Jung; Farina, Dario; Mehring, Carsten
Mental Tasks Modulate Motor-Units Above 10 Hz and are a Potential Control Signal for Movement Augmentation: a Preliminary Study Journal Article
In: Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference, vol. 2023, pp. 1–4, 2023, ISSN: 2694-0604.
Abstract | Links | BibTeX | Tags: Electromyography, Foot, Humans, Motor Neurons, Movement, Muscle, Skeletal
@article{ofner_mental_2023,
title = {Mental Tasks Modulate Motor-Units Above 10 Hz and are a Potential Control Signal for Movement Augmentation: a Preliminary Study},
author = { Patrick Ofner and Meng-Jung Lee and Dario Farina and Carsten Mehring},
doi = {10.1109/EMBC40787.2023.10340378},
issn = {2694-0604},
year = {2023},
date = {2023-07-01},
journal = {Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference},
volume = {2023},
pages = {1–4},
abstract = {Spinal motor neurons receive a wide range of input frequencies. However, only frequencies below ca. 10 Hz are directly translated into motor output. Frequency components above 10 Hz are filtered out by neural pathways and muscle dynamics. These higher frequency components may have an indirect effect on motor output, or may simply represent movement-independent oscillations that leak down from supraspinal areas such as the motor cortex. If movement-independent oscillations leak down from supraspinal areas, they could provide a potential control signal in movement augmentation applications. We analysed high-density electromyography (HD-EMG) signals from the tibialis anterior muscle while human subjects performed various mental tasks. The subjects performed an isometric dorsiflexion of the right foot at a low level of force while simultaneously (1) imagining a movement of the right foot, (2) imagining a movement of both hands, (3) performing a mathematical task, or (4) performing no additional task. We classified the channel-averaged HD-EMG signals and the cumulative spike train (CST) of motor-units using a filter bank and a linear classifier. We found that in some subjects, the mental task can be classified from the channel-averaged HD-EMG signals and the CST in oscillations above 10 Hz. Furthermore, we found that these oscillation modulations are incompatible with a systematic and task-dependent change in force level. Our preliminary findings from a limited number of subjects suggest that some mental task-induced oscillations from supraspinal areas leak down to spinal motor neurons and are discriminable via EMG or CST signals at the innervated muscle.},
keywords = {Electromyography, Foot, Humans, Motor Neurons, Movement, Muscle, Skeletal},
pubstate = {published},
tppubtype = {article}
}