IEEE J Biomed Health Inform - Fall detection in homes of older adults using the Microsoft Kinect.

Tópicos

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Resumo

A method for detecting falls in the homes of older adults using the Microsoft Kinect and a two-stage fall detection system is presented. The first stage of the detection system characterizes a person's vertical state in individual depth image frames, and then segments on ground events from the vertical state time series obtained by tracking the person over time. The second stage uses an ensemble of decision trees to compute a confidence that a fall preceded on a ground event. Evaluation was conducted in the actual homes of older adults, using a combined nine years of continuous data collected in 13 apartments. The dataset includes 454 falls, 445 falls performed by trained stunt actors and nine naturally occurring resident falls. The extensive data collection allows for characterization of system performance under real-world conditions to a degree that has not been shown in other studies. Cross validation results are included for standing, sitting, and lying down positions, near (within 4 m) versus far fall locations, and occluded versus not occluded fallers. The method is compared against five state-of-the-art fall detection algorithms and significantly better results are achieved.

Resumo Limpo

method detect fall home older adult use microsoft kinect twostag fall detect system present first stage detect system character person vertic state individu depth imag frame segment ground event vertic state time seri obtain track person time second stage use ensembl decis tree comput confid fall preced ground event evalu conduct actual home older adult use combin nine year continu data collect apart dataset includ fall fall perform train stunt actor nine natur occur resid fall extens data collect allow character system perform realworld condit degre shown studi cross valid result includ stand sit lie posit near within m versus far fall locat occlud versus occlud faller method compar five stateoftheart fall detect algorithm signific better result achiev

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