OPDEMIVA: An integrated assistance and information system for elderly with dementia

Current Directions in Biomedical Engineering

Hirtz

2017

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Abstract:The remote determination of vital parameters can contribute to the field of ambient assisted living (AAL) to face the challenges of a steadily ageing society. In this study, we examined the possibility to remotely measure the four vital parameters heart rate, respiration rate, oxygen saturation and blood pressure in AAL environments. For this, we evaluated the state of the art, implementations and concepts. While, the determination of heart and respiration rate is ready for usage, further attention has to be paid to the determination of oxygen saturation and blood pressure.

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Section: Introductionmentioning

confidence: 99%

An evaluation study of vital parameter determination with RGB cameras in the field of ambient assisted living

Current Directions in Biomedical Engineering

Hirtz

2017

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“…In a steadily ageing society, taking care for elderly plays a major role. In the last years, several technical assistance systems have been developed to help elderly people in their daily activities (Meinel et al, 2015) and to call help in case of emergencies (Wohlrab et al, 2015). These works show that it is possible to detect a fall in the home environment and inform relatives or caregivers.…”

Section: Introductionmentioning

confidence: 99%

Remote Heart Rate Determination in RGB Data - An Investigation using Independent Component Analysis and Adaptive Filtering

Proceedings of the 5th International Conference on Pattern Recognition Applications and Methods

Apitzsch

et al. 2016

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An emerging topic in the field of elderly care is the determination and tracking of vital parameters, such as the heart rate. This parameter provides important information about a person's current health status. Within the last years, various research focussed on this topic. The recognition of vital parameters is increasingly relevant for our ageing society. This paper presents a method to remotely determine the human heart rate with a camera. At this point, we suggest to use independent component analysis (ICA) and adaptive filtering for a robust detection. In our processing chain, we used different image processing techniques, e. g. face detection, and signal processing techniques, e. g. FFT and bandpass filtering, in this study. An evaluation with several probands, illuminations, frame rates and different heart rate levels showed that we could achieve a mean error of 4.36 BPM, which corresponds to CAND of 94.45 %, and a speed of 35 fps.

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Contact-Less, Optical Heart Rate Determination in the Field Ambient Assisted Living

Communications in Computer and Information Science

Hirtz

2019