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Ambient assistance service for fall and heart problem detection

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Abstract

Continuous monitoring of vital signs and activity measures has the potential to provide remote health monitoring and rapid detection of critical events such as heart attacks and falls. This paper proposes a multimodal system for monitoring the elderly at their homes. The system proposed contains three ambient assistance services (Fall detection, Heart disorder detection and Location) and an emergency service. A three-axis accelerometer, pulse oximeter and eight photoelectric sensors are applied for fall detection, cardiac problems detection and location respectively. The emergency service provides data fusion of this sensors and sends detailed information about the statue of the followed person to the doctor. This multimodal system is modeled by Colored Timed and Stochastic Petri nets (CTSPN) simulated in CPNTools. Experimental tests for each service have been performed on 10 subjects. The results show that falls can be detected from walking or standing with 87% of accuracy, 82% of sensitivity and 92% of specificity, from a total data set of 50 emulates falls and 50 normal activities daily living. The results obtained during the tests validate the detection of tachycardia with 100% of success. The location was done with 94% of sensitivity. The proposed system minimizes the false positive and false negative.

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Authors and Affiliations

  1. LRPE Laboratory, University of Sciences and Technology Houari Boumediene, BP 32 EL ALIA, 16111, Bab Ezzouar Algiers, Algeria

    Amina Makhlouf, Isma Boudouane & Nadia Saadia

  2. LISV Laboratory, University of Versailles Saint-Quentin-en-yvelines, 10-12 avenue de l’Europe, 78140, Velizy, France

    Amar Ramdane Cherif

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  1. Amina Makhlouf
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  2. Isma Boudouane
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Correspondence to Amina Makhlouf.

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Makhlouf, A., Boudouane, I., Saadia, N. et al. Ambient assistance service for fall and heart problem detection. J Ambient Intell Human Comput 10, 1527–1546 (2019). https://doi.org/10.1007/s12652-018-0724-4

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