Fall detection system for elderly people using IoT and Big Data

Falls represent a major public health risk worldwide for the elderly people. A fall not assisted in time can cause functional impairment in an elderly and a significant decrease in his mobility, independence, and life quality. In this sense, we propose IoTE-Fall system, an intelligent system for detecting falls of elderly people in indoor environments that takes advantages of the Internet of Thing and the ensemble machine learning algorithm. IoTE-Fall system employs a 3D-axis accelerometer embedded into a 6LowPAN wearable device capable of capturing in real time the data of the movements of elderly volunteers. To provide high efficiency in fall detection, in this paper, four machine learning algorithms (classifiers): decision trees, ensemble, logistic regression, and Deepnets are evaluated in terms of AUC ROC, training time and testing time. The acceleration readings are processed and analyzed at the edge of the network using an ensemble-based predictor model that is identified as the most suitable predictor for fall detection. The experiment results from collection data, interoperability services, data processing, data analysis, alert emergency service, and cloud services show that our system achieves accuracy, precision, sensitivity, and specificity above 94%.

Fall detection system for elderly people using IoT and ensemble machine learning algorithm

"Healthy Aging" Concepts and Measures.

Cognitive frailty is the simultaneous clinical manifestation of both physical frailty and cognitive impairment. This paper aimed to propose and test an operational definition of cognitive frailty. The following specific aims were pursued: (i) to rate the prevalence of cognitive frailty; (ii) to evaluate differences in cognitive functioning among robust, pre-frail, and frail individuals; (iii) to examine the association of cognitive frailty with disability, in a sample of Italian community-dwelling older adults. Five hundred and ninety-four older adults (mean age 73.6 years, SD=5.8) were involved in this cross-sectional study. Cognitive frailty was operationalized using the Mini Mental State Examination (cut-off score equal or less than 25) for the evaluation of cognitive functions and the five criteria of the Cardiovascular Health Study (cut-off score equal or higher than 3) for the evaluation of physical frailty. Participants positive for both instruments were classified as cognitively frail. The outcome was disability measured with the Groningen Activity Restriction Scale. Descriptive statistics, one-way and two-way analysis of covariance (ANCOVA) were carried out. The prevalence rate of cognitive frailty was 4.4%. The one-way ANCOVA, controlling for age and gender, showed a significant difference (p< .001) among robust, pre-frail, and frail participants for the cognitive functioning. Moreover, cognitively frail individuals showed a difference (p<.001) in disability in comparison with non-frail participants. Our results are significant and provide empirical evidence about the usefulness of the cognitive frailty concept.

Cognitive Frailty in Italian Community-Dwelling Older Adults: Prevalence Rate and Its Association with Disability.

The Strategic Implementation Plan of the European Innovation Partnership on Active and Healthy Ageing (EIP on AHA) proposed six Action Groups. After almost three years of activity, many achievements have been obtained through commitments or collaborative work of the Action Groups. However, they have often worked in silos and, consequently, synergies between Action Groups have been proposed to strengthen the triple win of the EIP on AHA. The paper presents the methodology and current status of the Task Force on EIP on AHA synergies. Synergies are in line with the Action Groups’ new Renovated Action Plan (2016-2018) to ensure that their future objectives are coherent and fully connected. The outcomes and impact of synergies are using the Monitoring and Assessment Framework for the EIP on AHA (MAFEIP). Eight proposals for synergies have been approved by the Task Force: Five cross-cutting synergies which can be used for all current and future synergies as they consider overarching domains (appropriate polypharmacy, citizen empowerment, teaching and coaching on AHA, deployment of synergies to EU regions, Responsible Research and Innovation), and three cross-cutting synergies focussing on current Action Group activities (falls, frailty, integrated care and chronic respiratory diseases).

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Building bridges for innovation in ageing : Synergies between Action Groups of the EIP on AHA

Health is a multi-dimensional concept, capturing how people feel and function. The broad concept of Active and Healthy Ageing was proposed by the World Health Organisation (WHO) as the process of optimizing opportunities for health to enhance quality of life as people age. It applies to both individuals and population groups. A universal Active and Healthy Ageing definition is not available and it may differ depending on the purpose of the definition and/or the questions raised. While the European Innovation Partnership on Active and Healthy Ageing (EIP on AHA) has had a major impact, a definition of Active and Healthy Ageing is urgently needed. A meeting was organised in Montpellier, France, October 20-21, 2014 as the annual conference of the EIP on AHA Reference Site MACVIA-LR (Contre les Maladies Chroniques pour un Vieillissement Actif en Languedoc Roussillon) to propose an operational definition of Active and Healthy Ageing including tools that may be used for this. The current paper describes the rationale and the process by which the aims of the meeting will be reached.

G. Mercier

Papers

Operational definition of Active and Healthy Ageing (AHA): A conceptual framework