2010 ANNUAL INTERNATIONAL CONFERENCE OF THE IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY (EMBC)

Gearóid Ó Laighin

2010 ANNUAL INTERNATIONAL CONFERENCE OF THE IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY (EMBC)

Gearóid Ó Laighin

Electrical & Electronic Engineering

Research output: Chapter in Book or Conference Publication/Proceeding › Conference Publication › peer-review

Abstract

This study aims to evaluate a variety of existing and novel fall detection algorithms, for a waist mounted accelerometer based system. Algorithms were tested against a comprehensive data-set recorded from 10 young healthy subjects performing 240 falls and 120 activities of daily living and 10 elderly healthy subjects performing 240 scripted and 52.4 hours of continuous unscripted normal activities.Results show that using a simple algorithm employing Velocity+Impact+Posture can achieve a low false-positive rate of less than 1 FP day* (0.94FPs day*) with a sensitivity of 94.6% and a specificity of 100%.The algorithms were tested using unsupervised continuous activities performed by elderly subjects living in the community, which is the target environment for a fall detection device.

Original language	English (Ireland)
Title of host publication	Assessment of Waist-worn Tri-axial Accelerometer Based Fall-detection Algorithms using Continuous Unsupervised Activities
Number of pages	4
Publication status	Published - 1 Oct 2010

Cite this

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title = "2010 ANNUAL INTERNATIONAL CONFERENCE OF THE IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY (EMBC)",

abstract = "This study aims to evaluate a variety of existing and novel fall detection algorithms, for a waist mounted accelerometer based system. Algorithms were tested against a comprehensive data-set recorded from 10 young healthy subjects performing 240 falls and 120 activities of daily living and 10 elderly healthy subjects performing 240 scripted and 52.4 hours of continuous unscripted normal activities.Results show that using a simple algorithm employing Velocity+Impact+Posture can achieve a low false-positive rate of less than 1 FP day* (0.94FPs day*) with a sensitivity of 94.6\% and a specificity of 100\%.The algorithms were tested using unsupervised continuous activities performed by elderly subjects living in the community, which is the target environment for a fall detection device.",

author = "\{{\'O} Laighin\}, Gear{\'o}id",

year = "2010",

month = oct,

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language = "English (Ireland)",

booktitle = "Assessment of Waist-worn Tri-axial Accelerometer Based Fall-detection Algorithms using Continuous Unsupervised Activities",

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T1 - 2010 ANNUAL INTERNATIONAL CONFERENCE OF THE IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY (EMBC)

AU - Ó Laighin, Gearóid

PY - 2010/10/1

Y1 - 2010/10/1

N2 - This study aims to evaluate a variety of existing and novel fall detection algorithms, for a waist mounted accelerometer based system. Algorithms were tested against a comprehensive data-set recorded from 10 young healthy subjects performing 240 falls and 120 activities of daily living and 10 elderly healthy subjects performing 240 scripted and 52.4 hours of continuous unscripted normal activities.Results show that using a simple algorithm employing Velocity+Impact+Posture can achieve a low false-positive rate of less than 1 FP day* (0.94FPs day*) with a sensitivity of 94.6% and a specificity of 100%.The algorithms were tested using unsupervised continuous activities performed by elderly subjects living in the community, which is the target environment for a fall detection device.

AB - This study aims to evaluate a variety of existing and novel fall detection algorithms, for a waist mounted accelerometer based system. Algorithms were tested against a comprehensive data-set recorded from 10 young healthy subjects performing 240 falls and 120 activities of daily living and 10 elderly healthy subjects performing 240 scripted and 52.4 hours of continuous unscripted normal activities.Results show that using a simple algorithm employing Velocity+Impact+Posture can achieve a low false-positive rate of less than 1 FP day* (0.94FPs day*) with a sensitivity of 94.6% and a specificity of 100%.The algorithms were tested using unsupervised continuous activities performed by elderly subjects living in the community, which is the target environment for a fall detection device.

M3 - Conference Publication

BT - Assessment of Waist-worn Tri-axial Accelerometer Based Fall-detection Algorithms using Continuous Unsupervised Activities

ER -

2010 ANNUAL INTERNATIONAL CONFERENCE OF THE IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY (EMBC)

Abstract

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