OBJECTIVE: To examine the ability of wearable sensor-based in-home assessment of gait, balance, and physical activity (PA) to discriminate between frailty levels (nonfrail, prefrail, and frail).
Author Archive | Lis Boulton
Towards a social and context-aware multi-sensor fall detection and risk assessment platform
In this paper, a social- and context-aware multi-sensor platform is presented, which integrates information gathered by a plethora of fall detection systems and sensors at the home of the elderly, by using a cloud-based solution, making use of an ontology.
Pilot evaluation of an unobtrusive system to detect falls at night time
In this study, a previously proposed unobtrusive nighttime fall detection system based on wireless passive infrared sensors and furniture load sensors is evaluated in a pilot study involving three older subjects, monitored for a combined total of 174 days.
A comparison of cross-sectional and prospective algorithms for falls risk assessment
The purpose of this study was to compare the performance of sensor based falls risk assessment algorithms derived from cross- sectional (N=909) and prospective (N=259) datasets in terms of false positive rate.
