Semi-supervised near-miss fall detection for ironworkers with a wearable inertial measurement unit

Source: Automation in Construction, 2016, Vol 68 p. 194-202

Follow this link for the abstract

Date of publication: August 2016

Publication type: Journal article

In a nutshell: Accidental falls are the leading cause of injury and death in construction work. Near misses can provide valuable data about the causes as a proactive prevention measure, but collecting information can be challenging. This study aims to develop a method to automatically collect such data using wearable inertial measurement units, which could ultimately prevent fall accidents.

Length of publication: 8 pages

Some important notes: Please contact your local NHS Library for the full text of the article. Follow this link to find your local NHS Library.

Distinguishing causes of falls using various wearable tri-axial accelerometers

Source: Gait and Posture, online 2013

Follow this link for abstract

Date of publication: September 2013

Publication type: Journal article

In a nutshell: Lack of evidence on cause and circumstance of falls can be a barrier to effective prevention strategies. Previous studies have used inertial sensors to automatically detect falls to deliver medical assistance. This study expanded on the idea by developing and evaluating the accuracy of wearable sensor systems for determining the causes of falls.

Length of publication: 1 page

Some important notes: Please contact your local NHS Library for the full text of the article. Follow this link to find your local NHS Library.