Abstract
During human walking, there exists a functional neural coupling between arms and legs, and between cervical and lumbosacral pattern generators. Here, we present a novel approach for associating the electromyographic (EMG) activity from upper limb muscles with leg kinematics. Our methodology takes advantage of the high involvement of shoulder muscles in most locomotor-related movements and of the natural co-ordination between arms and legs. Nine healthy subjects were asked to walk at different constant and variable speeds (3–5 km/h), while EMG activity of shoulder (deltoid) muscles and the kinematics of walking were recorded. To ensure a high level of EMG activity in deltoid, the subjects performed slightly larger arm swinging than they usually do. The temporal structure of the burst-like EMG activity was used to predict the spatiotemporal kinematic pattern of the forthcoming step. A comparison of actual and predicted stride leg kinematics showed a high degree of correspondence (r >0.9). This algorithm has been also implemented in pilot experiments for controlling avatar walking in a virtual reality setup and an exoskeleton during over-ground stepping. The proposed approach may have important implications for the design of human–machine interfaces and neuroprosthetic technologies such as those of assistive lower limb exoskeletons.
| Original language | English |
|---|---|
| Article number | 838 |
| Journal | Frontiers in Human Neuroscience |
| Volume | 8 |
| Issue number | OCT |
| DOIs | |
| Publication status | Published - Oct 20 2014 |
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Keywords
- Arm–leg co-ordination
- EMG patterns
- Gait kinematics
- Neuroprosthetic technology
- Quadrupedal locomotion
ASJC Scopus subject areas
- Psychiatry and Mental health
- Neurology
- Biological Psychiatry
- Behavioral Neuroscience
- Neuropsychology and Physiological Psychology
Cite this
Control of leg movements driven by EMG activity of shoulder muscles. / La Scaleia, Valentina; Sylos-Labini, Francesca; Hoellinger, Thomas; Wang, Letian; Cheron, Guy; Lacquaniti, Francesco; Ivanenko, Yuri P.
In: Frontiers in Human Neuroscience, Vol. 8, No. OCT, 838, 20.10.2014.Research output: Contribution to journal › Article
}
TY - JOUR
T1 - Control of leg movements driven by EMG activity of shoulder muscles
AU - La Scaleia, Valentina
AU - Sylos-Labini, Francesca
AU - Hoellinger, Thomas
AU - Wang, Letian
AU - Cheron, Guy
AU - Lacquaniti, Francesco
AU - Ivanenko, Yuri P.
PY - 2014/10/20
Y1 - 2014/10/20
N2 - During human walking, there exists a functional neural coupling between arms and legs, and between cervical and lumbosacral pattern generators. Here, we present a novel approach for associating the electromyographic (EMG) activity from upper limb muscles with leg kinematics. Our methodology takes advantage of the high involvement of shoulder muscles in most locomotor-related movements and of the natural co-ordination between arms and legs. Nine healthy subjects were asked to walk at different constant and variable speeds (3–5 km/h), while EMG activity of shoulder (deltoid) muscles and the kinematics of walking were recorded. To ensure a high level of EMG activity in deltoid, the subjects performed slightly larger arm swinging than they usually do. The temporal structure of the burst-like EMG activity was used to predict the spatiotemporal kinematic pattern of the forthcoming step. A comparison of actual and predicted stride leg kinematics showed a high degree of correspondence (r >0.9). This algorithm has been also implemented in pilot experiments for controlling avatar walking in a virtual reality setup and an exoskeleton during over-ground stepping. The proposed approach may have important implications for the design of human–machine interfaces and neuroprosthetic technologies such as those of assistive lower limb exoskeletons.
AB - During human walking, there exists a functional neural coupling between arms and legs, and between cervical and lumbosacral pattern generators. Here, we present a novel approach for associating the electromyographic (EMG) activity from upper limb muscles with leg kinematics. Our methodology takes advantage of the high involvement of shoulder muscles in most locomotor-related movements and of the natural co-ordination between arms and legs. Nine healthy subjects were asked to walk at different constant and variable speeds (3–5 km/h), while EMG activity of shoulder (deltoid) muscles and the kinematics of walking were recorded. To ensure a high level of EMG activity in deltoid, the subjects performed slightly larger arm swinging than they usually do. The temporal structure of the burst-like EMG activity was used to predict the spatiotemporal kinematic pattern of the forthcoming step. A comparison of actual and predicted stride leg kinematics showed a high degree of correspondence (r >0.9). This algorithm has been also implemented in pilot experiments for controlling avatar walking in a virtual reality setup and an exoskeleton during over-ground stepping. The proposed approach may have important implications for the design of human–machine interfaces and neuroprosthetic technologies such as those of assistive lower limb exoskeletons.
KW - Arm–leg co-ordination
KW - EMG patterns
KW - Gait kinematics
KW - Neuroprosthetic technology
KW - Quadrupedal locomotion
UR - http://www.scopus.com/inward/record.url?scp=84933677726&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84933677726&partnerID=8YFLogxK
U2 - 10.3389/fnhum.2014.00838
DO - 10.3389/fnhum.2014.00838
M3 - Article
AN - SCOPUS:84933677726
VL - 8
JO - Frontiers in Human Neuroscience
JF - Frontiers in Human Neuroscience
SN - 1662-5161
IS - OCT
M1 - 838
ER -