Imperial College London
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Dr Ad Spiers

Faculty of Engineering, Department of Electrical and Electronic Engineering

Lecturer in Robotics and Machine Learning
 
 
 
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Contact

 

a.spiers

 
 
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Location

 

Electrical EngineeringSouth Kensington Campus

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Summary

 

Publications

Citation

BibTex format

@article{Gloumakov:2020:10.1109/TNSRE.2020.3040522,
author = {Gloumakov, Y and Spiers, AJ and Dollar, AM},
doi = {10.1109/TNSRE.2020.3040522},
journal = {IEEE Transactions on Neural Systems and Rehabilitation Engineering},
pages = {2826--2836},
title = {Dimensionality reduction and motion clustering during activities of daily living: three-, four-, and seven-degree-of-freedom arm movements},
url = {http://dx.doi.org/10.1109/TNSRE.2020.3040522},
volume = {28},
year = {2020}
}
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RIS format (EndNote, RefMan)

TY  - JOUR
AB  - This paper is the first in a two-part series analyzing human arm and hand motion during a wide range of unstructured tasks. The wide variety of motions performed by the human arm during daily tasks makes it desirable to find representative subsets to reduce the dimensionality of these movements for a variety of applications, including the design and control of robotic and prosthetic devices. This paper presents a novel method and the results of an extensive human subjects study to obtain representative arm joint angle trajectories that span naturalistic motions during Activities of Daily Living (ADLs). In particular, we seek to identify sets of useful motion trajectories of the upper limb that are functions of a single variable, allowing, for instance, an entire prosthetic or robotic arm to be controlled with a single input from a user, along with a means to select between motions for different tasks. Data driven approaches are used to discover clusters and representative motion averages for the wrist 3 degree of freedom (DOF), elbow-wrist 4 DOF, and full-arm 7 DOF motions. The proposed method makes use of well-known techniques such as dynamic time warping (DTW) to obtain a divergence measure between motion segments, Ward’s distance criterion to build hierarchical trees, and functional principal component analysis (fPCA) to evaluate cluster variability. The emerging clusters associate various recorded motions into primarily hand start and end location for the full-arm system, motion direction for the wrist-only system, and an intermediate between the two qualities for the elbow-wrist system.
AU  - Gloumakov,Y
AU  - Spiers,AJ
AU  - Dollar,AM
DO  - 10.1109/TNSRE.2020.3040522
EP  - 2836
PY  - 2020///
SN  - 1534-4320
SP  - 2826
TI  - Dimensionality reduction and motion clustering during activities of daily living: three-, four-, and seven-degree-of-freedom arm movements
T2  - IEEE Transactions on Neural Systems and Rehabilitation Engineering
UR  - http://dx.doi.org/10.1109/TNSRE.2020.3040522
UR  - http://gateway.webofknowledge.com/gateway/Gateway.cgi?GWVersion=2&SrcApp=PARTNER_APP&SrcAuth=LinksAMR&KeyUT=WOS:000613615700024&DestLinkType=FullRecord&DestApp=ALL_WOS&UsrCustomerID=1ba7043ffcc86c417c072aa74d649202
UR  - https://ieeexplore.ieee.org/document/9271867
UR  - http://hdl.handle.net/10044/1/86974
VL  - 28
ER  -
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