POF Sensing Grid:: Signal Analysis to extract Human Motion Characteristics

Patricia Scully; Omar Costilla Reyes; Nabeel Ahmed; John Vaughan; Emma Stanmore; Krikor Ozanyan

POF Sensing Grid: Signal Analysis to extract Human Motion Characteristics

Patricia Scully, Omar Costilla Reyes, Nabeel Ahmed, John Vaughan, Emma Stanmore, Krikor Ozanyan

Nursing & Midwifery

University of Manchester (UOM)

Research output: Contribution to conference › Paper › peer-review

Abstract

Low cost standard polymer optical fibre (POF) is incorporated into a standard carpet or rubber mat, enabling unobtrusive collection of longitudinal data from individuals walking or exercising on the mat. We present several data analysis methods applied to distributed sensor mats using POF grids for measuring human motion, including detection of position, locus and motion of a person at any position, using tomographic imaging, and for measuring the balance and changes in centre of mass of a person who is stationary on the mat using analogue null balance methods, and pattern recognition and machine learning classification, to identify different types of walking.

Original language	English
Number of pages	4
Publication status	Published - Sept 2016
Event	25th International Conference on Plastic Optical Fibres - Aston University, Birmingham, United Kingdom Duration: 13 Sept 2016 → 15 Sept 2016 http://www.pof2016.uk

Conference

Conference	25th International Conference on Plastic Optical Fibres
Abbreviated title	POF2016
Country/Territory	United Kingdom
City	Birmingham
Period	13/09/16 → 15/09/16
Internet address	http://www.pof2016.uk

Technology Transfer Healthcare-Rehabilitation Mat
Scully, P. (Collaborator), Stanmore, E. (Collaborator) & Ozanyan, K. (Collaborator)
Impact: Technological, Health and wellbeing, Society and culture

Cite this

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title = "POF Sensing Grid:: Signal Analysis to extract Human Motion Characteristics",

abstract = "Low cost standard polymer optical fibre (POF) is incorporated into a standard carpet or rubber mat, enabling unobtrusive collection of longitudinal data from individuals walking or exercising on the mat. We present several data analysis methods applied to distributed sensor mats using POF grids for measuring human motion, including detection of position, locus and motion of a person at any position, using tomographic imaging, and for measuring the balance and changes in centre of mass of a person who is stationary on the mat using analogue null balance methods, and pattern recognition and machine learning classification, to identify different types of walking.",

author = "Patricia Scully and {Costilla Reyes}, Omar and Nabeel Ahmed and John Vaughan and Emma Stanmore and Krikor Ozanyan",

year = "2016",

month = sep,

language = "English",

note = "25th International Conference on Plastic Optical Fibres , POF2016 ; Conference date: 13-09-2016 Through 15-09-2016",

url = "http://www.pof2016.uk",

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TY - CONF

T1 - POF Sensing Grid:

T2 - 25th International Conference on Plastic Optical Fibres

AU - Scully, Patricia

AU - Costilla Reyes, Omar

AU - Ahmed, Nabeel

AU - Vaughan, John

AU - Stanmore, Emma

AU - Ozanyan, Krikor

PY - 2016/9

Y1 - 2016/9

N2 - Low cost standard polymer optical fibre (POF) is incorporated into a standard carpet or rubber mat, enabling unobtrusive collection of longitudinal data from individuals walking or exercising on the mat. We present several data analysis methods applied to distributed sensor mats using POF grids for measuring human motion, including detection of position, locus and motion of a person at any position, using tomographic imaging, and for measuring the balance and changes in centre of mass of a person who is stationary on the mat using analogue null balance methods, and pattern recognition and machine learning classification, to identify different types of walking.

AB - Low cost standard polymer optical fibre (POF) is incorporated into a standard carpet or rubber mat, enabling unobtrusive collection of longitudinal data from individuals walking or exercising on the mat. We present several data analysis methods applied to distributed sensor mats using POF grids for measuring human motion, including detection of position, locus and motion of a person at any position, using tomographic imaging, and for measuring the balance and changes in centre of mass of a person who is stationary on the mat using analogue null balance methods, and pattern recognition and machine learning classification, to identify different types of walking.

M3 - Paper

Y2 - 13 September 2016 through 15 September 2016

ER -

POF Sensing Grid: Signal Analysis to extract Human Motion Characteristics

Abstract

Conference

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Impacts

Technology Transfer Healthcare-Rehabilitation Mat

Cite this