WIISEL: Wireless Insole for Independent and Safe Elderly Living (WIISEL)

Published on: 18/09/2013
Document

WIISEL aims to develop an unobtrusive and wearable system to measure risk of falls in the elderly population, by continuously monitoring gait and fall risk and providing information to users, careers, families and clinicians on long term fall risk assessments.

The idea is that elderly people put a specifically designed insole in their shoes, which monitors their walking pattern.

The WIISEL system will enable clinicians to quantitatively evaluate and monitor fall risk in elderly patients, in the home and community environment, mostly reflecting everyday life behavior.

The goals of the finished WIISEL system are as follows:

  1. Constant Monitoring: To provide a wearable continuous monitoring device which can quantify fall risk by analyzing spatial- temporal aspects of gait and balance using the WIISEL insole.
  2. A research tool: A useful device for assessing gait in different conditions and simulated everyday life activities. The system can be used for gait analysis unconstrained to a laboratory setting and correlate gait parameters and patterns.
  3. Ease Burden on Resources: the system will enable remote monitoring of the person and thereby ease the burden of traveling to the clinic, and provide online care following the principle of telemedicine.
  4. Increase Awareness and Decrease the Fear of Falling: The system can provide information to the user on his gait and fall risk, which could enhance the user to become conscious of their increased risk of falling and take practical steps to decrease this fall risk thereby decreasing the fear of falling and subsequently improving mobility and an independent lifestyle.

Policy Context

According to the European Union, by 2050 the number of people in the EU aged 65 and above is expected to grow by 70 % and the number of people aged over 80 by 170 %. It is a fact the ageing of Europe’s population is a challenge for the European social and health systems. Age is a major risk factor for fall injury. 30 % of people over 65 and 50 % of those over 80 years fall each year, and older adults who fall once are two to three times as likely to fall again within a year.[1]

A system like WIISEL, that in an unobtrusive way will allow to analyse movement, posture and activity of the elderly population by extracting a direct and continuous information from feet pressure, is beyond any doubt of utmost importance. It will help to decrease the incidence of falls among the elders, allowing them to live longer independently at home and thus decreasing care provision, ambulatory and clinical costs.

The project is co-funded by the European Commission (FP7-ICT).

[1] Skelton D, Todd C. What are the main risk factors for falls amongst older people and what are the most effective interventions to prevent these falls? How should interventions to prevent falls be implemented? Copenhagen, World Health Organization, Europe, 2004 http://euro.who.dk/HEN/Syntheses/Fallrisk/20040318_1

Description of target users and groups

Caregivers, elderly population, etc.

Description of the way to implement the initiative

The novel WIISEL architecture will communicate at two levels, first with a near element (e.g., smartphone), that can interact with the person. The second communication will be with a remote control management system. This remote control system incorporates an intelligent prediction system that aims to discover patterns and make predictions based on historical and real-time daily behavioural data. In other words, the system is self-learning and user-friendly.

This self-learning system will facilitate the assessment of fall risk by a gait and activity pattern recognition. This recognition will interact with the clinicians and the user enabling prevention interventions like rehabilitation exercises monitoring or recognition of the fear of falling by reduction of activity, and thus permitting a corrective intervention.

Technology solution

Thanks to a wireless system and chips built into the insole, the data captured by the movement of the foot are sent to a mobile device or computer, so that the doctor, caregiver or nurse, can follow the evolution of the patient, to know if he/she follows correctly the rehabilitation or if he/she returns into bad habits that increase the risk of falling. If this occurs, an alert is sent to the responsible caregiver.

Technology choice: Proprietary technology, Standards-based technology, Open source software

Main results, benefits and impacts

It is anticipated that this new technology will enable preventing falls in elderly population in general. It will drive a paradigm shift and empower new clinical and research opportunities, ultimately leading to a reduction in the burden of falls, improved health-related quality, and economic benefits for EUs healthcare system that is faced with caring for a growing elderly population.

More specifically, it is expected that:

  • Elderly have less fear of falling
  • They maintain daily activity
  • Physical therapy is better accepted and more efficient
  • Elderly can stay at home and be independent for longer time
  • Quality of life improves for elderly and their family, friends and caretakers
  • Health and care provision costs decrease and public systems become more sustainable
  • Europe becomes world leader in Technologies for elderly

Insole prototype at this stage:

Return on investment

Return on investment: Not applicable / Not available

Track record of sharing

The consortium aims at providing a new insole to continuously collect data about gait and balance, and will set a self learning analysis framework and data base to collect gait data as a worthwhile contribution to research.

Part of the developments obtained in the project will be available as open source; the consortium is interested in sharing knowledge and feeding such analysis framework and data base in order to enrich WIISEL outputs.

Lessons learnt

The project is still at an intermediate stage, and the consortium will make lessons learnt available while the technical developments and validation trials are progressing. Some lessons learnt so far:

  • It is crucial to take into account the expertise from the gait analysis experts, as well as the needs from the end users, from the very beginning, for the development of the system.
  • Ethical and legal requirements must be explored in each country well in advance, in order to apply for ethical approvals in an efficient way. They will depend both on the kind of device, and what is meant to be validated during the trials.
  • It is very important to make key decisions in a timely manner, and if needed, implement the planned contingency plans in order to avoid delays in the next tasks. 
Scope: Pan-European