FAll Repository for the design of Smart and sElf-adaptive Environments prolonging INdependent livinG

  • Contact person: Anisoara Ionescu
  • People involved: Anisoara Ionescu, Christopher Moufawad El Achkar, Alan Kevin Bourke
  • Partners:
  • Funding source:

A paramount challenge in today’s healthcare systems is promoting independent living, specifically with regards to the elderly population. Commonly occurring in old people, falls drastically reduce capabilities of independent living, leading eventually to institutionalization. As a consequence, falls account for an enormous cost in modern healthcare. To this end, FARSEEING emerges as a joint effort under the European Commission that tackles this problem from various standpoints: physical (e.g. gait and posture analysis), physiological (e.g. heart rate, blood pressure monitoring), technological (e.g. smartphone, smart home, telemedicine), clinical (e.g. complex rehabilitation) and psychological (e.g. persuasive technology), all with the best levels of data protection and ethical considerations.

Eleven academic and industrial institutions from seven European countries share a common goal under FARSEEING: this project is aimed at promoting better living conditions for the elderly by enhancing prediction, assessment and intervention modalities for a better understanding of falls, their consequences and potential ways to reduce their socio-economic burden on healthcare systems. FARSEEING incorporates an intensive use of ICTs (Information and Communication Technologies) focusing on smart phone applications and smart home environments, ultimately with the aim of building a digital repository of physical activity monitoring, fall detection and complex rehabilitation techniques that improve daily life in the elderly community. Novel methods shall be used that build on and enhance standard or classical techniques for monitoring and rehabilitation, such as the use of inertial sensors for physical activity quantification/detection and non-linear dynamics for rehabilitation. In this respect, FARSEEING will define a new state-of-the-art in global management of falls in the elderly.

Smart shoes for activity monitoring

Smart shoes to monitor daily physical activity were developed as part of FARSEEING to provide an unobtrusive wearable sensing solution. The system includes an inertial measurement unit (Physilog, GaitUp, CH) combining 3D accelerometer, 3D gyroscope, 3D magnetometer and barometer and a force sensing insole (IEE, LU) that measures the load distribution under the foot.

Using the data extracted from these sensors, an activity classification algorithm was built. The algorithm relies on movement biodynamics and has shown an accuracy of 97% in classifying basic activities such as sitting, standing and walking and more refined activity detail such as stair climbing, ramps and elevators. The smart shoes were tested by older adults performing activities of daily life in a semi-structured protocol as well as freely at home.

Stepping based VR exergame

A novel VR exergame was developed with the smart shoes, as part of the interventional aspect of FARSEEING. The goal of the game is to perform steps in different squares based on what is generated on the screen.

The game uses real-time signals from the smart shoes and performs online step detection to validate a correct step and reject an incorrect step. A neural network based step classifier has been devised to correctly detect the user’s steps and acheived good performances with >90% step classification accuracy.

Main publications

Conference proceedings

Moufawad el Achkar C., Major K., Lenoble-Hoskovec C., Paraschiv-Ionescu A., Krief H., Bula C., Aminian K., Instrumented shoes for activity monitoring in the elderly: measurement system and in lab validation. In 83eme Assemblée Générale de la SSMI, 20-22 May, Basel, Switzerland 2015

El Achkar, C.M.; Masse, F.; Arami, A.; Aminian, K., “Physical activity recognition via minimal in-shoes force sensor configuration,” Pervasive Computing Technologies for Healthcare (PervasiveHealth), 2013 7th International Conference on , vol., no., pp.256,259, 5-8 May 2013

Moufawad el Achkar C., Paraschiv-Ionescu A., Bourke A.K., Aminian K., Stair descent detection using foot-worn inertial sensors. 3DAHM 2014, Lausanne

Moufawad Al Achkar C., Smart shoes to promote active ageing. 2015 Global Young Scientists Summit @One-north, Singapore. Finalist of the Singapore Challenge

Bourke A.K., An inertial sensor based stepping exergame for the elderly, 11th Body Sensor Networks, Zurich, Switzerland, 16-19th June 2014.